A surrogate-assisted point estimate method for hybrid probabilistic and interval power flow in distribution networks. (November 2022)

• Record Type: Journal Article
• Authors: Wang, Chenxu; Peng, Yan; Zhou, Yixi; Ma, Junchao; Lu, Chengyu; Yang, Xiyun
• Is Part Of: Energy reports. Volume 8(2022)Supplement 13
• Page Start: 713
• Page End: 721
• Publication Date: 2022-11
• Subjects: Uncertain power flow -- Hybrid uncertainties -- Distributed generators -- Point estimate method -- Surrogate model; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2022.08.044
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: The uncertain power flow analysis is essential to assessing the operating states of distribution networks under various uncertainties. The power flow calculations considering the single uncertainty have been well developed. However, different types of uncertainties may coexist in power systems. In order to comprehensively assess the impacts of mixed uncertainties, this paper proposes a surrogate-assisted point estimate method to solve the hybrid probabilistic and interval power flow. By taking advantage of the point estimate method and high-fidelity surrogate model, the proposed method can accurately obtain the relevant results of power flow calculation with high efficiency. The numerical studies in IEEE 33-bus and 141-bus systems verify the accuracy and efficiency of the proposed method by comparing it with other well-known methods.