云模型理论在月售电量预测中的应用研究

Application research of cloud model theory in month electricity consumption forecasting

针对售电量预测中无法计及气温变化及变化持续时间影响的难点,提出了基于云模型及比重法的月售电量预测算法。在考虑传统售电量预测中经济因素影响的基础上,利用云规则发生器获得日气温对于各个气温及持续时间长短定性云规则的隶属程度,同时利用逆向云发生器计算获得各月售电量比重的云模型定性概念的数字特征值,以隶属度及总评估进行月售电量的预测研究。仿真结果显示,考虑气温影响因素的月售电量预测模型较为全面、准确。

Against the troublesome problems in electricity consumption forecasting that are unable to take the variety and duration time of temperature into account, a new method based on cloud model and proportion method is proposed to do month electricity consumption forecasting. Considering the influence of economic ＆ctors in traditional forecasting models, the new method calculates the subordination degree to describe the variety and duration time of the temperature by cloud regulation generators. At the same time, the cloud model qualitative concept digital eigen-value of each month＇s electricity consumption proportion is calcu-lated with the help of reverse cloud generator. This paper does the month electricity consumption forecasting research based on the subordination degree and the evaluation. The simulation result displays that the forecasting model taking the aspect of temperature into account is more comprehensive and accurate.