Distributed chance-constrained based total energy supply capability evaluation method for integrated power and natural gas system. (October 2022)

• Record Type: Journal Article
• Authors: Wu, Zhi; Sun, Qirun; Lu, Yuping; Gu, Wei; Liu, Pengxiang; Dai, Renjie; Wei, Siming
• Is Part Of: International journal of electrical power & energy systems. Volume 141(2022)
• Publication Date: 2022-10
• Subjects: Total energy supply capacity -- Integrated power and and natural gas system -- Joint chance constraint -- Distributed optimization; 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.2022.108193
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A distributed TESC evaluation model for IDGS is proposed. Uncertainties of WTs are modeled via a novel Boolean reformulation method with JCCs. ATC algorithm is utilized to keep the information privacy of the PDS and NGS. A double-loop solution procedure is developed for solving the proposed model. Abstract: With the development of gas turbines and power to gas technologies, the modern energy infrastructure has evolved into a coupled power and natural gas system. To fully exploit the maximum total energy supply capability (TESC) of the integrated power distribution and natural gas system (IDGS), a distributed chance-constrained based TESC evaluation method with consideration of wind power uncertainties is proposed in this paper, which can be utilized as a guideline for the planning, operation and reliability assessment of the IDGS. Specifically, to preserve the privacy of the operation data shared among power distribution system (PDS) and natural gas system (NGS), the established TESC model is solved in a distributed manner based on the analytical target cascading (ATC) algorithm. In the PDS and NGS sub-problems, the difference-of-convex programming (DCP) algorithm is utilized to deal with the nonconvex power flow and Weymouth gas flow equations to guarantee the feasibility of the solution results. Moreover, the uncertain nature of wind power is incorporated into the model and represented by a set of joint chance constraints (JCCs) with a predefined confidence level, which can be effectively solved via a novel Boolean reformulation method. Numerical studies are performed on a modified 94-bus distribution system and 20-node natural gas system to verify the effectiveness of the proposed model and solution methodology.