基于负荷分解的日最大负荷预测方法研究

提出了1种基于负荷分解的日最大负荷预测算法，即将负荷分解为正常负荷分量和天气敏感负荷分量，用结合指数趋势和周期趋势的组合模型预测正常负荷分量．用神经网络法预测天气敏感负荷分量。同时，在分析最大负荷和人体舒适度相关性的基础上，在预测中用人体舒适度替代了常规气象因子。预测结果表明，该方法可以取得较为满意的预测效果。

Maximum load forecasting method based on load resolution

This paper presents an arithmetic based on load-decomposition which divides daily maximum load into normal load and weather sensitive load. It uses composite model combining exponential increasing trend and cycle trend to forecast the normal load and uses artificial neural network to forecast weather sensitive load. While modeling, the paper uses human body amenity to replace previous conventional climaticgene based on the relativity between human body amenity and the maximum load. The result indicates that using human body amenity to forecast the maximum load is feasible.