Semi-Supervised, Non-Intrusive Disaggregation of Nodal Load Profiles With Significant Behind-the-Meter Solar Generation
Semi-Supervised, Non-Intrusive Disaggregation of Nodal Load Profiles With Significant Behind-the-Meter Solar Generation
复制标题
DOI：
10.1109/tpwrs.2023.3334995
复制
发表时间：
2024-05
影响因子：
6.6
通讯作者：
Daniel Moscovitz;Zhenyu Zhao;Liang Du;Xiaoyuan Fan
中科院分区：
文献类型：
--
作者：
Daniel Moscovitz;Zhenyu Zhao;Liang Du;Xiaoyuan Fan
区域输电组织（RTO）的当务之急是有效地提取实际的负载分布在传输节点与显着的表后太阳能发电，这仍然是现有的技术范式的差距。本文提出了一个明确而有效的线性估计分解实际负载分布在传输总线与显着的表后（BTM）太阳能发电。所提出的估计量基于分解（即，提取）在考虑中的输电公交车附近的位置。为了克服缺乏基础事实并验证所提出的算法的性能，我们首先提出了具有参数调整和无监督聚类的半监督机制，并利用BTM太阳能峰值行为中零交叉点的独特特性，我们将其称为区域到节点（Z2N）方法。接下来，我们进一步提出了一个双层节点到节点（N2N）框架，与Z2N相比，该框架提高了整体分解性能。数值结果使用真实世界的数据在PJM互连。
It is of imperative interests for regional transmission organizations (RTOs) to effectively extract actual load profiles at transmission nodes with significant behind-the-meter solar generation, which remains a gap in the existing technology paradigm. This paper proposes an explicit yet efficient linear estimator to disaggregate actual load profiles at transmission buses with significant behind-the-meter (BTM) solar generations. The proposed estimator is based on disaggregating (i.e., extracting) at locations close to transmission buses under consideration. To overcome the lack of ground truth and validate the performance of the proposed algorithms, we first propose semi-supervised mechanisms with parameter tuning as well as unsupervised clustering and leverage the unique characteristics of zero-crossing points in BTM solar peaking behaviors, which we refer to as Zone-to-Node (Z2N) methods. Next, we further propose a bi-level Node-to-Node (N2N) framework that improves the overall disaggregation performances compared to Z2N. Numerical results are presented using real-world data at PJM Interconnection.