【摘要】 为了提高某一个省短期电力负荷预测的精度,应该充分利用全省各个地区的气象因素。以湖南省为例,采用粒子群算法来优化湖南省14个地区气温的权值比率,用各地区的气温加权平均得到一个最合适的全局气温。优化后的气温与全省电力负荷的关联度更高。以该气温作为负荷预测系统的输入气温,提高了负荷预测的精度。算例分析结果证明了该方法的有效性。更多还原

【Abstract】 In order to forecast the short-term power load more accurate,the meteorological factors in various regions across the province should be fully made use.Take Hunan Province as an example,the weight ratios of temperatures of the 14 regions of Hunan Province is got by using the Particle Swarm Optimization,which gives us a good weighted average global temperature.The optimized temperature is related to the power load of Hunan Province more closely.Take the optimized temperature as the input of the load forecast system,which can improve the precision of load forecasting.Examples show the effectiveness of the method.更多还原