A distributed calculation method for robust day-ahead scheduling of integrated electricity-gas systems

Gang Zhang, Feng Zhang*, Ke Meng, Zhaoyang Dong

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

14 Citations (Scopus)

Abstract

The urgency to address the uncertainty in the day-ahead scheduling (DAS) of integrated electricity and natural gas systems (IEGSs) has been highlighted, and the robust optimization has been proven to be an effective method. However, the gas system and electricity system are generally operated by different utilities in practice, i.e., gas system operator (GSO) and electricity system operator (ESO), which poses a considerable challenge to solve this two-stage mixed-integer nonlinear DAS model due to the limit on information sharing. In this paper, a novel distributed calculation method is proposed to solve the robust DAS model of IEGSs in a decentralized way. First, a mixed-integer master problem and a non-convex max–min subproblem can be obtained from the original DAS model by employing the column and constraint generation (CCG) method. Afterwards, based on the limited information exchange between ESO and GSO, an innovative decomposition method is proposed for the master problem to obtain the optimal DAS solution, and then a novel inner CCG algorithm is presented for the subproblem to guarantee the security of IEGSs. By doing so, the robust DAS of IEGS is decomposed into several mixed-integer linear programming (MILP) problems, and GSO and ESO can coordinately solve these MILPs with limited information sharing. Last, numerical tests on two IEGSs verify the superiority of the proposed method in hedging against the wind uncertainty and achieving the solution optimality. © 2021 Elsevier Ltd
Original languageEnglish
Article number107636
JournalInternational Journal of Electrical Power and Energy Systems
Volume136
Online published8 Oct 2021
DOIs
Publication statusPublished - Mar 2022
Externally publishedYes

Research Keywords

  • Day-ahead scheduling
  • Distributed calculation
  • Multi-energy system
  • Robust optimization

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