Abstract: As power load forecasting grows quickly, the traditional gray prediction model GM（1, 1） becomes worse. According to the shortcoming, in this article a new improved bi-group Evolutionary Strategy Optimization Grey Model is proposed, combining the advantage about evolutionary strategy in solving parameter with GM（1, 1） model, and then the parameters about GM（1, 1） are solved by using evolutionary strategy algorithm. The power load forecast example indicates that the model gives better precision and has wider application field.

Key words: power load forecasting, grey model, bi-group, evolutionary strategy algorithms

摘要： 传统灰色预测模型GM（1，1）在预测增长较快的电力负荷时效果会变差。针对这一缺陷，提出了一种改进的双种群ESOGM模型，将进化策略对参数优化处理的优点与GM（1，1）模型相结合，利用进化策略算法优化模型中的参数。电力负荷预测实例表明该模型具有较高的预测精度和较广的应用范围。

关键词: 电力负荷预测, 灰色模型, 双种群, 进化策略算法