摘要
<span style="font-family:Verdana;">The target of this paper is to model a Maximum Power Point Tracker (MPPT) using a Fuzzy Logic Control (FLC) algorithm and to investigate its behavior with a battery load. The advantage of this study over other studies in this field is that it considers a battery load rather than the commonly used</span><span></span><span></span><b><span><span></span><span></span> </span></b><span style="font-family:Verdana;">resistive load especially when we deal with the relationship between MPPT and system load. The system is about 60</span><span style="font-family:""> </span><span style="font-family:Verdana;">kW which </span><span style="font-family:Verdana;">is </span><span style="font-family:Verdana;">simulated under various environmental conditions by Matlab/Simulink program. For this type of non-linear application, FLC naturally offers a superior controller for </span><span style="font-family:Verdana;">the </span><span style="font-family:Verdana;">real load case. The artificial intelligence approach also benefits from this method for overcoming the complexity of nonlinear system modelling. The results show that FLC provides high performance for MPPT of PV system with battery load due to its low settling time and limited oscillation around the steady state value. These are</span><span style="font-family:""> </span><span style="font-family:Verdana;">assistant factors for increasing battery life.</span>
<span style="font-family:Verdana;">The target of this paper is to model a Maximum Power Point Tracker (MPPT) using a Fuzzy Logic Control (FLC) algorithm and to investigate its behavior with a battery load. The advantage of this study over other studies in this field is that it considers a battery load rather than the commonly used</span><span></span><span></span><b><span><span></span><span></span> </span></b><span style="font-family:Verdana;">resistive load especially when we deal with the relationship between MPPT and system load. The system is about 60</span><span style="font-family:""> </span><span style="font-family:Verdana;">kW which </span><span style="font-family:Verdana;">is </span><span style="font-family:Verdana;">simulated under various environmental conditions by Matlab/Simulink program. For this type of non-linear application, FLC naturally offers a superior controller for </span><span style="font-family:Verdana;">the </span><span style="font-family:Verdana;">real load case. The artificial intelligence approach also benefits from this method for overcoming the complexity of nonlinear system modelling. The results show that FLC provides high performance for MPPT of PV system with battery load due to its low settling time and limited oscillation around the steady state value. These are</span><span style="font-family:""> </span><span style="font-family:Verdana;">assistant factors for increasing battery life.</span>
