A distributed state estimation method for power systems incorporating linear and nonlinear models. (January 2015)

• Record Type: Journal Article
• Authors: Guo, Ye; Wu, Wenchuan; Zhang, Boming; Sun, Hongbin
• Is Part Of: International journal of electrical power & energy systems. Volume 64(2015:Jan.)
• Page Start: 608
• Page End: 616
• Publication Date: 2015-01
• Subjects: State estimation -- Distributed state estimation -- Phasor measurement units; 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.2014.07.053
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A distributed state estimation method is proposed for power system combined with PMUs observable and RTUs observable areas. This distributed SE method needs no iterations on coordination level. Those centralized algorithms can be easily distributed according to the proposed method. Abstract: High-voltage transmission networks are commonly equipped with phasor measurement units (PMU), and some of them are PMU observable. However, PMUs are seldom installed in distribution networks due to budget limitations. The state estimation equations of PMU observable areas are linear, while those of other areas remain nonlinear. This paper proposes a new distributed state estimation method for solving multi-area state estimation problems, in which linear models are used for high-voltage transmission network, while nonlinear models are adopted for other areas. In PMU observable area, we select coordinating variables as generalized cost functions which accurately represent the sensitivity between the linear SE objective function and boundary states. Consequently, SE results identical to a centralized estimator can be obtained without iterations at the coordination level. This paper presents the problem model and theoretical analysis of the proposed method, and shows its effectiveness by numerical tests.