主动配电网的主动需求管理技术(Active Demand,AD)通过市场引导机制来改变用户的典型用电行为,电网负荷特性随之发生改变,降低了传统负荷预测技术的预测精度.针对AD对主动配电网负荷预测的影响,考虑用户响应特性分析影响AD响应负荷的因素,作为负荷预测的外生输入量,然后利用粒子群优化的支持向量机技术在黑盒框架下建立含AD输入的完备负荷预测模型,提出了适用于考虑主动需求的主动配电网负荷预测新方法.基于用户响应行为的现实考虑,建立时变AD模型产生含AD效应的负荷数据集来测试所提出的负荷预测方法.实验结果表明,所提负荷预测模型与不含AD输入的负荷预测模型相比,预测精度更高.%Active Demand (AD) of active distribution network changes user's typical power consumption behavior through market guidance mechanism,the load characteristics of power grid change accordingly,which reduces the accuracy of traditional load forecasting technology.To counter the influence of AD on load forecasting for active distribution network,this paper extracts the variables that affect the AD response load as the exogenous input of load forecasting by considering user's response feature,establishes the complete load forecasting model containing AD input under black box framework based on support vector machine optimized by particle swarm,and proposes a new load forecasting method for active distribution network considering AD.Based on practical considerations about consumers' behavior,a time-varying AD model is built to produce a data set of load including AD effect to test the proposed load forecasting method.The experimental results show that the proposed load forecasting model is more accurate than the load forecasting model without AD input.
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