Engineering Research Project Planning
Engineering Research Project Planning
Unit Code: ENRP20001
Term 2, 2020
Literature Review
Power Quality Issue at High PV Penetration in a Low/High Voltage Distribution System
Student Name: BHajjs KOOMIEL
Student ID: 12079300
Supervisor: Dr Narottam Das
2011680394970
School of Engineering and Technology
Central Queensland University, Melbourne Campus
Australia
Submission Date: 27/08/2020Table of Contents
TOC o "1-3" h z u Chapter 1: Introduction PAGEREF _Toc18313060 h 51.1 Introduction and Background PAGEREF _Toc18313061 h 51.2 Research Question PAGEREF _Toc18313062 h 91.3 Project Aim PAGEREF _Toc18313063 h 91.4 Project Objectives PAGEREF _Toc18313064 h 91.5 Limitation PAGEREF _Toc18313065 h 101.6 Inclusion and Exclusion PAGEREF _Toc18313066 h 10Chapter 2: Literature Review PAGEREF _Toc18313067 h 112.1. Growth Statistics of Solar PV Systems. PAGEREF _Toc18313068 h 112.2. Electric Grid-connected Solar PV System PAGEREF _Toc18313069 h 132.3.1. Solar PV System. PAGEREF _Toc18313070 h 132.3.2 Battery PAGEREF _Toc18313071 h 142.3.3 Boost Converter PAGEREF _Toc18313072 h 152.4. What is PV penetration? PAGEREF _Toc18313073 h 162.5. Power Quality Issues in LV distribution systems PAGEREF _Toc18313074 h 162.5.1 Voltage Fluctuation/ Flicker PAGEREF _Toc18313075 h 162.5.2 Voltage rise PAGEREF _Toc18313076 h 172.5.3 Voltage Unbalance PAGEREF _Toc18313077 h 182.5.4 Harmonics Distortion PAGEREF _Toc18313078 h 192.5.5 Voltage seg/ swell PAGEREF _Toc18313079 h 202.5.6 Low/high Power factor PAGEREF _Toc18313080 h 212.6. Mitigation techniques of power quality problems PAGEREF _Toc18313081 h 212.6.1 Static Synchronous Compensator (STATCOM) PAGEREF _Toc18313082 h 222.6.2 Distribution Static Compensator (DSTATCOM) PAGEREF _Toc18313083 h 222.6.4 UPQC (Unified Power Quality Conditioner) PAGEREF _Toc18313084 h 242.6.7 Energy Storage system PAGEREF _Toc18313085 h 252.7. Technologies for Application of Energy Storage. PAGEREF _Toc18313086 h 262.7.1 Lithium-ion (Li-ion) Batteries. PAGEREF _Toc18313087 h 262.7.2 Supercapacitors. PAGEREF _Toc18313088 h 272.8. Distributed solar PV system with Energy storage system. PAGEREF _Toc18313089 h 282.8.1 Peak power shaving with photovoltaic systems and Li-ion battery storage PAGEREF _Toc18313090 h 292.9. Solar PV with Battery and Supercapacitor. PAGEREF _Toc18313091 h 292.10. Why Batteries Energy Storage System? PAGEREF _Toc18313092 h 302.11. Simulation Platform for Improving Power Quality Issue. PAGEREF _Toc18313093 h 31Chapter 3: Methodology PAGEREF _Toc18313094 h 323.1 Reactive Power Control Method PAGEREF _Toc18313095 h 323.2 MPPT (Maximum Power Point Tracking) Method. PAGEREF _Toc18313096 h 323.3 Proposed Optimization Method. PAGEREF _Toc18313097 h 333.3.1. Preparation Stage. PAGEREF _Toc18313098 h 333.3.2. The first stage of proposed optimization. PAGEREF _Toc18313099 h 333.3.2 Second stage of proposed optimization. PAGEREF _Toc18313100 h 34Chapter 4: Conclusion PAGEREF _Toc18313101 h 37References PAGEREF _Toc18313102 h 38Appendix 1: How and where I addressed feedback given on the Project Scope. PAGEREF _Toc18313103 h 41
List of Figures
TOC h z c "Figure" Figure 1: Global Capacity of Solar PV Generation during 2004 2014 (Global Status Report (REN21-2015)). PAGEREF _Toc18313121 h 7Figure 2: Grid-connected Solar PV Acceptance in Australia (Australian PV Institute live report on market analyse). PAGEREF _Toc18313122 h 12Figure 3: Power Grid-Connected Solar PV with Battery Storage and Load Ru, Kleissl, and Martinez, 2012. PAGEREF _Toc18313123 h 13Figure 4: Equivalent circuit of solar PV (Dharavath, Raglend, and Manmohan, 2017). PAGEREF _Toc18313124 h 14Figure 5: Diagram of DC-DC Boost Converter (Dharavath, Raglend, and Manmohan, 2017). PAGEREF _Toc18313125 h 16Figure 6: Voltage waveform showing Fluctuation/ Flicker (Tekale, et al., 2017). PAGEREF _Toc18313126 h 17Figure 7: Voltage Profile with the first column without PV and a second column with PV (Demirok, et al., 2009). PAGEREF _Toc18313127 h 18Figure 8: Voltage Unbalance at LV distribution network (Tekale, et al., 2017). PAGEREF _Toc18313128 h 19Figure 9: 3rd and 5th Harmonics in voltage or current waveform (Tekale, et al., 2017). PAGEREF _Toc18313129 h 20Figure 10: Voltage waveform showing voltage sag (Tekale, et al., 2017). PAGEREF _Toc18313130 h 21Figure 11: Voltage waveform showing voltage swell (Tekale, et al., 2017). PAGEREF _Toc18313131 h 21Figure 12: DSTATCOM System Configuration (Khadem, Basu, Conlon, 2010). PAGEREF _Toc18313132 h 23Figure 13: Block diagram od dynamic voltage restorer (Dharavath, Raglend, and Manmohan, 2017). PAGEREF _Toc18313133 h 24Figure 14: Block Diagram of UPQC (Khadem, Basu, Conlon, 2010). PAGEREF _Toc18313134 h 24Figure 15: Schematic of On-Load Tap Changing Transformer (Haque, and Wolfs, 2016). PAGEREF _Toc18313135 h 25Figure 16: Energy storage technologies in terms of efficiency and durability (Nourai, 2002). PAGEREF _Toc18313136 h 26Figure 17: Double layer supercapacitor (Nourai, 2002). PAGEREF _Toc18313137 h 28Figure 18: Grid-connected Solar PV with and without Energy storage system (Hoff, Perez and Margolis, 2007). PAGEREF _Toc18313138 h 29Figure 19: Equivalent Circuit of Super Capacitor (Zahedi, 2011). PAGEREF _Toc18313139 h 30Figure 20: Electrical circuit of Solar PV Module with Super Capacitor (Zahedi, 2011). PAGEREF _Toc18313140 h 30Figure 21: Reactive Power Capability between 0.85 lagging and 0.85 leading Power Factor (Demirok, et al., 2009). PAGEREF _Toc18313141 h 33Figure 22: Proposed optimization method flowchart. PAGEREF _Toc18313142 h 37List of Table
TOC h z c "Table" Table 1: Energy Storage Technology. PAGEREF _Toc18313215 h 27Table 2: Project Proposal Feedback PAGEREF _Toc18313216 h 42Abbreviations and Acronyms
PV Photovoltaic
DG Distributed Generation
LV Low Voltage
PQ Power Quality
DER Distributed Energy Sources
RMS Root Means Square
PCC Point of Common Coupling
ESS Energy Storage System
BESS Battery Energy Storage System
STATCOM Static Synchronous Compensator
DSTATCOM Distributed Static Compensator
DVR Dynamic Voltage Restorer
OLTC On-Load Tap Changer
UPQC Unified Power Quality Conditioner
MPPT Maximum Power Point Tracking
MATLAB Matrix Laboratory
AUTOCAD Automated Computer-Aided Design
Chapter 1: Introduction1.1 Introduction and BackgroundIn the last few decades, with the increasing price of fossil fuels and frequently changing atmosphere have forced to start using electricity from renewable energy sources such as wind and solar. Moreover, solar energy is one of the best methods for generating electricity from the sun. The main reason for adopting solar PV is the high efficiency of the solar PV system and inverter, and low initial cost due to government benefits like subsidies and feed-in tariff etc. However, electricity suppliers are facing problems with the quality of power at the customer level. Due to the development of the power electronics stream, several solutions are obtained to resolve the fluctuation observed in the distribution network to improve possible power quality to the customer. Moreover, the world's population, energy consumption, and economies are increasing speedily than ever. It is predicted that the electricity demand will be increased by 40% in 2040 (Matthieu Metayer, Christian Breyer, and Hans-Josef Fell, 2015). A requirement of present energy is supplied by the burning of fossil fuels. In contrast, these energy sources are insufficient to meet the increasing demand for electricity. In addition to this, the usage of fossil fuels in the production of electricity generates environmental issues such as emissions of CO2 (Greenhouse gases) and climate change. Hence, many countries are approaching towards the utilization of non-conventional energy sources for sustainable, inexpensive, and clean power supply. For future electricity requirement, solar, wind, hydro (renewables) are assumed to supply a significant percentage. In 2013, renewable energy delivered nearly 19.1% of global energy consumption, and the predicted renewable power generation has augmented 22.8% of global power-producing capacity and the power installation capacity reached at 657 GW in 2014 (Adib et al, 2015).
In the last few years, distributed generation (DG) based on renewable source has been increasing due to their viability. Due to lowest capital costs and rapidly increment of technological advancement, among all DG technologies, solar PV is world widely fastest-growing system. As per global status report (REN21-2015), Solar PV installed capacity worldwide had increased to 177 GW in 2014 whereas, total renewable power capacity worldwide was 657 GW. Ideally, Australia is suitable for the production of solar power since a high isolation level. Recent research (AEMO, 2012) has indicated that Australia's energy will mainly dependent on rooftop solar PV system soon, as in 2030, Australia's 21% need of electricity covered by solar PV.
Figure SEQ Figure * ARABIC 1: World-wide Capacity of Solar PV Generation during 2004 2014 (Global Status Report (REN21-2015)).
The solar PV system can be connected to transmission and distribution networks (both sided). In a power system, the application of solar PV is classified as off-grid and grid-connected.
Off-grid PV system: Power can provide to the remote loads, which cannot enter to the power generation. As this system entirely disconnected from the grid can integrate with an energy storage system.
On-grid PV system: Grid-connected PV system install at a near location of the power network, which can eliminate the costs of transmission and distribution network. However, in this system network become active as the customer can export and import power to the grid which leads to voltage unbalance and voltage rise problem. With energy storage system, when power generation exceeds the limit of user consumption instead of exporting the energy back to the grid, it charges the battery which can be used at night time.
The capacity of the PV installation is limited in the LV grid-connected system due to this voltage rise issue occurs with high PV penetration. In addition to this, solar energy is dependent on the sun rays, continuous solar irradiation, as well as climate changes, can raise voltage fluctuation. Moreover, voltage regulation issues occur due to seasonal effects as the solar system is intermittent. Furthermore, solar PV uses an inverter to convert dc to ac from PV panels, which can insert harmonics into the system. There is also reverse power flow in LV distribution feeder during the situation of high production of solar PV and low demand. There are myriad of other reasons of power quality issue such as growth in solar PV system and benefits from governments subsidies, reduction in solar PV installation cost. Therefore, it is important to investigate the power quality issue with high PV penetration in LV distribution system and to provide a suitable solution for improving the power quality of the system.
When solar PV integrated with LV distribution grid, Power quality issue happens in this system. This issue occurs due to nonlinearity of loads, faults and different weather condition. The term power quality is to maintain sinusoidal waveform of voltage and frequency which is purely free from any distortion. The main goal of power companies to provide uninterrupted power to their customer.
Main purpose of this research project is to maximize solar PV generation and minimize power quality issues and power losses in the LV distribution system. To achieve the solution of my research question, I will design solar PV system with energy storage systems such as battery and supercapacitor as this system will help to integrate solar power into the grid and eliminate fluctuation and power quality issue. I will implement this concept in MATLAB simulation platform. We can regulate power between the PV generation and grid by using battery ESS to improve the power quality of the system. Many studies show that to reduce fluctuation of voltage, battery storage system in a PV network has an economic benefit (Sugihara et al, 2012). The capacitor provides better voltage control when the sudden voltage rises. Power quality-related resources give a link between past and future research gap, Energy storage system such as batteries and capacitors give an accurate result, transportable due to lightweight, fast charging time but its cost is very high. For that more research is required to reduced battery cost and get desired RMS voltage as an output.
Stakeholder of this research project is distribution companies, customers, suppliers, and regulators, Energy Australia who will get benefit from this project. They will give their contribution to solve this issue and understand and accept the future value of this result project.
Keywords: Distributed generation, distribution network, Energy storage system, Power quality, Power grids, PV penetration, Renewable energy.
1.2 Research Question
Myriad of articles available on power and energy stream which is a subdiscipline of renewable energy stream among all this power quality is a very interesting topic for research (Adib et al, 2015). Suitable research project title of this issue is Power quality issue at high PV penetration in a low voltage distribution system. The main purpose of a power system is to produce electricity and supply that power to the customer. Since electric power was invented, power quality issue has been introduced. It has become a well-known problem from few years as loads are affected. Power quality issue occurred in low voltage distribution system due to integrating solar PV system with an existing power grid. The focus of these research projects is on power quality issue such as voltage rise and drop, voltage and frequency regulation, poor power factor and reverse power flow due to high PV penetration in low voltage distribution system. My research question related to this topic is How power quality is affected by high solar PV penetration and how it can be mitigated in the LV distribution system?'. This question relates to my project title. To solve this question, I will use a battery storage system, it will be charged at day time when energy demand is less than generation and battery will be discharged at night time. I will also distinguish RMS voltage of obtained result with PV penetration and without penetration.
1.3 Project AimWhen, renewable energy integrates with the electrical grid, at that time power quality issues such as Voltage rise and drop, voltage regulation, poor power factor and reverse power flow occurred due to high renewable penetration. The main reason for this power quality issue is the intermittent nature of renewable energy, fluctuated load demand and energy generation, and non-linearity of loads. By using storage energy systems, PQ issues will be mitigated at Low voltage distribution network and improve efficiency and generation of renewable energy at the customer level.
1.4 Project ObjectivesThe main objective of this research project is to investigate and understand the impact of high PV penetration on power quality of LV distribution system. The following objectives will be achieved during the planning and implementation of this research project.
Review the issue with high PV penetration in grid integration of solar PV through literature review.
Modelling low/medium voltage distribution network with solar PV system using MATLAB simulation platform.
Design a range of storage devices that might be used with a solar PV system to resolve the problem of power quality.
Develop new control methodology to improve power quality and increase power feed in the capacity of voltage feeder.
Enhance efficiency, solar power generation and reduce CO2 emission.
Expand level of reliability (power quality level) to supply lossless power to the customer.
1.5 LimitationControlling power quality issue at high PV penetration in a low voltage distribution system with an energy storage system may be challenging. The cost of Lithium-ion (Li-ion) batteries is very high. Li-ion batteries give the greatest ability for future development, as it has a small size and lightweight. The Li-ion batteries offer the highest energy density and storage efficiency close to 100%, which makes them ideally suited for portable devices (Divya & stergaard, 2009, p.513). Modelling of LV distribution system with solar PV may be possible in MATLAB simulation platform. However, implementing this concept practically required more research, knowledge and development in the field of engineering.
1.6 Inclusion and ExclusionThere are numerous quality issues such as voltage rise and drop, voltage fluctuation, poor power factor, harmonics, voltage unbalance, flickers, voltage sag, reverse power flow and many more. Among all these issues, major concerning issues which are going to be solved in this research projects are the voltages rise and drop and reverse power flow, and voltage regulation. The appropriate method used with a battery storage system to get maximum output. By controlling these issues, grid-connected equipment is protected and overall energy will be saved. Other issues are considered in an exclusion for this research project as limited time and resources to complete this project. For that more research, knowledge and development is required in the field of engineering to bridge the gap between past, recent and future research.
Chapter 2: Literature ReviewThe necessity to mitigate carbon gas emission due to heavily usage of non-renewable resources have led to large scale growth of sustainable energy generation in power grids. Nowadays, the installation of solar photovoltaic system has been increased dramatically as compared to the other clean resources such as hydroelectric, geothermal, tidal systems, wind and biomass. This increment is predicted due to increasing government subsidies, high electricity prices, decrease PV installation cost and sustainable to the environment. It is also noticed that the congestion in feeder might be occurred due to high penetration of distributed energy sources (DERs), such as solar and wind power system is big concern for energy distribution companies, planners and operators of the grids. Due to increase of PV penetration into the distribution network, solar PV might cause an issue of power quality such as voltage regulation, frequency regulation, reverse power flow, voltage rise and drop. To resolve these issues, need to apply different appropriate control methods and improve the overall efficiency of power grid. By using an accurate technique, the capacity of power supply could be enhanced and increase the instability of low/medium type distribution feeders to control the fluctuation of solar PV power of the grid. Hence, smart batteries and supercapacitors used with solar PV generator for improving the reliability of the distribution network. In this chapter, first, general summary of the solar system with the statistics of penetration on power systems in different countries are described. Secondly, detailed power quality issue with high renewable penetration in a low or medium system are described. Finally, various methods apply to improve the power quality are provided in this literature.
2.1. Growth Statistics of PV Systems.Solar technology has been used for integration into LV and MV distribution systems due to the availability of sun rays and its possibility as compared to the other types of renewable sources. In the last five years, the installed capacity of low voltage grid-connected solar PV system installation has developed significantly. In 2015, the installation capacity of solar PV has reached about 7.3 GW in the USA. The total increasing installed capacity reached around 25 GW, and a total 29.5% was supplied from new power production capacity (Ghosh and Rahman, 2016). India has a target to generate approximately 175 GW of solar power till 2021-22, all over the world this target is highest (Buckley, 2016). According to IEEFA (Institute for Energy Economics and Financial Analysis) report, from solar resources, 100 GW of energy is predictable.
In Australia, the significance of the research program in solar PV is showing rapid grawth and its aim to improve penetration to overcome future energy requirement. It would be predicted that in 2020, renewable power produces 45,000 GWh and that signifies 25% of total power generation in 2020 (Byrnes, et al., 2013). By the end of 2015, the installed capacity of PV system reached approximately 4.7 GW.
Figure SEQ Figure * ARABIC 2: Grid-connected Solar Photovoltaic Acceptance in Australia (Australian PV Institute live report, 2019).Solar PV installation capacity in 2031 will be increased 12 times greater than the current installation capacity of solar PV as per the record of the Australian Energy Market Operator (AEMO, 2012). This estimated installation capacity might lead to several impacts on the existing distribution system, which impose to a power quality issue, stability, reliability and protection of the system. As per the Energex distribution annual planning (EDAP) report (2015), the level of PV penetration is already producing PQ issues on the current feeder and it is anticipated to overstate the problems in coming years. This growth is due to the reduction of solar PV cost, Intensive programs from governments and increasing the price of electricity. Hence, it is important to investigate the power quality issues and its impacts of a PV system on the distribution network and to use preventive method to enhance the current network capability to simplify more PV integration.
2.2. Electric Grid-connected PV SystemGrid-connected solar PV converts sun rays into electricity (AC). This system requires panels, boost converter, energy storage, inverter and isolation transformer.
Power can be taken from the power grid and returned to the back. For example, suppose that the cost for sales and buys at time t signified as Cg(t)($/Wh). When commercial buildings connected with the PV system that would consider a storage system (battery) usually pay time-of-use electricity price (Cg(t) 0 depends on t). Pg(t)(W) represents the electricity replaced with the grid.
Where,
Pg(t) > 0 if energy taken from the grid.
Pg(t) < 0 if energy returned to the grid.
If power prices are positive then it means power taken from the grid, and if price are negative means power returned to the grid.
Figure SEQ Figure * ARABIC 3: Power Grid-Connected Solar Photovoltaic with Storage and Load (Source: Ru, Kleissl, and Martinez, 2012).2.3.1. Solar PV System.61785548768000Because of the photovoltaic effects solar power is produced. Solar cells are managed in series or parallel with the array, solar cell is a non-linear device.
Figure SEQ Figure * ARABIC 4: Equivalent circuit of solar PV (Dharavath, Raglend, and Manmohan, 2017).The model for PV array with relation of current and voltage is getting by using bellowing equation.
Vpv=nKT q ln ISCIPV+1 ... (2.1)
Ipv=ISC-IPV0[exp(qVpv+IPVRSNSKTn-1]-Vpv+ISCRSRsh (2.2)
Where,
IPV = Solar PV current,
VPV= Solar PV Voltage,
K= Boltzmann Constant,
T=Temperature of cell,
ISC= Short circuit current,
IPV0= Saturation current of diode,
q = electric charge in coulombs),
NS= Number of cells in series,
Rsh= Resistance both series and shunt,
n= identify factor.
2.3.2 BatteryDynamic equation for battery is
dEB(t)dt= PBt (2.3)
Where,
EB(t)(Wh): At time t, amount of power stored in battery.
PB(t)(W): Rate of Charging and Discharging.
PB(t) > 0: charging
PB(t) < 0: discharging
As per battery age, C(t)(Wh) used to signify the capacity of the battery at time t. At t0 time, battery capacity is Cref. C(t)(Wh) shows the capacity loss at time t.
Therefore,
Ct=Cref-Ct (2.4)
To satisfies, battery ageing following equation is used.
dC(t)dt=-ZPB(t), if PB(t) < 00, &Otherwise ... (2.5)
The capacity loss only occurred when energy is discharged from the battery. We consider following limitation of battery.
The battery charging EB(t) should satisfy
0 EB(t) C(t) = Cref C(t),
Charging and discharging rate of the battery should satisfy
PB min PB(t) PB max,
Where, PBmin < 0 is the higher discharging rate of a battery,
PB max > 0 is the higher charging rate of the battery.
PB max=- PB min CtTc=Cref - CtTc (2.6)
Where Tc > 0 is the minimum time required for charging the battery from 0 to C(t) or discharge the battery from C(t) to 0.
2.3.3 Boost Converter449580102806500Main aim to connect boost converter is to step-up the voltage of solar system. This converter is used for stepping up the natural voltage of solar PV. Maximum Power Point Tracking (MPPT) controlling method is used for switching operation of this converter and it can also track the maximum power from the solar.
Figure SEQ Figure * ARABIC 5: Diagram of DC-DC Boost Converter (Dharavath, Raglend, and Manmohan, 2017).2.4. What is PV penetration?There are two types of PV penetration, the first one is Installed penetration is the percentage of installed solar capacity to the installed total solar generation capacity on the grid. The second one is Operational penetration' is the percentage of installed solar capacity to the total solar capacity at a significant time. It may change with isolation and load changes. Level of penetration should not badly impact on a grid voltage when distributed solar photovoltaic should not goes higher than 2.5 KW per house (Baran et al., 2012). High PV penetration of solar PV can affect voltage instability. In grid-connected solar PV, intermitted nature of PV is the main reason for voltage fluctuation.
2.5. Power Quality Issues in distribution systemsThe major solar penetration impact on-grid could be described as voltage, current and frequency fluctuation and unbalance, reverse power flow, flickers, harmonics unbalance, poor power factor and so on. This issue mainly depends on the level of penetration and photovoltaic location in the feeder. Voltage level may be affected by the high level of PV integration inject energy to the feeder. Here, the distribution network is working as an active network therefore, power quality problems related to the high level of penetration in the LV network will be explored in the following sections:
2.5.1 Voltage Fluctuation/ FlickerVoltage fluctuation means the fluctuation of voltage where amplitude adapted by a signal between 0 to 30 Hz frequency which leads to frequency on-off and loads fluctuation. Limited predictability and intermittent nature of solar PVs can lead to voltage fluctuation and voltage unbalance (voltage quality) in a power grid. Alternations between clouds and sunlights can be introduced this issue into the system for a short or long period of time. These issues also increase the chances of malfunction of voltage regulation equipment of distribution feeder. Hence, this issue can affect the photovoltaic voltage output in PCC (point of common coupling). Problems related with the voltage of solar PV connected with grid described as voltage unbalance, Voltage rise and drop, and Voltage flicker (Karimi, et al., 2016).
Figure SEQ Figure * ARABIC 6: Voltage waveform showing Fluctuation/ Flicker (Tekale, et al., 2017).2.5.2 Voltage riseSolar PV with high PV penetration may considerably affect the voltage of the LV distribution system by increasing the voltage above the limit at high irradiation condition. Impact of voltage is the main concern and a challenging issue for designing and planning of LV distribution network. Change in voltage profile is dependent on the number of feeders connected on the same substation, system configuration and load pattern (Katiraei, Mauch, and Dignard-Bailey, 2007). In the distribution system, photovoltaic arrays are located close to the loads can affect the voltage profile, power flow reduction, and minimize losses. Voltage rise and regulation issue in distribution network depend on the penetration level as follow:
If photovoltaic penetration level is low (5%), PV inverter does not make any effect on the networks regulation during peak demand.
63055584836000If photovoltaic penetration level is medium (10%), voltage of photovoltaic inverter can help to minimize the capacitors size by 40%. If PV penetration level is high (30-50%), inverters may be enough to give voltage support to the networks.
Figure SEQ Figure * ARABIC 7: Voltage waveform with the first column without using solar photovoltaic and a second column with solar photovoltaic (Demirok, et al., 2009).Voltage regulation derives has been used to control voltage of the feeder such as energy storage devices, OLTC, DSTATCOM, DVR, and STATCOM (Chidurala, 2016). The objective of these devices is to control or regulate the voltage at the demand side and set the high voltage along the feeder. The distribution system is becoming a bi-directional power flow system because of the integration of solar photovoltaic into the power grid. The major technical issue is a considerable increase the voltage level because of the reverse power flow and integration of number of photovoltaic generators in the utility grid. Due to unpredictable reverse power flow, voltage management limit of distribution operators can generate voltage rice and drop issue. Hence, the voltage rises, and regulation problems are more concerning issues in LV distribution system in high penetration and should be investigated.
2.5.3 Voltage Unbalance
Another issue in the feeder with high photovoltaic penetration is reverse power flow this might generate some voltage unbalance. Generally, distribution suppliers are supplying loads along the network to resolve the unbalance issue, due to unequal power usage by the consumers lead to unbalance in voltage level at the load side. Voltage unbalance is lower at the beginning of the distribution network than the ending (Chidurala, 2016). Voltage unbalances in LV distribution network can harmful for household electronics equipment and minimize the lifespan of household appliances. In LV distribution feeder, the unbalanced voltage on PCC can be increased with the PV system. Voltage unbalance is described by Voltage Unbalance Factor (VUF).
VUF=v-v+ 100% ... (2.7)
Here, V+ the positive voltages and V- is the negative voltages. The acceptable limit of unbalance factor is up to 2%. Voltage unbalance factor at point of common coupling exceeds the limit of 2% from 12.00 p.m. to 2.00 p.m. as highest photovoltaic output due to this voltage unbalance occurs during this period (Karimi, et al., 2016). To enhance voltage unbalance, control algorithm-based DVR and DSTATCOM method is used. By using this technology, a considerable amount of VUF reduced in LV network. Voltage unbalance is a variation in a three-phase system voltage, where magnitude and phase-angle of voltage are a difference with each other, which cause three phases of the system due to incorrect distribution loads.
Figure SEQ Figure * ARABIC 8: Voltage Unbalance at LV distribution network (Tekale, et al., 2017).2.5.4 Harmonics DistortionHarmonics distortion in the waveform of current and voltage has to become serious issue due to high integration of solar photovoltaic system in the electrical grid, the nonlinearity of loads, and increasing the use of electronics devices. High harmonics voltage occurs due to high R/X ratios and impedance of LV distribution system (Chidurala, 2016). This power quality issue mainly occurs because of the change of direct current to synchronize with the main supply through PV inverters. PV inverters are the key source to inject current harmonics into the network. This distortion also causes the total harmonics distortion (THD) in the network. PV inverter's maximum penetration level can be installed based on an satisfactory level of harmonics voltage distortion (Latheef et al., 2006). Harmonics at acceptance range of PV penetration level is defined as:
Plevel=NpvisNdistSinvStx (2.8)
Where,
Npvis is the number of inverters per network.
Ndist is the number of low voltage feeders connected to the transformer.
Sinv is the inverter rating (MVA).
Stx is the transformer rating of LV and MV (MVA).
Figure SEQ Figure * ARABIC 9: 3rd and 5th Harmonics in voltage or current waveform (Tekale, et al., 2017).Harmonics means non-sinusoidal shape of voltage and current waveform. This waveform changes with the different sine-waves of the sun with phase, magnitude and frequencies are multiple of power-system frequency.
The 3rd harmonics depicts peak during morning and evening time. The 3rd harmonics magniture in this period is nearly 70% of the fundamental current which is significantly higher. There is different level like distribution and transmission and the user end equipment where the solution of power quality take place. To mitigate harmonics issue in distributed networks generally filter is used.
2.5.5 Voltage seg/ swell
In a utility network, voltage sag/swell is considered as the main concerning power quality problem. Voltage sag/ swell is due to three-phase unsymmetrical and symmetrical faults will trip the circuit breaker which leads losses of power supply (Chidurala, 2016). Practically, due to unwanted faults, solar photovoltaic system disconnects solar PV from the electrical grid this will generate voltage sags on highly loaded phases and voltage swells at lightly loaded phases of the system. This issue also occurs due to altering weather pattern and could transient. Hence, sudden changes in solar rays can generate large fluctuation for small-time, leading to a voltage sag/ swell power quality issue. Normal voltage levels decrease from 10 and 90% of the root means square (RMS) voltage at frequency, from 0.5 to 1 minutes cycle duration shown in fig 10.
Figure SEQ Figure * ARABIC 10: Voltage waveform showing voltage sag (Tekale, et al., 2017).Voltage swell occurs at power frequency, voltage increase at outside of the normal tolerance with higher than one cycle or less than a few seconds periods are shown in fig. 11
Figure SEQ Figure * ARABIC 11: Voltage waveform showing voltage swell (Tekale, et al., 2017).2.5.6 Low/high Power factorHigh rate reactive power supply for the power grid is not accepted by the distribution company. Excessive reactive current flow minimizes the low/ medium voltage networks capacity and increases the PQ losses to the system. When it operates on low power factor (below pf=0.6 lagging), it may produce power losses (Katiraei, Mauch, and Dignard-Bailey, 2007).
2.6. Mitigation techniques for PQ issues
To resolve the PQ issue in renewable integration in to the feeder, the research has been conducted. Voltage quality is the main issue in PV integration. Various mitigation technical methods have been applied to solve power quality issues of the system. This issue can be mitigated either from utility side or from customer side. In the first method, confirms that the electrical equipment is less sensible to power disturbance, it may work under significant alteration. The second method is to install a controlling device that responds to the power quality problems. Flywheels, supercapacitor, smart batteries, control voltage transformer, harmonics filter are used to mitigate power quality issues as a controlling device. Custom Power Devices (CPD) like STATCOM, DSTATCOM, DVRs, and UPQC are also used to solve power quality issues associated with utility grid or used appliances.
2.6.1 Static Synchronous Compensator (STATCOM)This method has many positive points as compared to the static var compensator (SVC) using thyristor. It does not need thyristor or capacitor and can generate reactive power at very low voltage, and faster (Giroux, Sybille and Le-Huy, 2001). This system used for stability improvement and flicker mitigation. However, STATCOM only works in lagging and leading mode, that's why this device is not suitable to reactive power support as it hasn't the ability to control active power. For that BESS has been installed with STATCOM which can control both active and reactive power.
2.6.2 Distribution Static Compensator (DSTATCOM)This technique is more reliable techniques for improving voltage related issues such as voltage unbalance, rice and drop. This device is also providing compensation of harmonic and reactive power for the electrical grid. DSTATCOM provides a better solution for improvement of voltage profile and reduction of unbalance as compared to the DVR, for that DSTATCOM must have a much higher rating than the DVR (Chidurala, 2016). DSTATCOM is a parallel connected custom power device (CPD) and mainly designed for correction of PF (power factor), filtering harmonics current, voltage regulation and balancing the load. DSTATCOM has voltage and current source PWM converter. With an appropriate control scheme, the DSTATCOM can compensate for poor load power factor (Khadem, Basu and Conlon 2010, p. 4). However, this solution is expensive to install and manage for the distributor operator. Moreover, some DSTATCOM required additional devices such as transformer for compensation of natural and harmonics current in the low voltage system (Haque, and Wolfs, 2016).
Figure SEQ Figure * ARABIC 12: DSTATCOM System Configuration (Khadem, Basu and Conlon, 2010).
2.6.3 Dynamic Voltage Restorer (DVR)
Dynamic voltage restorer is a series-connected CPD to protect the loads from a disturbance at supply-side. It is also capable to solve PQ issues such as unbalance, voltage fluctuation/flickers and swell/sags. DVR has voltage source pulse width modulation with direct current capacitor and connected with main supply voltage through low pass filter and transformer (Dharavath, Raglend, and Manmohan, 2017). DVR is mainly used to maintain the voltage at during voltage fluctuation and during voltage sag. Hence, it has become one of the customers familiar device. However, like DSTATCOM, DVR solution is also expensive and like STATCOM, DVR can also be used with BESS for controlling active and reactive power for mitigation of harmonics voltage. DVR is not that much successful method like DSTATCOM to control voltage unbalance it requires very small rating than the DSTATCOM.
Figure SEQ Figure * ARABIC 13: Block diagram od dynamic voltage restorer (Dharavath, Raglend, and Manmohan, 2017).2.6.4 UPQC (Unified Power Quality Conditioner)UPQC is the integration of series and shunt active filters connected back to back on the DC side and share common capacitor (Khadem, Basu and Conlon 2010, p. 4). Supply-side power quality issue such as flickers, harmonics, voltage unbalance and voltage sags/swells mitigated by UPQC. It may insert voltage to maintain load voltage at the desired level. Problem generated by customers such as, load unbalance, load harmonics current and poor power factor, resolved by shunt component of the UPQC. It may inject current into the AC system as current source become in phase with voltage source and become balanced sinusoids. However, UPQC required an ascensive number of diodes, inverter, and many switching devices to enhance the system capacity.
Figure SEQ Figure * ARABIC 14: Block Diagram of UPQC (Khadem, Basu and Conlon, 2010).2.6.5 On Load Tap Changing Transformer (OLTC)
OLTC is also known as an autotransformer. To raise the starting voltage for the power grid and keep desired load voltage along with power grid, OLTCs are commonly used in a distribution system. The main disadvantages of these OLTC are high response time, produce arc during tap changing process, high service and maintenance cost (Haque, and Wolfs, 2016). This application is not suitable where the quick operation of tap changes is required. For instance, OLTC requires a quick operation to response center6419850fluctuations occur in the LV system with high PV penetration.
Figure SEQ Figure * ARABIC 15: Schematic diagram of On-Load Tap Changing Transformer (Haque, and Wolfs, 2016).2.6.7 Energy Storage systemTo solve the power quality issue of low voltage distribution systems, several mitigation methods have been used such as energy storage system, distribution static compensator (DSTATCOM), on-load tap changing transformer (OLTC), and dynamic voltage restorer (DVR). Among all techniques, Energy Storage System (ESS) plays crucial role with a renewable system as they can control the flexibility issue. Battery energy storage system is the most widely used ESS to integrate solar energy into the electric grid. This system is designed to store extra energy during high generation and low demand time for later use during peak power demand. Battery storage is used either to store extra power produced from the solar system for later use when solar power is not enough to cover demand or buy power from the grid when the demand of power is lower or returned to the grid when the demand of electricity is higher. ESS can be used for controlling voltage unbalance and overvoltage issue due to high photovoltaic penetration in distribution networks, voltage unbalance has mitigated about 2% by using energy storage, which was more than nearly 3.5% with high penetration in feeder (Chua et al., 2012). Battery energy storage system provides power to reduce consumers variations and it can be located centrally at the power substation or distributed with a feeder (Miller et al., 2010). Grid-connected BESS consists of a control system, battery bank, converters, transformer to covert battery output to the voltage level of transmission or distribution system. With the accurate control method, BESS can resolve the power quality issue and improve reliability, and economics of the Solar PV system.
2.7. Technologies for Application of Energy Storage.
There are many technologies available for the energy storage application such as Sodium sulfur batteries (NaS), Flow batteries (ZnBr, VRB and PSB), nickel-cadmium batteries (Ni-Cd), pumped hydro, Lead-acid batteries, supercapacitors, flywheels and Lithium-Ion (Li-ion) batteries (Nourai, 2002). Li-ion batteries and supercapacitor have higher efficiency and longevity.
Figure SEQ Figure * ARABIC 16: Energy storage technologies with life expectancy and efficiency (Nourai, 2002).2.7.1 Lithium-ion (Li-ion) Batteries.Batteries are playing an important role to store energy and mitigate power quality issue due to PV penetration in a feeder. Li-ion batteries will be used in this project. The cathode and anode of Li-ion batteries are created by lithiated metal oxide and graphic carbon respectively. The electrolyte is created by lithium salts melted in natural carbonates. During charging time, the lithium atoms which is present in the cathode converted into ions and travel through the electrolyte towards the anode where merge with outside electrons and are accumulated between lithium atoms and carbon layer during discharging, this process becomes reversed. Li-ion has small size, light in weight, durable and storage efficiency is nearly at 100% (Divya and stergaard, 2009). However, one drawback with Li-ion batteries is its high cost due to difficulty arise in the production process from the exclusive circuitry to protect these batteries and due to special packaging. To capture the large scale of the energy market, several companies are trying to reduce the production cost of this batteries. The cost of lithium-ion batteries is reducing approximately about 25% between 2009 and 2014, and the optimal system size would be increased (Muenzel et al., 2015).
Table SEQ Table * ARABIC 1: Different Technologies for energy storage.Energy Storage Technologies Pros Cons
Lithium-Ion Batteries High density, power and long lifespan Costly
Lead-Acid Batteries The initial cost is low 3-7 yeas durability
NiMH Batteries Long lifetime and reliable As compared to lead-acid batteries, 10 times more expensive
Hydrogen Fuel Cell High energy density Costly and short lifespan
Characteristics of Li-ion batteries include:
Long cycle life (3000 cycles (charge and discharge) at 80% depth of discharge (DOD)).
Higher efficiency (100%).
High energy density
operating temperature 30 to 60 C
Low generation of noise, vibration and emission as compared to other batteries.
Most of the Li-ion material about 98% can be recycled and reused except sodium.
low self-discharge and no memory effect
2.7.2 Supercapacitors.These capacitors also are known as Electrochemical Capacitors. It is made of two series capacitors as electric charge can be stored between this electrode and electrolyte. Due to the large carbon electrode surface area and few gaps between absorbed electrolyte ions and carbon surface, their capacitance is 1000 times higher than the electrolytic capacitor. As compared to lead-acid batteries, supercapacitors offer low energy density but highly reliable and efficient and can be recycled several times and more powerful as it has faster charge and discharge capability. The small electrochemical capacitors are well developed, the large units with energy density over 25kwh/m3 are still under development and are not mass-produced at this time (Nourai 2002, p. 315). Currently, very small supercapacitor about seven to ten watts are available for power quality applications at utility side and widely seen in residential electronics devices.
Figure SEQ Figure * ARABIC 17: Double layer supercapacitor (Nourai, 2002).2.8 Distributed Solar PV with Energy storage systemSolar PV stand-alone does not considerably act on peak hour demand when it is connected to a power grid due to its intermittency. Grid-connected solar PV with storage system has many advantages. Firstly, accepting managing load as it increases the decrement of customer usage from the utility. Secondly, it can increase the capability of utilities to stop energy disruption when solar PV generating power. Thirdly, enable residential to support local loads and satisfy their electricity demand in case of system failure and increase the efficiency and reliability of the system.
Figure SEQ Figure * ARABIC 18: Grid-connected Solar photovoltaic with and without ESS (Hoff, Perez and Margolis, 2007).2.8.1 Peak power shaving of solar photovoltaic systems and Li-ion battery storageThe use of solar PV with ESS adds value by allocating power consumption at peak hours. Its consumption includes characteristics of load managing, making the system more reliable and stable, and peak- shaving (Hadjipaschalis, Poullikkas, and Efthimiou, 2009). Advantages of Li-ion batteries with solar PV include: (i) In low demand photovoltaic system, battery charged by power grid, its called battery charging stage. (ii) In batteries discharging stage, photovoltaic and batteries meet peak demand (day time) when photovoltaic generation is limited, and the electricity cost of utility is high. (iii). Photovoltaic system attends high demand and generating electricity when the battery system in standby.
Li-ion battery is well developed well-developed technology and has durability, high efficiency, small size, light in weight and need less space while installation.
2.9. Solar PV with Battery and Supercapacitor.Solar PV with supercapacitor requires extra parameters such as series resistance and shunt resistance, equivalent series resistance RSC (mV), an inner equivalent parallel resistance, RPC (Kv). RSC has electrode, electrolyte, and constant resistance, during the charging or discharging process of super-capacitor, for internal heating all resistance waste power. When supercapacitor is in standby mode, RPC is responsible for leakage current.
Mathematical model equation for PV with supercapacitor is:
It=IL-IO(eV+IRSVT-1)V+IRsRSH (2.9)
Figure SEQ Figure * ARABIC 19: Equivalent Circuit of Supercapacitor (Zahedi, 2011).
Figure SEQ Figure * ARABIC 20: Electrical circuit of Photovoltaic Module with Supercapacitor (Zahedi, 2011).
At supercapacitor side,
I(t)=VBus1RPC+1RSC-VSC(t)RSC (2.10)
VSC(t)=VBus 1-e-t (2.11)
=RSCCSC (2.12)
2.10. Why Batteries Energy Storage System Needed?The use of energy storage (battery) with a solar system, enhance the local consumption during peak production periods is an accurate solution for improving power quality. Implementation of this solution method has become reasonable due to development of technology has decreased the cost of batteries. A battery can also use for backup power and peak power shaving. To regulate the voltage profile of the distribution network energy storage system seems an accurate method. BESS can also regulate the power between the generation of PV and the electrical grid to enhance power quality into the grid. Batteries have cost-effective electrochemical technologies for energy storage. To achieve the desired electrical characteristic, battery is made with a low-voltage module which are joined series and parallel. During charging process of the battery, the internal chemical reaction enters inside applied potential to the terminals or in discharging, when it reverses the chemical reaction, the absorbed energy is delivered. For storage application, batteries have high energy density, efficiency, duty cycle capability, long life and low initial cost (Divya and stergaard, 2009). Batteries and supercapacitor can reduce voltage fluctuation of PV output and give economic benefits. BESS is rapidly being used to enhance solar power into the network. BESS can absorb and deliver active and reactive power. With these capabilities, BESS can resolve power quality issue such as ramp rate, current, voltage and frequency problems. BESS now become more promising storage technology for the power system, as it offers a range of solutions such as power factor correction, frequency control and voltage regulation,
2.11 Simulation Platform for Improving Power Quality Issue
Low voltage distribution network has been created into MATLAB/Simulink software. MATLAB Simulink software is also used to simulate the proposed optimization method to solve power quality issue. There are so many useful applications in the MATLAB software. In this software, the integration of solar PV into the distribution network will be considered. Firstly, without using any method result will be noted down. Then after adding energy storage devices such as smart batteries and supercapacitor distribution network will be updated. The voltage output will be again observed after adding energy storage system and applying the proposed optimization method. There should be a huge difference in these two results of power quality issue.
Chapter 3: MethodologyThere are numerous methods for improving power quality issue at customer level such as reactive power control method, MPPT method, Proposed optimization methods etc. But one method that widely used with battery energy storage system is proposed optimization.
3.1 Reactive Power Control MethodThis method is commonly used to control overvoltage. Reactive power absorption/injection from the system to make PCC voltage lower (Demirok, et al., 2009). In this case, high inverter capacity required to provide reactive power flow. Over rating of 17.64% extends the range of operational inverter between 0.85 lagging and 0.85 leading. Reactive power control method enhances the level of delivered power but still, this method is not accurate for high R/X value and extra inverter is needed to absorb reactive power from the electrical grid. Absorption of reactive power by inverter may give more trouble and it also can reduce their lifetime. Moreover, this method requires a higher current flow on feeders that may give extra losses. This method is also used for the reduction of power factor depending on the reactive power absorbed by PVs.
Figure SEQ Figure * ARABIC 21: Capability of Reactive Power (Demirok, et al., 2009).3.2 MPPT (Maximum Power Point Tracking) Method.In the case of solar PV in LV distribution network, overvoltage issue can be solved by controlling power injection at full sunny day. This might be done by enabling the MPPT of the inverters to leave the maximum power point if overvoltage risk switch-off gets read. This may lead to the green power losses but preferred over the loss of the completion of solar PV installation due to overvoltage protection of the inverter. One problem with this solution is that one who has an extra feature of MPPT losses green power, while the installation gets benefits of lowered voltage.
3.3 Proposed Optimization Method.The proposed optimization method is divided into three stages. Which will process the storage devices such as batteries and capacitor effectively?
3.3.1. Preparation Stage.In this stage, location will be determined of distributed generation (DG) and storage devices. Location of the voltage regulator is fixed at the centre of the feeder (Ausavanop, Chanhome, and Chaitusaney, 2014). Calculation based on the number of combination equation is used here to find the possible location of storage devices.
Total Combination=N-11x (3.1)
Where,
N= Total number of buses,
X= Total amount of storage devices and DG.
All possible location of DG and storage devices are will be used as the starting parameter for the first and second stages.
3.3.2. First stage of proposed optimization.This stage determines every possible location and size of DG and storage devices for getting the desired voltage output. The objective of this stage is to reduce the voltage difference between each bus on an hourly basis (here, 1.00 PU is used). average voltage difference equation is shown below.
Min voltage differrence=i=1NLi(Vi-1.00)2i=1NLi (3.2)
Where,
Li (kVA)= Load at bus
Vi= Voltage at bus
N and I = Total number of bus
In equation (2), the weighting factor is multiplied with Li for voltage regulation. Li (kVA) is more than 1.
Power flow equation:
PQ=J11J12J21J22 V ... (3.3)
Where,
P=Real power, Q= Reactive power, =Voltage angle, and V=Voltage.
Active power production limit of distributed generation (Pdg).
Pdg, min Pdg Pdg, max (3.4)
Reactive power production limit of distributed generation (Qdg).
Qdg, min Qdg Qdg, max ... (3.5)
Power factor limits of DG (PFdg).
arccos(PFdg)arccos(PFdg )limit ... (3.6)
Reactive power of capacitor (QCB).
QCBQCB, max (3.7)
Transformer limit (Pt).
PtPt, limit (3.8)
This stage performed in an interval of 1hr. Then, the second stage of proposed optimization is performed here.
3.3.2 Second stage of proposed optimization.In this stage objective equation derived from the sum of total voltage difference with time. By applying this equation, the voltage drop can be measured at any time.
Min objective function=t=t1t2Average voltage difference (3.9)
In the preparation stage, every possible location of storage system gives different results. For getting the desired result, the best location should be found out. The steps of the proposed algorithm are shown below:
Step 1: find out all possible location with the help of the preparation stage.
Step 2: Set time interval (t1 and t2)
Step 3: Set initial condition (Count k=1)
Step 4: Generate random variable input by using MATLAB simulation.
Step 5: select the best location and get a better result
Step 6: If criteria satisfied (K riches at Kmax?) then go to next step, otherwise go back to step 5 and set k=k+1.
Step 7: compare the initial solution with the next solution, then select a better solution.
Step 8: Terminate process if criteria satisfied (K reaches Kmax) otherwise return to step 5 and set k=k+1.
Step 9: Stop simulation process if a random variable has covered mean value and then go to the next step otherwise, return to step 4.
Step 10: Stop the process if t reaches tmax. Otherwise set t=t+1 and go back to step 3.
Step 11: Stop all process if all possible location is assessed. Otherwise, choose the next possible location return to step 2.
All possible location of storage devices will give different results. Therefore, the best location of storage devices and DG can be decoded by using the preparation stage. After penetrating solar PV power quality issue such as voltage rise and drop, and reverse power flow occurred into the network. To mitigate this issue energy storage devices such as batteries and capacitor are introduced into the network with a different location. The best location will be found by using the proposed optimization method. The whole process can be understood by reviewing the below flowchart.
Flowchart
Figure SEQ Figure * ARABIC 22: Flowchart of Proposed optimization method.Chapter 4: Simulation Results and Discussion
Chapter 5: Conclusion5.1 Summary
The solar energy system is becoming more useful in electricity generation due to its simplicity for installation, portability and modularity. It provides clean energy during its usage, generation and transmission and it emits zero pollution. However, during integration into the distribution system, it generates power quality issues which are reviewed in this project. This power quality issue such as poor power factor, voltage rise and drop, voltage regulation, and reverse power flow are the main concerning issue in the low voltage network. Various mitigation methods are used to solve this problem at the customer side or utility side. Among all methods, energy storage system gives a better solution. Moreover, the high cost of solar PV installation can be reduced by using energy storage system. Li-ion battery will be used during implementation of this project as Li-ion has a long-life span, high efficiency and light in weight. In last proposed optimization method will be implemented in MATLAB Simulink platform.
5.2 Recommendation for Future Works
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Appendix 1: How and where I addressed feedback given on the Project Scope.
Table SEQ Table * ARABIC 2: Project Proposal FeedbackNo. Feedback/Comments/Guidance How I addressed? Where I addressed?
1 Introduction and Background: Introduction has all the elements. Good progress but need to improve a bit for research. I have added a research background and keywords in the starting and ending of the introduction. Page 5,7 paragraph 1
2 Aim and Objectives: Met all three criteria in the proposal. Need some improvement I have extended my aim and added two new objectives. Page 8,9, paragraph 1
Engineering Research Project Planning
ENRP20001 (Term 2, 2020)
Literature Review
Project Title
Modeling of Multi-Junction PV Cell for the Improvement of Conversion Efficiency Considering Maximum Power Point Tracking
Student Name: Maljsadk FJaveStudent ID: 12080005
Supervisor: Dr Narottam Das
Date of Submission: 27/08/2020
School of Engineering and Technology
Central Queensland University, Melbourne Campus
Australia
TABLE OF CONTENTS
TOC o "1-3" h z u 1. Introduction PAGEREF _Toc18254259 h 81.1 Background PAGEREF _Toc18254260 h 81.2 Aim and Objective PAGEREF _Toc18254261 h 111.3 Research Questions PAGEREF _Toc18254263 h 111.4 Limitations and Inclusions PAGEREF _Toc18254264 h 121.4.1 Limitations PAGEREF _Toc18254265 h 121.4.2 Inclusions: PAGEREF _Toc18254266 h 122. Literature Review PAGEREF _Toc18254270 h 132.1 Photovoltaic: Introduction, working, Advantages, Types PAGEREF _Toc18254271 h 132.1.1 Introduction PAGEREF _Toc18254272 h 132.1.2 Working of Photovoltaic cell PAGEREF _Toc18254273 h 152.1.3 Advantages of photovoltaic Technology PAGEREF _Toc18254274 h 172.2 Different Generations of photovoltaic Technology PAGEREF _Toc18254275 h 172.3 Characteristics of Solar Cell PAGEREF _Toc18254276 h 192.4 Different Parameters of solar cell PAGEREF _Toc18254277 h 202.4.1 Short circuit current PAGEREF _Toc18254278 h 202.4.2 Open circuit voltage PAGEREF _Toc18254279 h 202.4.3 Fill factor and maximum power PAGEREF _Toc18254280 h 212.4.4 Effect of Temperature and Irradiance PAGEREF _Toc18254281 h 212.4.5 The solar Spectrum PAGEREF _Toc18254282 h 212.5 Multi-junction solar cells (MJSC) PAGEREF _Toc18254283 h 242.6 Factors need to be considered for MJSC: PAGEREF _Toc18254284 h 272.6.1 Lattice Matching: PAGEREF _Toc18254285 h 272.6.2 Bandgap Energy Matching PAGEREF _Toc18254286 h 282.6.3 Current Matching PAGEREF _Toc18254287 h 292.7 Solar Cell efficiency PAGEREF _Toc18254288 h 292.7.1 Limitations of solar cell efficiency PAGEREF _Toc18254289 h 312.8 Double Diode Method PAGEREF _Toc18254290 h 322.9 Maximum Power Point Tracking Method PAGEREF _Toc18254291 h 352.9.1 Overview of Maximum Power Point Tracking PAGEREF _Toc18254292 h 353. Methodology PAGEREF _Toc18254293 h 363.1 Different Maximum Power Point tracking techniques: PAGEREF _Toc18254294 h 363.1.1 Perturb & Observe method PAGEREF _Toc18254295 h 373.1.2 Incremental Conduction method: PAGEREF _Toc18254296 h 373.1.3 Fractional Open circuit voltage PAGEREF _Toc18254297 h 393.1.4 Fractional Short circuit current PAGEREF _Toc18254298 h 393.1.5 Fuzzy Logic Control PAGEREF _Toc18254299 h 403.1.6 Neutral Network PAGEREF _Toc18254300 h 403.2 Perturb and Observe Method PAGEREF _Toc18254301 h 413.3 DC-DC Converter PAGEREF _Toc18254302 h 453.3.1 Buck Converter PAGEREF _Toc18254303 h 463.3.2 Boost Converter PAGEREF _Toc18254304 h 46List of References PAGEREF _Toc18254305 h 47Appendices PAGEREF _Toc18254306 h 51Appendix 1 How and where I addressed feedback given on the project scope. PAGEREF _Toc18254307 h 51
LIST OF FIGURES
TOC h z c "Figure" Figure 1: Schematic representation of MJSCs (Laurent, 2016) PAGEREF _Toc18254102 h 9Figure 2: Flexible thin-film III-V junction solar cell (Reprinted from Tanabe, 2009) PAGEREF _Toc18254103 h 10Figure 3: Solar cell or PV cell PAGEREF _Toc18254104 h 14Figure 4: Forecast of energy consumption PAGEREF _Toc18254105 h 15Figure 5: (a) Mechanism of electron excitation (Luque & Hegedus, 2011), (b) Characteristics of free carriers in a PV cell (Archer & Green, 2001). PAGEREF _Toc18254106 h 16Figure 6: Schematic of P-N Junction diode PAGEREF _Toc18254107 h 17Figure 7: Donor and acceptor levels in semiconductor (Luque & Hegedus, 2011). PAGEREF _Toc18254108 h 17Figure 8: Global market share: solar energy annual production PAGEREF _Toc18254109 h 18Figure 9:(a) Diode Curve Characteristics (b) Characteristics of Solar Cell (Martens & Roth, 2014). PAGEREF _Toc18254110 h 20Figure 10: Solar spectrum of 1.4ev bandgap (Tanabe, 2009). PAGEREF _Toc18254111 h 22Figure 11: Solar radiation spectrum of AlInGaP (1.9 eV) / GaAs (1.4 eV) / Ge (0.66 eV) AM1.5D triple junction solar cell (Tanabe, 2009). PAGEREF _Toc18254112 h 23Figure 12: Solar radiation spectrum of AlInGaP (1.9 eV) / GaAs (1.4 eV) / Ge (1.0 eV) AM1.5D triple junction solar cell (Tanabe, 2009). PAGEREF _Toc18254113 h 24Figure 13: (a) Double Junction Diode (Jain &Hudait, 2012) PAGEREF _Toc18254114 h 25Figure 14: Triple Junction Diode Model (Das et al., 2014). PAGEREF _Toc18254115 h 26Figure 15: Efficiency of InGaP/InGaAs/Ge MJSC (King et al., 2007). PAGEREF _Toc18254116 h 27Figure 16: III-V compounds relation between lattice constant and band gap (Roman, 2004). PAGEREF _Toc18254117 h 28Figure 17: Atom with three orbital and their energies (Baider & Samberg, 2013). PAGEREF _Toc18254118 h 29Figure 18: Comparison of different solar cells efficiency ( Dey & Ahmmed, 2015). PAGEREF _Toc18254119 h 31Figure 19: Reported solar cell efficiency Vs. Time Courtesy of NREL, USA PAGEREF _Toc18254120 h 31Figure 20: Early theoretical and experimental efficiencies (W. Shockley, 1961) PAGEREF _Toc18254121 h 32Figure 23: Basic Circuit of MPPT (Mankar&Moharil, 2014). PAGEREF _Toc18254122 h 36Figure 24: P-V and I-V characteristics of solar PV (Kamran et al., 2018) PAGEREF _Toc18254123 h 36Figure 25: Flow chart of Increase Conduction Method. PAGEREF _Toc18254124 h 39Figure 26: Voltage and current characteristics (Esram & Chapman, 2007). PAGEREF _Toc18254125 h 40Figure 27: Function of Fuzzy Logic controller (Esram & Chapman, 2007). PAGEREF _Toc18254126 h 41Figure 28: Concept of Neutral Network (Esram & Chapman, 2007). PAGEREF _Toc18254127 h 41Figure 29: P&O MPP point characteristics (Mankar and Moharil, 2014). PAGEREF _Toc18254128 h 42Figure 30: Flow chart of Perturb and Observe method PAGEREF _Toc18254129 h 44Figure 31: Tracking of wrong MPP under rapidly varying irradiance (Harjai et al., 2011). PAGEREF _Toc18254130 h 45Figure 33: MPPT diagram with DC-DC converter and PV array (Gradella et al., 2009). PAGEREF _Toc18254131 h 46Figure 34: Buck converter PV system (Gradella, 2009). PAGEREF _Toc18254132 h 47Figure 35: Boost converter PV system (Gradella, 2009). PAGEREF _Toc18254133 h 47
LIST OF TABLES
TOC h z c "Table" Table 1: Dual junction solar cell characteristics (Jain &Hudait, 2012). PAGEREF _Toc18254142 h 26Table 2: Basic crystal structure parameters for commonly used MJSC semiconductors. PAGEREF _Toc18254143 h 30Table 3: Comparison of different MPPT methods PAGEREF _Toc18254144 h 42Table 4: Scheme of P&O algorithm ( Kamran et al., 2018). PAGEREF _Toc18254145 h 43Table 5: How and where Feedback is addressed. PAGEREF _Toc18254146 h 52
Nomenclature
a1 ideality factor for diffusion current component of diode 1(D2 model)
a2 ideality factor for recombination current component of diode 1(D2 model)
D2 Double diode model
Eg bandgap energy (eV)
FF fill factor
Gc actual measured irradiance of PV cell
Gstc Irradiance at standard test condition (1000 W/m2)
I total current
Iph Photon generated current
Iph_stc Photon current at standard test condition
Is1 reverse saturation current of first diode for double diode
Is2 reverse saturation current of second diode for double diode
Isc short circuit current
K Boltzmanns constant, 1.381*10(-23)
MJSC multi-junction solar cell
MPPT maximum power point tracking
Pin input power
P& O perturb and observe
VI curve voltage current curve
VP curve voltage power curve
Pmpp power at maximum point
STC standard test condition
V total voltage
Rp shunt losses in PV cell
Rs series losses in PV cell
Tc actual measured temperature
Tsct temperature at standard test condition
Chapter 1: Introduction
1.1 BackgroundThe popularity of electrical energy is growing day by day all over the world with growth in population. As per the research conducted, the energy produced through the limited traditional sources such as oil, gas, and coal are more than 80% (Das et al., 2014). However, these conventional methods are creating so many environmental issues. Continues use of these resources may face disappearance in a short period. To avoid this, an alternative source of energy such as solar, wind, tidal, geothermal, biomass should be developed urgently to save the earth. The main aim is to produce clean and green renewable energy which can be fulfilled by using solar energy because it generates the energy directly from the sun. It has been investigated that, from the last two decades annually the demand for solar electric energy has been increased tremendously (approx. 20 to 25%) (Agui et al., 1998). A photovoltaic cell is an essential part of solar electric systems as an alternative resource of power. To get more absorption of sunlight, a variety of materials can be used to increase the conversion efficiency of the solar cell (Wang et al., 2017). The efficiency of the solar cell is defined as, the ratio of generated power of solar cell to the energy of the sun into the time of solar cell (Tanabe, 2009). The concentration of sunlight into a smaller incident area using lenses has two advantages for solar cell applications. The first is the material cost reduction with a smaller area of cells and second is the efficiency enhancement with the higher open-circuit voltage Voc increases.
This project focuses mainly on multi-junction solar cell (MJSC) for improvement of the conversion efficiency because it is considered to be the most efficient technology than the single junction, as losses produced by the multi-junction solar cell is less. MJSC is a combination of several single junctions. The MJSCs was first introduced by the Research Triangle Institute (Colorado, United States) (Das et al., 2014). The greater efficiency can be achieved through the photon wavelength of MJSCs (Laurent, 2016) shown in Figure 1. Previously, So many research and studies were carried out in this area of improvement of conversion efficiency of solar cell. However, a major drawback of the PV source is its ineffectiveness the nights or low isolation periods or during partially shaded conditions. High initial capital cost has been another hurdle in the popularity of PV systems (Mankar & Moharil, 2014).
Figure SEQ Figure * ARABIC 1: Schematic representation of MJSCs (Friedman, 2010).Selection of semiconductor materials is the most crucial part of this study. There were three-generation technologies mentioned in the study of (Bhattacharya, 2013). First and second-generation solar cells were made of Mono-crystalline and thin-film silicon respectively. However, production of power is very limited from these materials, because it produces very low efficiency. Apart from this cost is the biggest issue. Efficiency produced by the first-generation solar cell (Mono-crystalline) was recorded 31% and 20% by second-generation (thin-film silicon) in the laboratory. However, mass production is still a big question in the second generation. These limitations can be overcome by considering the tandem PV cells or multi-junction solar cells with semiconductor materials of different bandgap (Bhattacharya, 2013). We have found that the conversion efficiency can be improved in MJSCs (Triple-Junction) by using such materials as InGap/GaAs/Ge (Indium Gallium Phosphide / Gallium Arsenide /Germanium) in theory of (Barati et al., 2019) because these materials absorb the wider wavelengths of the solar radiation spectrum. 30.3% conversion efficiency is recorded through a double junction solar cell. The highest conversion efficiency achieved by the latest MJSC (Triple junction) is about 43.5% as compared to another solar cell (Das et al., 2014) and 44.7% efficiency was achieved by using four junction solar cells. However, the biggest issue for choosing these materials with an appropriate band gap is that it has a high physical and production cost. So that, to improve the conversion efficiency, in this project I will consider a stack of cells with different bandgap materials when the top cell is having the higher bandgap and the bottom cell is considered with the lowest bandgap. We can choose GaAs due to its low effect crystal structure and wide band gap. Currently, it is considered to be the highest efficient material in the world so far as 20 % more effectiveness was found in GaAs than conventional silicon cells (Hendy et al., 2016). The solar cell of III-V semiconductor material has proven leading conversion efficiency because it shows more advantages with respect to bandgap energy, photon absorption, efficiency.
Figure SEQ Figure * ARABIC 2: Flexible thin-film III-V junction solar cell (Reprinted from Tanabe, 2009).
Maximum power point tracking method is playing an important role in improving the solar cell conversion efficiency as it produces the maximum power for different atmospheric conditions (Das et al., 2016). MPPT methods will be proposed such as perturb and observe, increase conduction method, fuzzy logic control, open-circuit voltage, short circuit current. The power extracted from PV cells is affected by 1) shading effects because of sun movements, 2) Temperature 3) solar irradiation 4) series resistance 5) shunt resistance. MATLAB/Simulation will be performed by varying temperature and solar irradiance most (Das et al., 2014) and also demonstrates how these factors will be affected, and it was seen from the characteristics of I-V and P-V of the solar cell. I will choose the most effective material for the improvement of the conversion efficiency of MJSC. Three times more maximum power can be obtained by tandem cells than the conventional PV cells (Das et al., 2014). The more efficient power can be generated for the solar cell with the help of maximum power point tracking method (Das et al., 2014). The MPPT algorithms are generally implemented between the PV panels and load where the maximum energy will be transferred by operating the load as closely as possible to MPP line of the PV output (Gandhi et al., 2014).
1.2 Aim and ObjectiveThe main aim of this research project is to improve the conversion efficiency of multi-junction solar cell (Triple junction) by obtaining maximum performance of PV system by considering the suitable material (InGap/GaAs/Ge) by applying adequate maximum power point tracking method (MPPT) within the Matlab/Simulink environment. This project is mainly focus on Perturb & observe and Incremental conduction method to obtain a higher output because of its benefits so far.The aim of this project will be achieved by reviewing some published papers. In this project, I will investigate how the MJSC PV cells produce higher power throughout the sunny day for the production of greener energy for the future. Different modeling techniques will be tested and reviewed using MATLAB/ Simulink to identify which semiconductor material will improve the conversion efficiency appropriately. I-V and P-V characteristics will be obtained by varying performance of temperature and irradiance by using MATLAB simulation will also be the part of this research project. Apart from this, Performance of MPPT methods such as Perturb and observe and increase conduction method will be analyzed in this research to obtain the higher output. Out of these methods, I will use the most accurate method for PV system for more precise results.1.3 Research QuestionsThis project presents various criteria while designing the multi-junction solar cells (MJSC) to improve the conversion efficiency by considering three research questions, such as 1) How the conversion efficiency of MJSC will be improved through the MATLAB/Simulink platform, 2) How the maximum power point tracking (MPPT) methods are being used to enhance maximum power by comparing with other methods 3) How various materials are performing with MJSC to improve conversion efficiency. The impact of different performance factors, such as temperature, irradiance, ideality factor, and bandgap on the conversion efficiency can be also investigated. We can observe all these factors through the I-V and P- V characteristics for MJSC in MATLAB/Simulink.
Keywords: Conversion efficiency, MATLAB/Simulink, Maximum power point tracking (MPPT), Multi-Junction solar cells (MJSC), Photovoltaic cell (PV).
1.4 Limitations and Inclusions1.4.1 LimitationsSelection of semiconductor material with an appropriate bandgap will be the biggest issue.
Initially, 20% conversion efficiency needs to be achieve compulsory if using Thin-film silicon PV for staying competitive with other PV technologies.
As the current matched device is quite complex, component cells are affected by some spectral overlap.
High installation cost.
Inexpensive and insufficient storage devices.
Seasonality of sunlight.
Very low conversion efficiency of solar.
Low energy density.
4.2 Inclusions:
Performance of such factors as temperature and irradiance to obtain I-V and P-V characteristics in MATLAB/Simulink.
Selection of semiconductor material to improve conversion efficiency by considering bandgap and lattice and current matching.
Comparison of MPPT Methods: Perturb and observe method, increase the conduction method to obtain a more precise method.
Chapter 2: Literature ReviewThis chapter contains a detail explanation of several solar research topics including the overview of photovoltaic (PV) cell, its advantages and disadvantages or limitations, different types, characteristics of the solar cell, P-N junction diodes, etc. A literature review of MJSC subjects includes the structure using double and triple diode models, various parameters such as bandgap energy, lattice, and current matching, temperature, and irradiance. This literature review also includes various maximum power point tracking methods to improve the conversion efficiency of MJSC. Perturb & observe method is explained in detail for implementation.
2.1 Photovoltaic cell: Introduction, working, Advantages, Types2.1.1 IntroductionPhotovoltaic (PV) is a kind of technology which generates direct power in watts (W) or Kilowatts (kW) by considering photons of energy for a bandgap of semiconductor material. A solar cell converts sunlight directly into electricity without moving any parts (Figure 3). A solar cell generates electricity directly from sunrays by the PV effect. The PV effect was first demonstrated in 1839 by A.E. Becquerel, a French Physicist is reported by Mahmoud et al., 2012. Most solar cells can charge 12V or 24 V batteries. However, when these solar cells are illuminated, it generates voltages between 0.4 to 0.7 Volts. Solar module and solar array are a combination of solar cells. To generate the desired voltage and current solar cells are combined into a solar module or array by connecting series or parallel (Gandhi et al., 2014).
Electron is emitted if photon light energy is more than the bandgap energy, which results in the current generation. A photovoltaic cell is different than the photodiode where in photodiode light current generate through the n-type semiconductor. While PV is a forward-biased (Markvart & Castaner, 2012).
Figure SEQ Figure * ARABIC 3: Solar cell or PV cellSource: https://images.app.goo.gl/1bGVGUrNmzYE5EZc6
Renewable sources (Solar, wind, geothermal) are also based on the sun and these sources are replacement of Non-renewable sources (coal, natural gas, oil) as these are not environmentally friendly and production is slower than its demand. If these sources are used once then these are not available to use it again. So, the world is now turning towards the cleanest, pollution-free, long-lasting and easily available renewable sources. It is considered to be the green energy and it fulfills the requirement of power shortage. Currently, on the earth, solar energy is now using the most as compared to others so far by considering its benefits.
Figure SEQ Figure * ARABIC 4: Forecast of energy consumption.
https://images.app.goo.gl/QgUpnmTKmQ7YTBu76
Solar energy consumption has been increased as compared to conventional energy sources. Solar energy is considered to be the most promising renewable energy by 2050 (as shown in Figure 4). More than 50% of the energy produced through renewable energy sources. By 2050, more than 70% of the energy comes from renewable energy, where, 60% of the contribution is noted by only solar PV cell (Wang, 2018).
2.1.2 Working of PV cellA solar cell generates electrical energy from the direct sunlight by the photovoltaic effect. A photovoltaic cell has two layers of semiconductor materials. Sometimes these materials have energy band with weakly bonded electrons is known as valence band (VB) and when the energy beyond a threshold value then covalent bonds are broken. These electrons then jump into new energy band and recognized as the conduction band (CB) (Figure 5 (a)). Now, these electrons are free from the valence band through bandgap energy (eV). Photons, light particles are being used to supply this threshold energy by breaking atoms of valence electrons and energizing them to the upper level of energy in CB. Electrons of conduction band lose their energy while driving towards the external circuit. Through the second contact, these free electrons are restored again and returned in the valence band before illumination with the same energy.
Figure SEQ Figure * ARABIC 5: (a) Mechanism of electron excitation (Luque & Hegedus, 2011), (b) Characteristics of free carriers in a PV cell (Archer & Green, 2001).Two different materials are joined together at the same boundary electrons from the n-layer transferred into the p-layer and generate a p-n junction. When these atoms absorbed the photon of light, it will create free electrons and these electrons have sufficient energy to jump out of the depletion zone. In P-N junction, the electron travels towards external load through P-type material and converts sunlight (irradiance) into direct current (DC) energy (Figure 5(b)) (Chin, Salam, & Ishaque, 2015).
P-N Junction Diode
The diode is an electrical device where current flows only in one direction. For example, a P-N junction is a very basic model of the diode and it acts as a valve (Figure 6). When anode terminal (P-type) of P-N junction diode is connected to the positive terminal of the battery and the cathode terminal (N-type) is attached to the ground then the diode is considered to be a forward biased and when the cathode and anode are interchanged then the diode is considered to be reversed biased.
Figure SEQ Figure * ARABIC 6: Schematic of P-N Junction diodeSource: https://images.app.goo.gl/1SuPkix8Crcgxw1S6
Donor atom Ed is very near to the conduction band and this conduction band has sufficient energy to provide a space for the extra electron to energize. Donor state is then charged positively. Ea is the negatively charged state. P-type and N-type semiconductor create due to the impurities of donor and acceptors in the semiconductor. This is called the basic way of creation of semiconductor which includes solar cells (Figure 7).
Figure SEQ Figure * ARABIC 7: Donor and acceptor levels in semiconductor (Luque & Hegedus, 2011).2.1.3 Advantages of PV Technology
PV cells are the most promising photo-conversion device and the most rising sustainable power source asset for the 21st century.
It is pollution free clean technology
Easily available and accessible source
Ability to generate power anywhere.
Free from generation of waste disposal, no emission.
Reliability is very high more than 25 years.
Useful for both stand alone and grid connected application.
Operation is noise free because no moving parts
Installation is rapid.
2.2 Different Generations of photovoltaic TechnologyVarieties of solar cells are available in the market and the development of solar cell technology is essential for stand-alone and grid-connected applications for cost. Technologies of a solar cell are classified into three types: Mono and Poly-crystalline silicon, Thin-film solar cells and full spectrum utilization (Figure 8).
First Generation: Mono and Poly-crystalline Silicon:High quality of mono-crystalline silicon wafers is comprised. 31% of conversion efficiency achieved through generation. Production cost is very higher of large crystals. Another challenge of this monocrystalline silicon material is when the temperature increases, efficiency decreases. Poly-crystalline silicon is the alternative of mono silicon and it can produce by combining the multiple silicon crystals by considering the cost reduction.
Second Generation: Thin-film Silicon:This generation semiconductor material is mitigating the challenges of first-generation. A requirement of material is reduced as compared to the first generation. Second-generation solar cells are made up of thin films silicon by deposition techniques. However, first-generation solar cells are formed of bulk crystalline silicon material. Amorphous silicon, cadmium telluride or cadmium sulfide (CdTe/CdS) and the chalcopyrite family alloys like copper indium gallium (di) selenide (CIGS) are three types of thin-film PV cells (Dey and Ahmmed, 2015).
Figure SEQ Figure * ARABIC 8: Global market share: solar energy annual production.
https://images.app.goo.gl/JEqoSALMpeNqA2eKA.
Third Generation: Full Spectrum Utilization: There are two limitations of the first and second generation. The first and foremost is if the photons of energy are less than the bandgap then this energy is not absorbed by the solar cells. However, higher bandgap energy is also not effective. For effective conversion efficiency, photons should be of the equal energy bandgap. Due to these limitations, encouraged for designing of a multi-junction solar cell with different semiconductor bandgap material. It is also known as stack-of cells where the topmost cell is considered with higher bandgap material and absorption of photons energy is higher (Green, 2002). On the other hand, a lower cell with the lowest bandgap energy and absorption of photons energy is lower (Bhattacharya, 2009).
2.3 Characteristics of Solar CellCharacteristics of the photodiode and solar cell are very much similar to each other. The only difference between these two with current, the diode curve is being represented in first quadrant, where it shows negative current and with the solar cell it becomes positive.
Figure SEQ Figure * ARABIC 9:(a) Diode Curve Characteristics (b) Characteristics of Solar Cell (Martens & Roth, 2014).2.4 Different Parameters of Solar Cell2.4.1 Short circuit currentFigure 9(b) shows short circuit current arises when the solar cell is shorted, voltage is zero and current is maximum. The solar cell is considered to be ideal where no losses and resistance is infinite. No current is flowing from the diode if the cell is shorted:
If the voltage of the solar cell is zero: Isc is same as Iph.
Isc relative to irradiance.
Higher solar cell efficiency can be obtained if the energy bandgap is lower. And it can be said that,
More number of photons can be absorbed with the lower bandgap.
Short circuit current increases with respect to decrementing in bandgap energy.
2.4.2 Open circuit voltageFrom Figure.9 (b) when the voltage is at a maximum open circuit voltage (Voc) and the current is zero. Voc can be obtained from equation 2.2.2.1 where I=0, Isc = Iph:
Voc=a.Vt.lnIscIs+1 (2.1)Where:
Vt= The temperature dependant voltage (V),
Isc=The short circuit current (A),
Is=The saturation current.
Above equation describes open circuit voltage is less dependent on irradiance and it can be said that,
Open circuit voltage is proportional to the natural log of irradiance.
Voc increases with bandgap energy increases.
Efficiency increases as Voc increases.
2.4.3 Fill factor and maximum powerHigher fill factor occurs with less rounded VI characteristics and known as a high-quality solar cell.
FF=Vmpp.ImppVoc.Isc=PmppVoc.Isc (2.2)
Where:
Pmpp = The power at the maximum power point (W),
Vmpp = The maximum voltage (V),
Impp = The maximum current (A),
Voc = The open-circuit voltage (V),
Isc = The short circuit current (A),
Fill factor is greatest at the intersection point where maximum voltage and current meet and is considered to be a maximum power point of the solar cell.
2.4.4 Effect of Temperature and IrradianceThe I-V and P-V characteristics of multi-junction solar cell can be obtained by varying two temperature and irradiance (Das et al., 2014). According to their study, when the temperature increases, increment in short circuit current and decrement open-circuit voltage is noticed due to losses occurs in open circuit voltage. So that, generation of power is decreased.
If solar irradiance is increased continuously then it is very advantageous for solar cell power, as both the short circuit current and open-circuit voltage are increases and consequently, power generation is also increasing. By this way, the conversion efficiency of photo-voltaic cell increases.
2.4.5 The solar SpectrumThe solar spectrum compares different solar cell conversion efficiency. Figure 10 describes with 31% efficiency is achieved through AM1.5G solar spectrum, 1 Sun.
Figure SEQ Figure * ARABIC 10: Solar spectrum of 1.4ev bandgap (Tanabe, 2009).However, AlInGaP (1.9 eV) / GaAs (1.4 eV) / Ge (0.66 eV) tandem cell generates 50.1% conversion efficiency under 1000 suns AM1.5D which is beyond the Shockleys scheme of 1000 schemes AM1.5G (Efficiency 41.4%) as shown in Figure 11.
Figure SEQ Figure * ARABIC 11: Solar radiation spectrum of AlInGaP (1.9 eV) / GaAs (1.4 eV) / Ge (0.66 eV) AM1.5D triple junction solar cell (Tanabe, 2009).:
Figure SEQ Figure * ARABIC 12: Solar radiation spectrum of AlInGaP (1.9 eV) / GaAs (1.4 eV) / Ge (1.0 eV) AM1.5D triple junction solar cell (Tanabe, 2009).Figure 12 shows, if 0.66eV bandgap is replaced with 1.0eV bandgap between GaAs and Ge material improves the conversion efficiency and improved efficiency become 55.0% with AM1.5D, 1000 Suns.
2.5 Multi-junction solar cells (MJSC)A multi-junction solar cell (MJSC) can be formed with two or more single junction semiconductors to absorb the wider range of the solar spectrum by layering one on other. Multi-junction solar cells, the direct sunlight matched for spectral sensitivity by splitting the spectrum into smaller slices. The relevant solutions are-increase the efficiency of solar cells, effective spectral splitting by different bandgap semiconductor sub-cell layers, implementation of III-V direct bandgap optically sensitive and high carrier mobility semiconductors (Wang, 2018). Increasing the efficiency of the existing solar cells from 15% to 40% will reduce the material usage and land acreage the cost can be reduced significantly.
The MJSC are made up of different semiconductor material bandgap where upper surface carries the highest bandgap and lower surface carries lower bandgap. As shown in below figure.9 top cell is having the highest bandgap 1.85 eV of gallium indium phosphide (GaInP) which is greater than gallium arsenide (GaAs) semiconductor material with bandgap 1.4 eV. Quantity of photons increases for production of energy in MJSC and it reduces the losses.
The first multi-junction solar cell was presented with dual junction and that formed by aluminum gallium arsenide (AlGaAs) and gallium arsenide (GaAs) (Virshup et al., 1988). Then later in 1990, the greater conversion efficiency was achieved by the addition of one more layer with the different semiconductor material. A tandem (triple junction) solar cell was presented by a combination of GaInP, GaAs, and Ge (Yamaguchi et al., 2005). 43.5% conversion efficiency is achieved through the triple-junction solar cell. Due to environmental effects and unavailability of conventional fossil fuels, MJSC is considered to be the best device to achieve desired conversion efficiency. Stacking of semiconductor materials from group III-V gives a more accurate result which results in higher conversion efficiency with low cost and it is considered to be leading technology in todays world (Cotal et al., 2008). While combining the semiconductor materials there are some essential requirements to follow: Lattice matching, Bandgap energy matching, current matching (Das et al., 2014).
Double junction diode model shown in Figure 13 (a) and (b),
Figure SEQ Figure * ARABIC 13: (a) Double Junction Diode (Jain &Hudait, 2012), (b) Double Diode Model (Das et al., 2014).Combination of Indium Gallium Phosphide (InGap) and Gallium Arsenide (GaAs) is considered to be a most common double junction solar cell because its bandgap is closely lattice matched with each other (Das, Wangsodihardjo & Islam., 2015). Figure 13(a) & (b) shows the typical dual junction solar cell of InGaP/GaAs. The expected efficiency from this dual junction is 30.8%. However, its experimental efficiency is between 27% - 30%. Its performance shown in Table 1.
Table SEQ Table * ARABIC 1: Dual junction solar cell characteristics (Jain &Hudait, 2012).InGaP/GaAs dual MJSC performance :InGaP (eV) 1.86 Spectrum AM(1.5)
GaAs (eV) 1.42 Irradiance 1000
Efficiency(%) 30.8 Area (cm2) 1
Mattched Lattice Constant (Tanabe, 2009)
Recorded Data Kayes et al. 2014 Takamoto et al. 1997 Algora et al. 2007
Cited in Jain & Hudait 2012 Cited in Jain & Hudait 2012
Voc (V) 2.547 2.48 2.52
Jsc(mA/cm2) 14.3 14.22 12.7
Fill Factor 84.7 85.6 85
Efficiency 30.8 30.28 27.2
A Triple Junction Diode model is shown in Figure14.
Figure SEQ Figure * ARABIC 14: Triple Junction Diode Model (Das et al., 2014).The most common used multi-junction solar cell is triple junction. In this project, most of the literature reviewed of triple junction with having a layer of Indium Gallium Phosphide (InGaP), Indium Gallium Arsenide (InGaAs), Germananium(Ge) (Das, Wangsodihardjo & Islam., 2015), (Hussain et al.,2016), (King et al., 2007).
Figure SEQ Figure * ARABIC 15: Efficiency of InGaP/InGaAs/Ge MJSC (King et al., 2007).
Figure 15 shows efficiency of triple junction solar cell where each cell is closely matched with lattice and band gap energy. Efficiency generated through is more than 40%.
2.6 Factors need to be considered for MJSC:2.6.1 Lattice Matching:Material selection is very important while checking lattice matching. Lattice constant check each material is matched to each other or not and also measure the spacing of atoms (Das et al., 2015). Dislocation may create if found mismatch in lattice constant. They also mentioned that, conversion efficiency will be reduced even if +/- 0.01% mismatch found in lattice matching. As shown in figure 12. Combination of GaAs, AlAs and Ge are currently creating high conversion efficiency because these materials have almost same lattice constant. However, bandgap is different (Green, 2003).
Figure SEQ Figure * ARABIC 16: III-V compounds relation between lattice constant and band gap (Roman, 2004).2.6.2 Bandgap Energy MatchingThis is the factor to be considered for multi-junction solar cell, where diversity of bandgap at each level should be considered. If semiconductor is having a wider bandgap then there is a possibility of highest spectrum level and absorption is also increases. Top cell absorbs the maximum energy from the sun and it is transmitted till bottom layer. For far bandgap range, unabsorbed light will turn into heat and go above the air and it causes losses. To reduce the losses and increase the conversion efficiency bandgap of nearest junction should be as close as possible (Takamoto, 2009). Figure 13shows relation of band gap energy with lattice constant. Ge cell of triple junction solar cell (GaInP/GaInAs/Ge) is produced almost double the current than GaInAs cell (Bedair & Samberg, 2013).
Figure SEQ Figure * ARABIC 17: Atom with three orbital and their energies (Baider & Samberg, 2013).While designing the solar cells bandgap model is very essential because it demonstrate the relation between selection of material and its potential. Figure 17 shows atom with specific energy levels by electron volt (eV). Greater the electron distance- level of energy is higher.
Table SEQ Table * ARABIC 2: Basic crystal structure parameters for commonly used MJSC semiconductors.Basic parameters at 300K
Material Lattice Constant(A) Bandgap energy(eV) Crystal structure
Aluminium gallium arsenide AlGaAs5.653 1.42-2.16 Zinc blend (FCC)
Gallium antimodeGaSb6.096 0.726 Zinc blend (FCC)
Gallium arsenide GaAs 5.653 1.424 Zinc blend (FCC)
Gallium indium phosphide GalnP5.869 Zinc blend (FCC)
Gallium phosphide GaP5.451 2.26 Zinc blend (FCC)
Germanium Ge 5.658 0.66 Diamond (FCC)
Silicon Si 5.431 1.12 Diamond(FCC)
Lattice constant and bandgap energy for different multifunction solar cell materials shown in Table 2.
2.6.3 Current MatchingIn MJSC, each sub cell is arranged in series. If this requirement is not meet then the total current will be reduced. Numbers of photons are responsible for generation of current through the absorption capacity of material. Photon can easily pass through the material with high absorption coefficient and thickness can decrease. If the absorption capacity is low then in order to provide the same space for photon to pass, thickness should be increase (Smestad, 2002).
2.7 Solar Cell efficiencyEfficiency of single junction solar cell differs from multi-junction solar cell due to series connection of more than two layers.
Single Junction cell efficiency:
SJSC=PmppPin=Voc.Isc.FFAreamm21000.100 (2.3)
It is very simple model and efficiency describe by maximum power divided by input power. Whereas, in MJSC summation of input power of each junction before divided by the input power.
Multi Junction cell efficiency:
MJSC=PmppPin=1Pin junctionsVoc.Isc.FFj.100 (2.4)
Where:
Pin = solar cell input power (W),
Pmpp = Power at the maximum power point (W),
Voc = Open current voltage (V),
Isc = Short circuit current (A),
FF = Fill factor,
Figure SEQ Figure * ARABIC 18: Comparison of different solar cells efficiency (Dey & Ahmmed, 2015).Figure 18 shows comparison of different solar cells: Si (Crystalline); 25.6%, Si(Multi-Crystalline); 20.4%, Si(Nano-Crystalline); 10.1%, Si(Amorphous); 10.1%, Multi-junction (GaInp/GaAs/Ge);32%, Multi-junction GaInp/GaInAs/Ge); 41.6%, Multi-junction (GaInp/GaAs/GaInNAs); 43.5%.
Figure SEQ Figure * ARABIC 19: Reported solar cell efficiency Vs. Time Courtesy of NREL, USA.
As shown in Figure 19, The highest conversion efficiency measured by multi-junction solar cells have the highest promise of increasing the efficiency as evidenced by the efficiency vs. year chart data mentioned by National Renewable Energy Lab (NREL). Many leading research organizations all over the world are investing money in the design of III-V multi-junction solar cell projects.
2.7.1 Limitations of solar cell efficiencyAdvancement in solar PV cell technology is achieved by considering the limitations of material used in existing technology. In Shockleys 1961 paper, he discussed about theoretical and experimental limit of conversion efficiency of P-N junction cell (Figure 20).
Figure SEQ Figure * ARABIC 20: Early theoretical and experimental efficiencies (W. Shockley, 1961).
As shown in figure 20, 33% Conversion efficiency achieved from single cell and single band gap. Advancement in Si technology was very slower because efficiency achieved through this technology is lower. MJSCs able to mitigate this issue simply by adding one layer of semiconductor material
The above obtainable efficiency has been achieved through the following assumption:
Band to band recombination occurred only.
Photons are absorbed whose energy is greater than bandgap and electrons with thermalisation loss.
During the collection and transportation of charge, no losses are occurred.
2.8 Double Diode Model
Although single diode model is most popular because of its simplicity and easy application. However, accuracy become diminishes at lower irradiance and lower voltages (Chin, Salam and Ishaque, 2015). Double diode model structure is made up of two diodes that reduce the losses Figure 21.
Figure 21: Double Diode equivalent circuit (Das et al., 2014).
The saturation current in both the single and double diode junction are generally equal (Ishaque, 2011) and (Mahmud et al., 2012). However, there is variant in ideality factor as this factor is function of voltage in device, where, a1 of first diode is generally 1, whereas second diode will have a2 same as or greater than 1.2.
The mathematical derivation of D2 model is just extension of the D1 model. The double diode model can be found by subtraction of both currents Id1 and Id2 and shunt current Irp from photoelectric current.
Iph- (Id1 +Id2 )-IRP-I=0 (2.5)
I=Iph- (Id1 +Id2 )-IRP (2.6)
By applying the voltage divider rule current from the shunt can be obtained and hence the output current of double diode PV model:
I=Iph- Is1expq.(V+I.Rs )a1.Ns.k.Tc-1 -Is2expq.(V+I.Rs )a2.Ns.k.Tc-1V+I.RsRp I=Iph- Is1expV+I.Rs a1.Vt-1 -Is2expV+I.Rs a2.Vt-1V+I.RsRp (2.7)
Where:
Ip: Photon generated current,
I_s1 : First diode saturation current,
I_s2 : Second diode saturation current,
q: Charge of an electron, 1.602*10^ (-19),
V i: Total voltage generated by each cell,
Irs: is the voltage across the series resistances,
a1 : First diode ideality factor,
a2 : Second diode ideality factor,
Ns : Number of cells in the PV cell module,
K is Boltzmanns constant, 1.381 * 10^ (-23),
Tc : Actual measured temperature of the PV cell (C),
Rp: Represents the shunt losses within the PV cell,
Vstc : Temperature dependant voltage for Ns cells (at any temperature).
Hence D2 saturation currents are given by:
Is1=Irs1TcTstc3 .expq.Ega1.k1Tstc-1Tc Is2=Irs2TcTstc3 .expq.Ega2.k1Tstc-1Tc (2.8)
Irs1=IphstcexpVoc_stca1.Vt-1 = Isc_stcexpVoc_stca1.Ns.k.Tcq-1 Irs2=Iph_stcexpVoc_stca2.Vt-1 = Isc_stcexpVoc_stca2.Ns.k.Tcq-1 (2.9)
2.10 Maximum Power Point Tracking Method2.10.1 Overview of Maximum Power Point TrackingConversion of solar irradiance into energy is only 30-40% by typical solar panel. However, +-r, to improve the conversion efficiency of solar cell maximum power point tracking method playing a vital role. It produces maximum power at different atmospheric condition. The power extracted from PV cells is affected by 1) shading effects due to sun movements, 2) Temperature 3) solar irradiation 4) series resistance 5) shunt resistance. All these parameters can be demonstrated through the I-V and P-V characteristics. As these parameters vary, maximum power point (MPP) also varies. Basic circuit of MPPT shown in Figure 23.
Figure SEQ Figure * ARABIC 23: Basic Circuit of MPPT (Mankar & Moharil, 2014).
Maximum power can be obtained under specific solar irradiance and temperature level by adjusting the current and voltage of solar PV (Mankar & Moharil, 2014). The function of PV cell can also find with help of converter duty cycle at maximum power point (Kamran et al., 2018).
Similarly, by varying parameters such as Pmax, Vmax, imax, Voc, Isc at high temperatures degradation of solar module has been noticed (Figure 24) (Ahmed & Salam, 2015).
Figure SEQ Figure * ARABIC 24: P-V and I-V characteristics of solar PV (Kamran et al., 2018).
Chapter 3: Methodology3.1 Different Maximum Power Point Tracking (MPPT) techniques:There are several methods to track the maximum power point, some of are given below:
Perturb and Observe method
Incremental conduction method
Fractional short circuit current
Fractional open circuit voltage
Fuzzy logic
Neutral networks
The above mention techniques are mostly depend on implementation cost, convergence speed, range of effectiveness, sensor required, and popularity, implementation of hardware and complexity of algorithm that uses to track the MPP (Mankar &Moharil, 2014).
3.1.1 Perturb & Observe methodThis is the most widely used MPPT method because of its simple structure and number of parameters used for measurement. In this method, only one sensor is used that is voltage sensor to sense the PV voltage. Due to this, easy to implement with less cost. As the time complexity is very less, it does not stop at MPP but very close to the MPP and keeps on perturbing on both the directions.
However, rapid change in irradiation level is not measured through this method because it is considering the perturbation change in MPP and consequently wrong MPP is being calculated. Incremental conduction method can be used to mitigate this issue.
3.1.2 Incremental Conduction method:Incremental conduction method measures both the output current and voltage by two sensors current and voltage of the PV array. This method describes the comparison of slop of power curve with respect to duty ratio (Shahid et al., 2018). Flowchart of increase conduction method is shown in Figure 25.
Figure SEQ Figure * ARABIC 25: Flow chart of Increase Conduction Method.At MPP the slope of PV curve is 0.
dPdVMPP=dVIdV
0=I+VdIdVMPP
dIdVMPP=-IV (3.1)From the above equation, Solar panel conductance becomes equal to the instantaneous conductance at MPP. Through this method we can measure both the current and voltage. So that error that causes because of irradiance in one sensor can be eliminated. Due to this, it becomes more complex compared to perturb and observe method. As compared to other methods, complexity levels are less in perturb & observe and Incremental conduction method, easy to implement. These two are widely used methods.
Advantage:
This method is overcome with steady state oscillation problem of perturb and observe method at MPP where the sudden change in atmospheric condition.
It can track the peak power at different environmental conditions.
It can also track rapidly change in irradiance with high accuracy.
Iteration levels are less.
Tracking speed is faster.
Limitations:
Requires more time for computation.
More complex than P&O.3.1.3 Fractional Open circuit voltageFractional Open circuit voltage method has been raised by considering the relationship between Voc and Vmpp at different temperature and irradiance levels.
Vmpp=K1*Voc (3.1)
K1 is the proportionality constant, which is dependent on used PV cell. It can be computed before formatting the Vmpp and Voc at various irradiance and temperature levels. The value of K1 is considered to be between 0.71 to 0.78. If the value of K1 is known, Vmpp can be calculated by measuring open circuit voltage Voc with the help of power converter. However, it comes with some limitations such as temporary power loss occurs (Esram & Chapman, 2007).
Figure SEQ Figure * ARABIC 26: Voltage and current characteristics (Esram & Chapman, 2007).3.1.4 Fractional Short circuit currentFractional short circuit current is obtained by varying different atmospheric condition, where Impp is Proportional to Isc of PV.
Impp=K2*Isc (3.2)
Where, K2 is constant. Just as function of K1 in fractional open circuit voltage, here K2 is also used according to use of PV cell. The value of K2 is between 0.78 to 0.92. Short circuit is creating a problem while measuring during the operation. To measure the Isc current sensor is being used by adding the switching in power converter by shorting the PV cell (Esram & Chapman, 2007).
3.1.5 Fuzzy Logic ControlFuzzy logic control has been popular since last decade with the help of Microcontroller. The most powerful advantage of this method is that it has ability to work with imprecise inputs, where data of accurate mathematical model is not required (Figure 27) (Esram & Chapman, 2007).
Figure SEQ Figure * ARABIC 27: Function of Fuzzy Logic controller (Esram & Chapman, 2007).3.1.6 Neutral NetworkNeutral network is also a kind of MPPT method is well adapted for microcontrollers. It is generally made up of three layers: Input, Hidden and output layer. Numbers of nodes are depending on the user in each layer (Figure 21). Open circuit voltage (Voc) , Short circuit current (Isc) , and temperature, solar irradiance is such examples of Input variables. While various reference signals i.e. duty cycle signal is used to track the MPP with the help of power converter (Esram& Chapman, 2007).
Figure SEQ Figure * ARABIC 28: Concept of Neutral Network (Esram & Chapman, 2007). Table SEQ Table * ARABIC 3: Comparison of different MPPT methods (Esram & Chapman, 2007).
MPPT technique Convergence speed Implementation Complexity Periodic tuning Sensed parameters
Perturb & observe Varies Low No Voltage
Incremental conduction Varies Medium No Voltage , current
Fractional VocMedium Low Yes Voltage
Fractional IscMedium Medium Yes Current
Fuzzy logic control Fast High Yes Varies
Neutral Network Fast High Yes Varies
3.2 Perturb and Observe MethodThe basic P&O algorithm describes, by taking the reference of the last increment point solar PV shifting or perturbation can be noticed. As the increment in PV power, the perturbation will go in same direction and once starts the decrement in PV power; the perturbation will be notices in the opposite direction. (Kumari et al., 2012).
Figure SEQ Figure * ARABIC 29: P&O MPP point characteristics (Mankar and Moharil, 2014).Perturbation moves towards the MPP if dP/dV>0 and P&O method will continue perturb the PV voltage in same direction. When dP/dV<0 then it shows that PV array moves away from MPP point and the direction of perturbation is reverse (Figure 29) (Mankar &Moharil, 2014). On the LHS side increment in power is linear with respect to voltage. However, on the RHS side power decreased with increase in the voltage. So that P&O try to maintain MPP by perturbing voltage and power respectively.
Table SEQ Table * ARABIC 5: Scheme of P&O algorithm (Kamran et al., 2018).
Above Table 3 represents how the resulting perturbation obtains with respect to change in voltage and power. So that according to sign of Delta V and Delta P a resulting perturbation can be approached. If the sign of dV and dP both positive or negative, then direction of perturbation is positive. Direction is negative if either is negative.
Figure SEQ Figure * ARABIC 30: Flow chart of Perturb and Observe method.
Modified algorithm (Figure 30) of P&O method is more effective as compared to conventional method because conventional method finding issue with steady state oscillations if there is a sudden change in weather. This problem is mitigating in modified algorithm where it tracked the MPP more accurately under uniform and different atmospheric condition without steady state oscillations. (Kamran et al., 2018). Modified P&O algorithm was becoming 99.96% efficient as compared to conventional P&O algorithm. During the partial shading condition, 16% tracking efficiency can be improved by modified P&O algorithm (Alik &Jusoh, 2018). Steady state oscillation issue can be resolved by implementing a variable step size and the perturbation moves towards maximum power point if this step size is larger and it becomes smaller if it passes through the MPP.
Advantage:
Simple structure with only one sensor i.e. voltage or current.
It requires less number of parameters to be measure.
Implementation cost of algorithm is very low.
Limitations:
Power loss occurs at maximum power point because it continuously deviating at MPP.
Steady state oscillation problem: larger step size with higher loss and smaller step size with slower response.
Unable to track peak power.
Rapidly varying irradiance track wrong MPP.
Figure SEQ Figure * ARABIC 31: Tracking of wrong MPP under rapidly varying irradiance (Harjai et al., 2011).When the irradiance changes MPP is also moves towards right direction and algorithms takes this change due to perturbation and in the next iteration direction goes in the opposite direction of MPP due to changes in perturbation direction (Figure 31).
3.3 DC-DC ConverterSome amount of energy waste in terms of power loss occurs in P&O method due to steady state oscillation around the maximum power point and due to this issue Perturb and observe method is not responding properly during rapidly varying atmospheric condition. To mitigate this negative effect, DC-DC converter is adopted with MPPT parameters (Famia et al., 2005). For changing the input resistance with respect to load resistance DC-DC converter required.
Studied shown that DC-DC converter gives maximum efficiency with buck converter, then for buck-boost and then for boost converter. However, it all depends on the application.
Figure SEQ Figure * ARABIC 33: MPPT diagram with DC-DC converter and PV array (Gradella et al., 2009).As shown in Figure 33, the converter output is denoted as constant DC voltage source. The PV output power is regulated through the converter. Here, the power is observed at the terminal of PV array by MPPT block and controls the input current and voltage. Finally, it creates pressure on the PV array to operate at maximum power point.
3.3.1 Buck Converter
Figure SEQ Figure * ARABIC 34: Buck converter PV system (Gradella, 2009).Figure 34 shows, voltage can be controlled through the buck converter as input current is discontinuous and low ripple voltage is found in capacitor. MPPT algorithm is used to control the voltage output. Capacitor is necessary for constant voltage constant and for filtering the discontinuity of input current.
3.3.2 Boost Converter
Figure SEQ Figure * ARABIC 35: Boost converter PV system (Gradella, 2009).Figure 35 shows, current of PV array and current of inductor are same. So, the MPPT algorithm use output power of array and converter inductor current to control the variable.
List of ReferencesAlik, R. and Jusoh, A., 2018. An enhanced P&O checking algorithm MPPT for high tracking efficiency of partially shaded PV module. Solar Energy, 163, pp.570-580.
Barati-Boldaji, R., Mojalal, S. and Seifi, M.R., 2019. Modeling and predictive control of InGap/GaAs/Ge triple-junction solar cells to increase the energy conversion efficiency. International Journal of Applied, 8(2), pp.120-128.
Bedair, SM & Samberg, Joshua P 2013, Current matching for high efficiency multi-junction solar cells, Journal of Electrical & Electronics, vol. 2012, Retrieved from.
Bhattacharya, I. and Foo, S.Y., 2009, July. Indium phosphide, indium-gallium-arsenide and indium-gallium-antimonide based high efficiency multijunction photovoltaic for solar energy harvesting. In 2009 1st Asia Symposium on Quality Electronic Design (pp. 237-241). IEEE.
Bhattacharya, I., 2013. Design and modeling of very high-efficiency multi-junction solar cells (Doctoral dissertation, The Florida State University).
Bonkoungou, D., Koalaga, Z. and Njomo, D., 2013. Modelling and Simulation of photovoltaic module considering single-diode equivalent circuit model in MATLAB. International Journal of Emerging Technology and Advanced Engineering, 3(3), pp.493-502.
Chin, Vun Jack, Salam, Zainal &Ishaque, Kashif 2015, Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review, Applied Energy, vol. 154, p. 502.
Cotal, H., Fetzer, C., Boisvert, J., Kinsey, G., King, R., Hebert, P., Yoon, H. and Karam, N., 2009. IIIV multijunction solar cells for concentrating photovoltaics. Energy & Environmental Science,2(2), pp.174-192.
Das, N., Al Ghadeer, A. and Islam, S., 2014, September. Modeling and analysis of multi-junction solar cells to improve the conversion efficiency of photovoltaic systems. In 2014 Australasian Universities Power Engineering Conference (AUPEC), pp. 1-5. IEEE.
Das, N., Wongsodihardjo, H. and Islam, S., 2014. Modeling of multi-junction photovoltaic cell using MATLAB/Simulink to improve the conversion efficiency. Renewable energy, 74, pp.917-924.
Das, N., Wongsodihardjo, H. and Islam, S., 2016. A preliminary study on conversion efficiency improvement of a multi-junction PV cell with MPPT. InSmart Power Systems and Renewable Energy System Integration, pp. 49-73.
Dey, G.K. and Ahmmed, K.T., 2015, September. Performance characterization of photovoltaic technology with highly efficient Multi-Junction Solar Cells for Space Solar Power Satellite system. In 2015 3rd International Conference on Green Energy and Technology (ICGET), pp. 1-6. IEEE.
Esram, T. and Chapman, P.L., 2007. Comparison of photovoltaic array maximum power point tracking techniques. IEEE Transactions on energy conversion, 22(2), pp.439-449.
Femia, N., Petrone, G., Spagnuolo, G. and Vitelli, M., 2005. Optimization of perturb and observe maximum power point tracking method. IEEE transactions on power electronics, 20(4), pp.963-973.
Harjai, A., Bhardwaj, A. and Sandhibigraha, M., 2011. Study of maximum power point tracking (MPPT) techniques in a solar photovoltaic array (Doctoral dissertation).
Gandhi, K., Ali, M., Saxena, S. and Mishra, M.,2014, MATLAB Based Solar Tracking Photovoltaic Module using MPPT Algorithm, International Journal of Electrical and Instrumentation Engineering, Vol. 4, No. 1, January 2014, pp. 16.
Gradella, M., Villalva, J., Rafael, G. and Ruppert Filho, E., 2009, September. Analysis and simulation of the P&O MPPT algorithm using a linearized PV array model. In 10th Brazilian Power Electronics Conference (COBEP).
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Jain, N. and Hudait, M.K., 2012, June. Design of metamorphic dual-junction InGaP/GaAs solar cell on Si with efficiency greater than 29% using finite element analysis. In 2012 38th IEEE Photovoltaic Specialists Conference (pp. 002056-002060).
Kamran, M., Mudassar, M., Fazal, M.R., Asghar, M.U., Bilal, M. and Asghar, R., 2018. Implementation of improved Perturb & Observe MPPT technique with confined search space for standalone photovoltaic system. Journal of King Saud University-Engineering Sciences.
King, R.R., Law, D.C., Edmondson, K.M., Fetzer, C.M., Kinsey, G.S., Yoon, H., Sherif, R.A. and Karam, N.H., 2007. 40% efficient metamorphic GaInP GaInAs Ge multijunction solar cells. Applied physics letters, 90(18), p.183516.
Laurent, A., 2016. Modelling and analysis of multi-junction photovoltaic cells using MATLAB/Simulink for the improvement of conversion efficiency.
Mahmoud, Soliman A., Alsari, M. M., Reda, E. I. &Alhammadi, R. M. 2012, MATLAB modeling and simulation of photovoltaic modules', in Circuits and Systems (MWSCAS), 2012 IEEE 55th International Midwest Symposium on: proceedings of theCircuits and Systems (MWSCAS), 2012 IEEE 55th International Midwest Symposium on pp. 786-9,
Mankar, P.U. and Moharil, R.M., 2014. Comparative analysis of the perturb and observe and incremental conductance MPPT methods. IJREAS, 2(02), pp.60-66.
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Smestad, G.P., 2002. Optoelectronics of solar cells(Vol. 115)..Patel, H. and Agarwal, V., 2008. Maximum power point tracking scheme for PV systems operating under partially shaded conditions. IEEE transactions on industrial electronics, 55(4), pp.1689-1698.
Roman, J.M., 2004. State-of-the-art of III-V solar cell fabrication technologies, device designs and applications. Advanced Photovoltaic Cell Design, 4.
Shahid, H., Kamran, M., Mehmood, Z., Saleem, M.Y., Mudassar, M. and Haider, K., 2018. Implementation of the novel temperature controller and incremental conductance MPPT algorithm for indoor photovoltaic system. Solar Energy, 163, pp.235-242.
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Villalva, M.G. and Ruppert, E., 2009, November. Analysis and simulation of the P&O MPPT algorithm using a linearized PV array model. In 2009 35th Annual Conference of IEEE Industrial Electronics (pp. 231-236).
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AppendicesAppendix 1 How and where I addressed feedback given on the project scope.
Table SEQ Table * ARABIC 6: How and where Feedback is addressed.# Feedback/Comments/Guidance How I addressed? Where I addressed?
1 Introduction: Has all the elements. Good progress but need to improve a bit for research introduction: I have clarified the introduction more in detail. Page 5, paragraph 1,
Page 6, Paragraph 1
Page 7, Paragraph 1
2 Aim & Objective: Met all three criteria in the proposal. Need some improvement I have clarified Aim and objective more in detail. Page 8, paragraph 1 and 2
Top Section (Max score 0.5)
The top section must include the Title page, Executive summary (keywords only), Table of contents, List of Figures, List of Tables, List of Abbreviations, Page number.
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0.5
Revised Chapter 1: Introduction (Max score 2.5)
It should include the following sub-sections -a) Project introduction, b) background information, c) problem statement, d) research hypothesis, e) provide an overview of existing research and e) establish the benefits of the project to its stakeholders. All elements must be present in your introduction.
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2.5
Revised Research Question (Max score 1)
Your research question should clearly state the problem that is being investigated. The question should lead to an analysis of an issue or a problem. You should use appropriate scientific/technical words when framing a research question.
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1
Revised Aims and objectives (Max score 2)
a) Research aim and objectives should inform the scope of the research question.b) Aim(s) should define the overall purpose of the work and express the intention of the study. You should clearly state what is aimed to achieve from the project.c) Objectives should align with the project aim(s). The objectives should show what are the specific steps planned to achieve the research aims.d) Aim(s) and objectives should be realistic and attainable, considering the constraints in terms of time, resources, technical ability and supports.
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2
Revised Scope and Limitations (Max score 1)
Clearly stated the scope of the project. In addition, limitations in terms of equipment, budget and tools required are identified and presented.
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1
Chapter 2: Literature Review (Overview/Mind map) (Max score 1)
A mind map has been developed to provide an overview of the literature review and explain the overview briefly.
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1
Literature review: Justification of work (Max score 4)
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4
Literature review: Methodology identification (Max score 4)
You should demonstrate a thorough understanding of the different approaches and identify one methodology that could be used to achieve the project aim and objectives. The justification of the proposed methodology should be based on high-quality literature review.
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4
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2
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TOC h z c "Figure"
Chapter 1: Introduction1.1 Background
Recycling is the practice of processing used materials for use in manufacturing new products. The use of natural aggregates is becoming increasingly intensive with the continued development of the infrastructure sector. The use of recycled aggregates in concrete production significantly reduces the demand for natural aggregates and the amount of solid waste that goes to landfills. Recycled aggregates are crushed and sorted inorganic particles processed from materials used in structures and demolition waste. These materials usually come from buildings, roads, bridges and sometimes even disasters such as wars and earthquakes. Today, there are many different uses for recycled aggregates in construction. Applications vary by country. Recycled aggregate is used in Australia as a concrete curb and gutter mix. However, this project aimed to study the impact of carbon nanotubes (CNTs) on the performance of concrete with recycled aggregates. The benefit of adding CNTs is increased strength and durability and reduced permeability.
1.2. Problem Statement
Recycled aggregates can be used as possible replacement for aggregate, but the strength will be decreased, and the shrinkage will be more which all act together in an increase of permeability. Carbon nanotube (CNT) will help the concrete increase of strength but however the shrinkage and permeability will be decreased.
So, the projected will investigates whether the CNT can be effectively improving the properties of concrete with RCA.
1.3. Research Hypothesis
To compensate for the shortcomings addressed in the Problem Statement, recycled aggregates are treated with Carbon Nanotubes to improve aspects such as chloride resistance and shrinkage. 32MPa concrete is selected for this project to perform the validations. Recycled coarse aggregate is used in the mixture at varying concentrations along with variations in the concentrations of carbon nanotubes. CNT will improve the properties of concrete with 100% RCA coarse aggregate.
1.4. Overview of Existing Research
Wang, Ho and Kitipornchai (2017) have performed a series of compression tests on concrete with recycled aggregates strengthened by carbon nanotubes (CNT) and untreated aggregates. This was done over different periods of curing. The concrete was cast in the form of a cylinder and compressive tests were done after 3,7 and 28 days. The results showed a small reduction in compressive strength varying at different curing times when CNT infused aggregates are mixed with concrete. Moreover, a remarkable difference in ductility was observed. The authors concluded that the sliding between aggregates, cement and CNTs provided a buffer for the deformation, leading to better ductility.
Madhavi et al. (2012) have discussed the effects of Multiwalled Carbon Nanotubes (MWCNTs) on the basis of their strength characteristics and durability of concrete. Multiwalled Carbon Nanotubes have the property of increasing mechanical strength and durability of concrete. They have used ultrasound waves to prevent agglomeration of MWCNT through sonication. Thirty-six specimens were prepared with varying strengths of MWCNTs with 28 days of curing. The results have demonstrated an increase in the compressive and splitting tensile strengths proportionally with the increase of MWCNTs concentration. Moreover, a decrease in crack propagation and water absorption was observed.
1.5. Research Significance
Concrete waste is one of the more significant wastes in the construction industry due to its large volume use and difficulty in disposal. Concrete waste is usually diverted to landfill creating large unusable disposal areas. With the successful completion of this project, it will significantly reduce the concrete waste that ends up in landfill, thereby creating a sustainable solution. Research indicates that there can be up to a 50% reduction in concrete waste by recycling the aggregates, thereby decreasing the need for natural aggregates. However, recycled aggregates by itself cannot provide the same structural strength and other desirable properties of concrete with natural aggregates. Hence carbon nanotubes used in this project to bridge this gap and create a betterment for sustainability.
1.6. Research Question
Q1. Will the CNT improve the property of concrete made of 100% RCA or coarse aggregate.
Q2. If so, what is the optimum dose of CNT.
1.7. Aim and Objectives
1.7.1 Aim
The main aim of the project is to study the effect of carbon Nanotubes (CNT) on the performance of Sustainable concrete with recycled aggregate.
1.7.2 Objectives To achieve the above mentioned aim the following objective are defined.
Complete a comprehensive literature review
Design an experimental program to study the effect of CNT on the properties of concrete
Finalise a concrete and cast the sample
Conduct aggregate tests such as density, porosity, gradation, crushing and L.A Abrasion
Conduct concrete testing such as compressive strength, tensile strength, permeability etc.
Analyse the result and conclude the effect of varying concentrations of CNTs on the performance of concrete with Recycled Coarse Aggregates
1.8 Scope and Limitation
The required equipment is summarised in table 1.
1.8.1 Equipments and consumables:
Table 1 Equipment Required
Equipments Campus
Concrete mixer and vibrator Rockhampton
Compressing testing machine Rockhampton
Flexural testing machine Rockhampton
UTM Rockhampton
Consumables:
Cement and aggregate Need to be purchased
RCA - Need to be collected (from RRC)
CNT - Supplied
1.8.2 Budget:
Expected budget $ 500.00.
1.8.3: Access to lab / workplace
Concrete lab in Rockhampton Campus.
1.9. Inclusion, Exclusion and deliverable plan
1.9.1 Inclusion
Literature review
Methodology
Procedure and applicable standards (AS1012)
Conclusion
1.9.2 Exclusion
Non-Disclosure agreement
Commercial in-confidential agreement
1.9.3 Deliverable plan
Table 2; Delivery Plan
Date Week Item name Deliver to
08/08/2022 Week 5 Introduction Supervisor
28/08/2022 Week 6 Literature Review Supervisor
23/09/2022 Week 10 Methodology Supervisor
09/10/2022 Week 12 Planning Thesis Supervisor
References
Amin, M., Hakeem, I., Zeyad, A., Tayeh, B., Maglad, A. and Agwa, I., 2022. Influence of recycled aggregates and carbonnanofibres on properties of ultra-high-performance concrete under elevated temperatures.Case Studies in Construction Materials, 16, p.e01063.
Meddah, M., Al-Harthy, A. and A. Ismail, M., 2020. Recycled Concrete Aggregates and Their Influences on Performances of Low and Normal Strength Concretes.Buildings, 10(9), p.167.
International Journal of Science and Research (IJSR), 2016. Effect of Recycled Plastic Aggregates on Concrete. 5(6), pp.912-915.
Dr.T.Ch.Madhavi, D., Pavithra.P, P., Sushmita Baban Singh, S., S.B.Vamsi Raj, S. and Paul, S., 2012. Effect of Multiwalled Carbon Nanotubes On Mechanical Properties of Concrete.International Journal of Scientific Research, 2(6), pp.166-168.
Nixon, P., 1978. Recycled concrete as an aggregate for concretea review.Matriaux et Constructions, 11(5), pp.371-378.
Tam, V., Soomro, M. and Evangelista, A., 2018. A review of recycled aggregate in concrete applications (20002017).Construction and Building Materials, 172, pp.272-292.
International Journal of Modern Trends in Engineering & Research, 2018. Self-Compacting Concrete made with Recycled Aggregates. 5(3), pp.242-253.
Poon, C., Kou, S. and Lam, L., 2002. Use of recycled aggregates in molded concrete bricks and blocks.Construction and Building Materials, 16(5), pp.281-289.
ACI Journal Proceedings, 1977. Recycled Concrete as a Source of Aggregate. 74(5).
