Sashuang Sun , YouBo Liu , Zhiyuan Tang , Mengfu Tu , Xili Du , Junyong Liu
{"title":"A hybrid stochastic-robust bidding model for wind-storage system in day-ahead market considering risk preference","authors":"Sashuang Sun , YouBo Liu , Zhiyuan Tang , Mengfu Tu , Xili Du , Junyong Liu","doi":"10.1016/j.epsr.2024.111148","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, a novel hybrid stochastic-robust bidding model for a wind-storage system in the day-ahead (DA) market considering risk preferences is proposed. In the proposed scheme, the uncertainties of wind power and DA electricity price are firstly accounted for through stochastic optimization (SO) and robust optimization (RO) models. Then, to combine the advantages of both SO and RO models, based on the Hurwicz optimistic coefficient, a hybrid stochastic-robust bidding model is formulated for wind-storage systems, where wind farm bidders can select bidding strategies with different risk levels. Additionally, to reflect a more realistic operating cost of Energy Storage System (ESS), the ESS life degradation model based on equivalent full cycle counts is embedded into this hybrid model. To make the proposed non-convex hybrid bidding model computationally tractable, strong duality theory and piecewise linear functions are employed to transform it into a mixed integer linear programming (MILP) problem, which can be efficiently solved with the off-the-shelf optimization software. The simulation results demonstrate that the proposed bidding model effectively handles various scenarios and enables the selection of appropriate strategies under different risk preferences.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"238 ","pages":"Article 111148"},"PeriodicalIF":3.3000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378779624010344","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a novel hybrid stochastic-robust bidding model for a wind-storage system in the day-ahead (DA) market considering risk preferences is proposed. In the proposed scheme, the uncertainties of wind power and DA electricity price are firstly accounted for through stochastic optimization (SO) and robust optimization (RO) models. Then, to combine the advantages of both SO and RO models, based on the Hurwicz optimistic coefficient, a hybrid stochastic-robust bidding model is formulated for wind-storage systems, where wind farm bidders can select bidding strategies with different risk levels. Additionally, to reflect a more realistic operating cost of Energy Storage System (ESS), the ESS life degradation model based on equivalent full cycle counts is embedded into this hybrid model. To make the proposed non-convex hybrid bidding model computationally tractable, strong duality theory and piecewise linear functions are employed to transform it into a mixed integer linear programming (MILP) problem, which can be efficiently solved with the off-the-shelf optimization software. The simulation results demonstrate that the proposed bidding model effectively handles various scenarios and enables the selection of appropriate strategies under different risk preferences.
期刊介绍:
Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview.
• Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation.
• Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design.
• Substation work: equipment design, protection and control systems.
• Distribution techniques, equipment development, and smart grids.
• The utilization area from energy efficiency to distributed load levelling techniques.
• Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.