Service restoration for distribution network with DGs based on stochastic response surface method. (May 2019)

• Record Type: Journal Article
• Authors: Wang, Feng; Xiao, Xuanyi; Sun, Qiuqin; Chen, Chun; Bin, Feng; Chen, She; Fan, Jingmin
• Is Part Of: International journal of electrical power & energy systems. Volume 107(2019)
• Page Start: 557
• Page End: 568
• Publication Date: 2019-05
• Subjects: 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.2018.12.015
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A service restoration model based on SRSM is proposed. A restoration strategy of joint planning of reconfiguration & islanding is proposed. An islanding partition method based on depth first search is proposed. The process of restoration based on SRSM and restoration strategy is proposed. Abstract: In order to deal with the uncertainty of renewable distributed generators (DGs) and load under fault conditions in distribution network, a service restoration method based on stochastic response surface method (SRSM) is proposed. After the input variables are processed by correlation, chaotic second-order polynomials are introduced, and the probability distributions of each state variable are obtained by solving its coefficients. Moreover, network reconfiguration is combined with intending islanding to resolve the service restoration problem in the distribution network. For a network structure that does not satisfy the probability constraint, the load is cut until it is satisfied. In the iterative process of service restoration algorithm, the stochastic response surface method is adopted to deal with the uncertainty, which can maximize power supply recovery of outage areas under the premise of satisfying the probability constraint. The proposed method is applied to the IEEE 33-bus system and TPC 84-bus system for testing. The comparison with other algorithms validates the correctness and effectiveness of the proposed method.