Control of Bidirectional DC-DC Converter for Photovoltaic Energy Storage based on ISMA-BP Neural Network
the anti-interference issues of bidirectional DC-DC converters for photovoltaic energy storage is researched,and a control method for bidirectional DC-DC converters for photovoltaic energy storage based on ISMA-BP neural network is proposed.The dual closed-loop model for the bidirectional DC-DC converter is established,and the fuzzy neural network optimized PID controller to control the voltage outer loop is used.Secondly,the multi subpopulation and multi evolutionary strategy slime mould algorithm(SMA)is designed to improve the global optimization accuracy.The improved SMA(ISMA)is used to initialize the parameters of the BP neural network,in order to enhance the stability of the BP neural network control.Finally,the ISMA-BP neural network is used to dynamically adjust the parameters of the PID controller in real-time,achieving stable control of the output voltage of the converter.The simulation results show that the proposed bidirectional DC-DC converter control method has good rate stability and strong anti-interference ability.
photovoltaic power generationenergy storagebidirectional DC converterslime mould algorithmBP neural networkPID control
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