基于城市居民峰谷电价响应特性的超短期负荷预测研究

Research on Ultra Short Term Load Forecasting Based on Response Characteristics of Urban Resident Under the Peak-valley Electricity Price

由于峰谷电价的逐步实施,电价对用户负荷特性的影响也逐渐凸显,而当前进行负荷预测时,未考虑峰谷电价变化影响,电价变化点附近的负荷预测精度相对较低。采用电价变化点负荷增长率作为描述居民峰谷电价响应特性指标,研究了城市居民峰谷电价响应特性,并进一步分析了负荷增长率的时域特性。在此基础上,用负荷增长率修正人工神经网络预测模型来考虑峰谷电价的影响作用,对响应峰谷电价敏感的时段进行了超短期负荷预测。研究结果表明,用电价变化点负荷增长率考虑峰谷电价影响可以提高电价变化后超短期负荷预测的精度。

Due to the gradual implementation of peak and valley electricity price,the impact of electricity price on the load characteristics of users is also gradually prominent.Currently,load forecasting has not taken the impact of peak and valley electricity price change into consideration.The accuracy of load forecasting near the change point of electricity price is relatively low.In this research,the load growth rate at the change point of electricity price is used as the index to describe the response characteristics of residential peak and valley electricity price for understanding response characteristics of urban residential peak and valley electricity price.The time-domain characteristics of load growth rate are further analyzed.On this basis,the load growth rate is used to modify the artificial neural network forecasting model to consider the impact of peak and valley price and the ultra-short term load forecasting is carried out in response to the sensitive period of peak and valley price.The results show that the accuracy of ultra-short term load forecasting can be improved by considering the peak valley price effect with the load growth rate at the price change point.