Fuzzy Logic Optimization Control Algorithm for Load of Photovoltaic Energy Storage Power Station Based on Deep Learning
The traditional load optimization control algorithm applied in photovoltaic energy storage stations cannot optimize and adjust the control based on real-time nonlinear load changes,resulting in waste of load power.A deep learning-based fuzzy logic optimization control algorithm for photovoltaic en-ergy storage station load is proposed to better adapt to changes in operating conditions of photovoltaic en-ergy storage stations.The unit failure trend is analyzed,the parameter degradation degree is calculated,the photovoltaic output situation is obtained,the load capacity of the energy storage power station unit is ob-tained,the load optimization model is established under fuzzy logic,the optimization objective function and power balance constraint conditions are established according to the fuzzy logic controller diagram,and the model is solved based on deep learning to realize the optimization of load distribution control.To verify the effectiveness of the design algorithm,a comparison is made between the traditional load control algorithm and the designed load control algorithm for photovoltaic energy storage stations.The results show that when considering the probability balance of power,the designed control algorithm has good response in terms of regulation,and there is no phenomenon of light abandonment,reducing the total output power of the power station.
deep learningphotovoltaic energy storage power stationfuzzy logicoptimize control algorithm
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