A maximum power point prediction method for group control of photovoltaic water pumping systems based on parameter identification

[摘要] This paper puts forward a maximum power estimation method based on the photovoltaic array (PVA) model to solve the optimization problems about group control of the PV water pumping systems (PVWPS) at the maximum power point (MPP). This method uses the improved genetic algorithm (GA) for model parameters estimation and identification in view of multi P-V characteristic curves of a PVA model, and then corrects the identification results through least square method. On this basis, the irradiation level and operating temperature under any condition are able to estimate so an accurate PVA model is established and the MPP none-disturbance estimation is achieved. The simulation adopts the proposed GA to determine parameters, and the results verify the accuracy and practicability of the methods.

[发布机构] School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China^1

[效力级别] 机械制造 [学科分类] 航空航天科学

[关键词] Characteristic curve;Disturbance estimation;Least square methods;Model parameters estimation;Operating temperature;Optimization problems;Photovoltaic water pumping;Pv water pumping systems