Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization
Regular Papers|更新时间:2026-10-15
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Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization
Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization
中国电机工程学会电力与能源系统学报(英文)2024年10卷第2期 页码:660-671
作者机构:
Department of Electrical Engineering, Key Laboratory of Control of Power Transmission and Conversion of Ministry of Education, Shanghai Jiao Tong University
Jingyang Yun, Zheng Yan, Yun Zhou, 等. Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(2):660-671.
Jingyang Yun, Zheng Yan, Yun Zhou, et al. Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization[J]. CSEE Journal of Power and Energy Systems, 2024, 10(2): 660-671.
Jingyang Yun, Zheng Yan, Yun Zhou, 等. Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(2):660-671.DOI: 10.17775/CSEEJPES.2020.03720.
Jingyang Yun, Zheng Yan, Yun Zhou, et al. Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization[J]. CSEE Journal of Power and Energy Systems, 2024, 10(2): 660-671.DOI: 10.17775/CSEEJPES.2020.03720.
Multi-Time Collaborative Restoration for Integrated Electrical-Gas Distribution Systems Based on Rolling Optimization
This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution systems (IEGDSs) considering multiple resources after extreme weather events. Based on the linearized power flow constraints of the unbalanced electrical distribution system (EDS) and gas distribution system (GDS)
this problem can be formulated as a mixed-integer linear programming (MILP) model. To improve the efficiency and veracity of the solution
a rolling optimization based two-stage method is developed with the first stage solved by a linear approximation model
and the second stage solved by real-time updated rolling optimization. By solving the MILP problem using rolling optimization
the proposed model and solution method achieve efficient and reliable collaborative restoration of IEGDS considering multiple resources and unbalanced operation characteristics of EDS. The effectiveness of the proposed model and method is validated by using an IEGDS made of a 37-bus unbalanced EDS and 11-node GDS.