{"title":"Robust transmission-constrained unit commitment considering robust economic redispatch: A tri-stage five-level structure","authors":"Fawzy A. Bukhari, Khalid A. Alnowibet","doi":"10.1016/j.segan.2025.101642","DOIUrl":null,"url":null,"abstract":"<div><div>Integrating renewable energy sources (RESs) into power systems increases operational uncertainty and threatens their efficiency. Hence, it is imperative to devise effective techniques to handle the uncertainty and mitigate the variability impacts of RESs in a transmission-constrained unit commitment (TCUC) problem. We propose a novel robust TCUC (RTCUC) model considering the robust economic redispatch (RERD) problem (balancing problem). To this end, a tri-stage, five-level hierarchical framework is constructed with two successive <em>min-max-min</em> structures. A conventional RTCUC problem is formulated as a <em>min-max-min</em> problem where the first stage decides on commitment statuses, and the second stage determines the generation scheduling using an economic dispatch model. In this paper, we change this conventional model by revisiting the second stage and formulating it as another <em>min-max-min</em> problem whose first stage determines the optimal base generation. Its second stage identifies the optimal generation re-scheduling (GRS) solution using an economic redispatch model. Thus, the whole problem is established based on a tri-stage <em>min-max-min-max-min</em> structure. The proposed problem is solved using the nested primal Benders decomposition (PBD) algorithm. The numerical studies reveal the outperformance of the proposed RTCUC model over the conventional models.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101642"},"PeriodicalIF":4.8000,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467725000244","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Integrating renewable energy sources (RESs) into power systems increases operational uncertainty and threatens their efficiency. Hence, it is imperative to devise effective techniques to handle the uncertainty and mitigate the variability impacts of RESs in a transmission-constrained unit commitment (TCUC) problem. We propose a novel robust TCUC (RTCUC) model considering the robust economic redispatch (RERD) problem (balancing problem). To this end, a tri-stage, five-level hierarchical framework is constructed with two successive min-max-min structures. A conventional RTCUC problem is formulated as a min-max-min problem where the first stage decides on commitment statuses, and the second stage determines the generation scheduling using an economic dispatch model. In this paper, we change this conventional model by revisiting the second stage and formulating it as another min-max-min problem whose first stage determines the optimal base generation. Its second stage identifies the optimal generation re-scheduling (GRS) solution using an economic redispatch model. Thus, the whole problem is established based on a tri-stage min-max-min-max-min structure. The proposed problem is solved using the nested primal Benders decomposition (PBD) algorithm. The numerical studies reveal the outperformance of the proposed RTCUC model over the conventional models.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.