基于云理论的中长期负荷预测

Mid-long Term Load Forecasting Based on Cloud Theory

针对中长期电力负荷预测,选取了7个影响因素:最高温度、湿度、居民人均支出、人口增长率、经济发展情况、电价、消费价格指数,并基于云的模糊性和随机性,针对每个因素建立相应的云推理规则,以收集到的样本数据作为输入,通过云推理形成客观评分矩阵,然后基于评分矩阵,结合关联度分析法计算各影响因素的客观权重,最后利用地区发展的相似性确定未来负荷的增长趋势,采用模糊聚类的方法对算例进行预测。算例结果表明该方法预测精度高,具有较强的可操作性。

In this paper, such seven infulence factors as highest temperature, humidity, the percent of hibitatent, population growth, economic development conditions, electricity price and consumer price index, are selected to study midlong term load forecasting. Based on the fuzziness and randomness of the cloud, the cloud reasonning rules are established for each factor. The collected sample data being input, through reasonning to form objective scoring matrix, the objective weights of each influence factor are computed by combining correlative degree analysis method based on scoring matrix. In the end, the growing trend of future load is determined by the similiarity of district development, and the forecasting is carried out by fuzzy clustering method for an example. The results show that the method has high pre- cision and strong operationality.