An improved power flow calculation method based on linear regression for multi-area networks with information barriers. (November 2022)

• Record Type: Journal Article
• Authors: Dong, Xiaoming; Ma, Yue; Wang, Yong; Chen, Quan; Liu, Zhengqi; Jia, Xueyong
• Is Part Of: International journal of electrical power & energy systems. Volume 142:Part B(2022)
• Publication Date: 2022-11
• Subjects: Power system analysis computing -- Power flow calculation -- Locally weighted linear regression -- Power system interconnection -- Automatic generation control; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108385
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A decomposition-coordination PFC model is proposed for the interconnection system. The LWLR combining with the Ridge Regression is employed into the PF model. The used cases demonstrate the efficiency of the proposed method in PFC. The proposed PF model can be used to analyzing the cause of numerical ill-conditions. Abstract: For multi-area interconnected power networks, energy interchange among subareas is benefit to improve energy utilization. The regulators of different subareas are generally incapable to access the private system information from others, which makes the information barriers. Then, the conventional integrated Power Flow (PF) method based on complete network information show incapability in analyzing operation state for multi-area systems. To generate the same PF solution as that by integrated method, an optional approach is to separately run PF Calculation (PFC) for each subarea alternated with the adjustment of state variables for boundary buses. Thus, this study proposes a decomposition-coordination PF model with two layers of coordination. Moreover, incorporated with the Ridge Regression, an improved Locally Weighted Linear Regression (LWLR) approach is established in treating the adjustment of boundary variables. Case studies based on IEEE300 and IEEE RTS-1996 test systems demonstrate the efficiency of the proposed method, which generates PF results with high accuracy and convergence in case of less data requirement compared to conventional Newton's method. Furthermore, the proposed PF method is capable to identify the subarea with potential questionable data in case of PFC divergence, contributing to analyzing the cause of numerical ill-conditions.