摘要
针对需求响应的实施对电力系统短期负荷预测带来的新挑战,本文构建了计及尖峰电价需求响应机制的电力系统短期负荷预测模型。研究了基于尖峰电价的需求响应机理,依据基于消费者心理学的用户响应模型,对实施需求响应后的负荷序列进行模拟。同时,构造了Elman神经网络短期负荷预测模型,由于Elman神经网络的承接层反馈使其具有较好的动态存储功能,使模型对非线性负荷序列具有良好的预测性能,并给出实际算例进行仿真分析。仿真结果表明,采用计及尖峰电价需求响应机制的Elman神经网络预测模型,能较准确预测在需求响应策略影响下负荷曲线的变化,最大相对误差为4.34%,平均绝对误差为2.14%;而未考虑需求响应的Elman神经网络预测模型,预测精度明显较低,其最大相对误差为10.76%,平均绝对误差为6.71%,说明将需求响应作为影响因素的预测模型可有效提高模型的预测精度。该研究为计及需求响应的短期负荷预测提供了理论依据。
In view of the new challenges brought by the implementation of demand response to short-term load forecasting of power system,this paper constructs a short-term load forecasting model of power system considering the demand response mechanism of peak electricity price.The demand response mechanism based on peak electricity price is studied,and the load sequence after implementing demand response is simulated according to the user response model based on consumer psychology.At the same time,a short-term load forecasting model based on Elman neural network is constructed.Because of the feedback of the receiving layer of Elman neural network,it has better dynamic storage function,which makes the model have good forecasting performance for the non-linear load series.The simulation analysis is carried out by an actual example.The simulation results show that the Elman neural network forecasting model considering the demand response mechanism of peak electricity price can accurately predict the change of load curve under the influence of demand response strategy,with the maximum relative error of 4.34% and the average absolute error of 2.14%.The Elman neural network forecasting model without considering demand response has obviously lower forecasting accuracy,with the maximum relative error of 10.76%.The average absolute error is 6.71%,which shows that the prediction model with demand response as the influencing factor can effectively improve the prediction accuracy of the model.This study provides a theoretical basis for short-term load forecasting considering demand response.
引文
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