基于随机森林非侵入式负荷分解的地区居民需求响应能力评估

需求响应在缓解供电不足、促进新能源消纳以及节约发电侧的资源投资方面意义重大,而需求响应能力评估可以为需求响应策略的制定提供依据。为解决需求响应能力评估困难的问题,本文提出一种基于非侵入式负荷分解的地区居民响应能力评估的方法。首先建立基于随机森林算法的非侵入式负荷分解模型,再使用该模型针对性的分解出单个用户的可中断负荷,然后基于可中断负荷的用电情况计算出单个用户在各个时刻的响应能力,最后再将区域内的所有用户聚合即可得到地区居民总的响应能力。在真实数据集上进行验证,结果表明所提出的基于随机森林非侵入式负荷分解模型可以更精确的得到用户可中断负荷的有功功率值,地区有功功率聚合误差也更小,可以较好的进行需求响应能力评估。

Regional residential demand responsiveness assessment based on random forest non-intrusive load decomposition

Demand response is significant in alleviating power supply shortage, promoting new energy consumption and saving resource investment on the generation side, while demand response capability assessment can provide a basis for the formulation of demand response strategies. In order to solve the problem of difficult demand response capacity assessment, this paper proposes a method for regional residential response capacity assessment based on non-intrusive load decomposition. First, a non-intrusive load decomposition model based on random forest algorithm is established, and then the interruptible load of individual customers is decomposed by this model, and then the responsiveness of individual customers at each moment is calculated based on the interruptible load usage, and finally the total responsiveness of area residents is obtained by aggregating all customers in the area. The results show that the proposed random forest-based non-intrusive load decomposition model can obtain more accurate active power values of interruptible loads of customers, and the regional active power aggregation error is also smaller, which can be better for demand responsiveness assessment.