Abstract
Peak load and frequency modulation is an important task in grid scheduling. In this paper, we proposed a peak load and frequency control strategy with deep learning method. In this strategy, we used deep learning method to forecast the power load curve, and combine the predicted load curve with real-time load power in grid to control the distributed thermal storage electric boiler to help regulating peak load and frequency. In this paper, we used LSTM method to forecast load power, and compare the results with SVM method. The deep learning control strategy about peak load regulation and frequency regulation with distribution thermal storage electric boiler improve responding speed and redundancy of load peak and frequency modulation.
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