Short-term Load Prediction of Electric Vehicle Charging Stations built on GA-BPNN Model

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In response to the rapid growth of electric vehicles (EVs), the expanding charging demand significantly impacts the distribution network, and load prediction for EV charging stations is required. We combine the genetic algorithm and BPNN to achieve a more accurate and efficient prediction effect for electric vehicle charging stations. It adopts GA to optimize the weights and thresholds of BPNN to obtain the optimal solution of the BP neural net prediction model, thus establishing a BPNN prediction model built on GA. We apply this model to the load prediction of actual EV charging stations. The MATLAB simulation study shows that the prediction model optimized by GA acquires higher accuracy and better practicability than the unoptimized prediction model.