Description
CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND OF THE STUDY
Harmonics is one of the power quality issues that influencetoagreatextenttransformeroverheating,rotary machinevibration,voltagequalitydegradation,destruction ofelectric powercomponents,andmalfunctioningofmedical facilities (Henderson et al., 2014). Power quality improvement has been given considerableattentionduetotheintensiveuseofnonlinear loadsandthe limitations requiredby international standards suchasIEEE519-2012(IEEE, 2012).Thoselimitationsweresettolimit thedisturbances andavoid majorproblems inpowersystem. Sincelinearand/ornon-linearsingle-phaseloadsarerapidly increasing, zero sequence component and current harmonics are generated. This causes overheating of the associate distributiontransformersthatmayleadtoasystemfailure, especiallyin weak networks (Gruzs et al., 2010).Photovoltaic (PV) power supplied to the utility grid is gaining more and more visibility, while the world’s power demand is increasing. Global demand of electrical energy is growing by high rate due to the requirement of modern civilization. Recently, energygeneratedfromclean,efficientandenvironmentally friendlysourceshasbecomeoneofthemajorchallengesfor engineers and scientists. Among them, PV application has receivedagreatattentioninresearchbecauseitappearsto be one of the most efficient and effective solutions to this environmentalproblem(Shimizu et al., 2013).Therearetwotopologiesused toconnectthePVwiththegrid;twostagesandsinglestage PVsystem.Atwostageisthetraditionaltypeandconsistsof aCUKDC/DCconverterdirectcoupledwithPVarrayandagridconnecteduniversalbridgeinverter.InsinglestagePV system,theDC/ACinverterhasmorecomplexcontrolgoals; MaximumPowerPointTracking(MPPT)andoutputcurrent control. Regardless its control complicity, single stage PV systemismoreefficientandcheaperthantwostagessystem. For connecting the PV system to the grid, there are three widely used grid interactive PV systems; the centralized inverter system, the string inverter system and the AC modulator the Module Integrated Converter (MIC) system. Amongthese,theMICsystemoffers“plugandplay”concept and greatly optimizes the energy yield (Shimizu et al., 2013).With these advantages, the MIC concept has become the trend for the future PV system development but challenges remain in termsofcost,reliabilityandstabilityforthegridconnection (Carrascoet.al., 2016).Conventionally singlephase shunt active power filter(APF) uses an inverter for harmonics elimination and reactivepowercompensation(Carrasco et.al., 2016).AgridconnectedPV system with active power filtering feature has been presentedin(Kjær et al., 2015). However,measuringtheloadcurrent is mandatory. In this paper, an inverter is used as a single- phaseshuntactivepowerinadditiontointerfacingapower ofaphotovoltaic(PV).FuzzyLogicControl (FLC) is used as a robust controller for MPPT; this control techniquecanhandlethemodeluncertaintiesinadditionto easilyhandlethenonlinearity.Thesingle-phaseshuntactive power filter (APF) uses a predictive control technique to mitigate of the grid current harmonics and improve the power factor. The proposed control strategy provides a multifunctionwithasimplecontrollerincorporatingPhase Locked Loop (PLL) independency, less sensors, ease of practicalimplementation,andreducedsystemsizeandcost.
1.2 STATEMENT OF THE PROBLEM
The increasing global need for renewable energy has become the main impetus of the energy sector, primarily because of the negative impact of fossil fuels on the environment (Akorede et al., 2012). Photovoltaic (PV) power generation is one of the most promising renewable energy technologies that can be utilized in industrial power systems and rural electrification (Chel et al., 2019).
Photovoltaic (PV) plant as a part of a smart grid system is investigated in this work. Tracking the maximum available power of the PV panel is essential and it is possible by various maximum power point (MPP) methods. Most of these methods are iterative, time consuming and do not work well in quickly changing environmental conditions.
1.3 AIM AND OBJECTIVES OF THE STUDY
The presented work aims to improve the PV system performance by using fuzzy logic control (FLC). The objectives of the system are:
- To improve solar system performance.
- To control the voltage of the solar panel together maximum power that canbeproducedbyobservingthePVsystemunderanychangeintemperatureandinsolation
- To provide only as much power as is needed
1.4 SCOPE OF THE SYSTEM
Photovoltaic (PV) plant as a part of a smart grid system is investigated in this work. Tracking the maximum available power of the PV panel is essential and it is possible by various maximum power point (MPP) methods. Most of these methods are iterative, time consuming and do not work well in quickly changing environmental conditions.
In this work, pv interfacing inverter is controlled using a predictive control technique to perform both functions of power quality improvement in addition to transferring the PV maximum power to the grid. AFuzzy logic control algorithm is applied for MPPT
1.5 SIGNIFICANCE OF THE STUDY
This study will serve as a means of improving solar system performance, and a means of controlling the voltage of the solar panel to get the maximum power that canbeproducedbyobservingthePVsystemunderanychangeintemperatureandinsolation.
CHAPTER FIVE
5.1 CONCLUSION
In this paper, a PV system is interfaced to the grid via a multifunctional interfacing inverter. A MPPT fuzzy logic controller is employed to feed the grid by the maximum allowable PV power. A simple predictive current control algorithm is used. The system performance is investigated usingaMATLAB/Simulinkmodelatdifferentcasesofload variation, atmospheric temperature variation and solar irradiation variation. The inverter achieves functions of supplying the available power from the PV unit into the loadsinadditiontoimprovingthepowerqualityintermsof gridcurrentTHDandpowerfactor.
5.2 RECOMMNENDATION
The aim of a photovoltaic power system is to provide only as much power as is needed, an approachknownaspowermatching.Inthisapproach,anypowerinasolarpanelthatremainsnon- extracted(i.e.,becauseit is notfunctioning atthecurrentmaximumpower point) isthen released as surface heat. To implement this approach in a real-life situation, such as, for instance, a water pumpinaremotevillage,theMPPTcircuitneedstohavesomewaytoknowtheamountofpower requiredtoprovideappropriatemaximumpowertrackingtomeetthepowerneeds.Changessuch as these will significantly enhance the system’s functionality.
Futureworkcouldincludemethodsforapplyingafuzzylogicalgorithminadedicatedsingle-chip microcontroller.Aswell,aGalileoboardcouldbeusedratherthantwoArduinoboardstosatisfy memoryspacerestrictionsandboostmicrocontrollerspeedwhentestingandcomparingtwotypes ofMPPTs.Thiswouldalsoshortenthetimerequiredforhardwaresetup.Moreover,thecircuitin general could be changed so that it can provide power to the control circuit by utilizing MPPT- chargedbatteries.Overall,althoughweconcludethatwesatisfactorilydevelopedandimplemented a fuzzy logic-based maximum power point tracker for a photovoltaic power system, more work still needs to be done to convert lab prototype to a commercial product. This thesis provides a strong foundation for such work.
CHAPTER FIVE
5.1 CONCLUSION
In this paper, a PV system is interfaced to the grid via a multi functional interfacing inverter. A MPPT fuzzy logic controller is employed to feed the grid by the maximum allowable PV power. A simple predictive current control algorithm is used. The system performance is investigated using a MATLAB/Simulink model at different cases of load variation, atmospheric temperature variation and solar irradiation variation. The inverter achieves functions of supplying the available power from the PV unit into the load sin addition to improving the power quality interms of grid current THDand powerf actor.
5.2 RECOMMNENDATION
The aim of a photovoltaic power system is to provide only as much power as is needed, an approach known as power matching. In this approach, any power in a solar panel that remain snon- extracted(i.e., because it is not functioning at the current maximum power point) is then released as surface heat. To implement this approach in a real-life situation, such as, for instance, a water pump in are mote village, the MPPT circuit needs to have some way to know the amount of power requiredtoprovideappropriatemaximumpowertrackingtomeetthepowerneeds.Changessuch as these will significantly enhance the system’s functionality.
Futureworkcouldincludemethodsforapplyingafuzzylogicalgorithminadedicatedsingle-chip microcontroller.Aswell,aGalileoboardcouldbeusedratherthantwoArduinoboardstosatisfy memoryspacerestrictionsandboostmicrocontrollerspeedwhentestingandcomparingtwotypes ofMPPTs.Thiswouldalsoshortenthetimerequiredforhardwaresetup.Moreover,thecircuitin general could be changed so that it can provide power to the control circuit by utilizing MPPT- chargedbatteries.Overall,althoughweconcludethatwesatisfactorilydevelopedandimplemented a fuzzy logic-based maximum power point tracker for a photovoltaic power system, more work still needs to be done to convert lab prototype to a commercial product. This thesis provides a strong foundation for such work.
