The present study explores the use of clustering techniques for the design and implementation of a demand response (DR) program for commercial and residential prosumers. The goal of the program is to shift the participants' consumption behavior to mitigate two issues a) the reverse power flow at the primary substation, that occurs when generation from solar panels in the local grid exceeds consumption and b) the system wide peak demand, that typically occurs during hours of the late afternoon. For the clustering stage, three popular algorithms for electrical load clustering are employed -- namely k-means, k-medoids and a hierarchical clustering algorithm -- alongside two different distance metrics -- namely euclidean and constrained Dynamic Time Warping (DTW). We evaluate the methods using different validation metrics including a novel metric -- namely peak performance score (PPS) -- that we propose in the context of this study. The best setup is employed to divide daily prosumer load profiles into clusters and each cluster is analyzed in terms of load shape, mean entropy and distribution of load profiles from each load type. These characteristics are then used to distinguish the clusters that would be most likely to aid with the DR schemes would fit each cluster. Finally, we conceptualize a DR system that combines forecasting, clustering and a price-based demand projection engine to produce daily individualized DR recommendations and pricing policies for prosumers participating in the program. The results of this study can be useful for network operators and utilities that aim to develop targeted DR programs for groups of prosumers within flexible energy communities.
翻译:本研究探索使用集群技术来设计和实施商业和住宅造价公司的需求反应(DR)方案。本方案的目标是改变参与者的消费行为,以减少两个问题:(a) 初级分站的逆向电流,即当当地电网太阳能电池板的发电量超过消耗量时出现的反向电流;(b) 全系统的峰值需求,通常是在下午晚些时候发生的。在集群阶段,采用了三种通用的电荷组合算法 -- -- 即k值、 k-Medids和等级组合算法 -- -- 以及两种不同的远程计量法 -- -- 即euclidean和限制的动态时间扭曲社区。我们评估了不同验证指标的方法,包括我们在本研究中提议的新型衡量标准,即最高性能评分(PPSS) -- -- 最佳配置用于将每天的造纸机负载量剖分分为各组,对每组的载量形状、平均值和每类负载量剖面算法进行分析。这些特征用于区分最有可能帮助进行准确度时间转换的社区(euclideide)的集群,我们用新鉴定了这个网络的能源运行程序,然后将每个预测方案与每一组合组合组合用于计算价格方案,我们把每一组合的能源预测方案与每一组合用于计算。</s>