Electricity Market Price Prediction Based on Differential Evolutionary Algorithm and Neural Network

Yuetong Fu, Zheng Zhang, Tianran Li
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Abstract

In order to obtain a practical and high-precision prediction method of the clearing price in the spot market of electric power, this paper tries to apply the neural network optimized by differential evolutionary algorithm to the prediction of the clearing price in the spot market. Firstly, the weights and thresholds of BP neural network are optimized based on differential evolutionary algorithm, and then the BP neural network model is used to test on the basis of the PJM spot market data in the United States. The experiment shows that the prediction accuracy of the proposed method is improved obviously and the prediction effect is stable.
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基于差分进化算法和神经网络的电力市场价格预测
为了获得一种实用、高精度的电力现货市场出清价格预测方法,本文尝试将微分进化算法优化的神经网络应用于电力现货市场出清价格预测。首先基于差分进化算法对BP神经网络的权值和阈值进行优化,然后基于美国PJM现货市场数据对BP神经网络模型进行检验。实验表明,该方法的预测精度明显提高,预测效果稳定。
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