IGDT-Based Complementarity Approach for Dealing With Strategic Decision Making of Price-Maker VPP Considering Demand Flexibility

被引:62
作者
Gazijahani, Farhad Samadi [1 ]
Salehi, Javad [1 ]
机构
[1] Azarbaijan Shahid Madani Univ, Dept Elect Engn, Tabriz 53714161, Iran
关键词
Cogeneration; Mathematical model; Uncertainty; Informatics; Contracts; Real-time systems; Demand flexibility; profit maximization; renewable energy; uncertainty modeling; virtual power plant; VIRTUAL POWER-PLANT; OFFERING STRATEGY; MODEL; MARKETS;
D O I
10.1109/TII.2019.2932107
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we outline a novel bilevel decision-making framework for a price-maker virtual power plant (VPP) to participate in both day-ahead and balancing oligopoly markets considering multiple forward contracts. In principle, the VPP operator with having the possession of financial transmission rights can manage its financial risk through trading electricity among various markets such as centralized pool and contract markets aimed at maximizing its own profit and minimizing the associated risk. Besides, the VPP operator will be able to optimize its procurement expenditures by incentivizing flexible demands proportion to different electricity tariffs. In the proposed bilevel model, the VPP aggregator strives to maximize its own profit at the upper level while an independent system operator seeks to clear both markets at the lower levels with an eye to maximize social welfare. Each lower level is then replaced by its complementarity slackness conditions and, consequently, is recast as a mathematical program with equilibrium constraints that can be solved using off-the-shelf software packages. Furthermore, the uncertainty pertaining to renewables has been envisaged through information gap decision theory resulting in robustness & x002F;opportunity function to deal with self-scheduling of VPP. This article ends up with different illustrative case studies through performing after-the-fact actual market data to verify the applicability of the model.
引用
收藏
页码:2212 / 2220
页数:9
相关论文
共 28 条
[1]   Optimal Demand Response Bidding and Pricing Mechanism With Fuzzy Optimization: Application for a Virtual Power Plant [J].
Al-Awami, Ali T. ;
Amleh, Nemer A. ;
Muqbel, Ammar M. .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2017, 53 (05) :5051-5061
[2]  
[Anonymous], NAT HOUS TRAV SURV N
[3]  
[Anonymous], SES6518272
[4]  
[Anonymous], MARKET OPERATIONS EL
[5]   A Stochastic Adaptive Robust Optimization Approach for the Offering Strategy of a Virtual Power Plant [J].
Baringo, Ana ;
Baringo, Luis .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (05) :3492-3504
[6]  
Ben-Haim Y., 2006, Academic
[7]   Optimal response of an oligopolistic generating company to a competitive pool-based electric power market [J].
Conejo, AJ ;
Contreras, J ;
Arroyo, JM ;
de la Torre, S .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (02) :424-430
[8]   Optimal Offering and Operating Strategy for a Large Wind-Storage System as a Price Maker [J].
Ding, Huajie ;
Pinson, Pierre ;
Hu, Zechun ;
Wang, Jianhui ;
Song, Yonghua .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (06) :4904-4913
[9]  
Gabriel SA, 2012, Complementarity modeling in energy markets, V180
[10]   Optimal Bilevel Model for Stochastic Risk-Based Planning of Microgrids Under Uncertainty [J].
Gazijahani, Farhad Samadi ;
Salehi, Javad .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (07) :3054-3064