An optimization-based partial marginal pricing method to reduce excessive consumer payment in electricity markets

被引:0
|
作者
Wang, Yi [1 ]
Yang, Zhifang [1 ]
Yu, Juan [1 ]
Liu, Junyong [2 ]
机构
[1] Chongqing Univ, Coll Elect Engn, State Key Lab Power Transmiss Equipment & Syst Sec, Chongqing 400030, Peoples R China
[2] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Sichuan, Peoples R China
关键词
Electricity market; Pricing scheme; Consumer payment; Strategic bidding; Locational marginal price; MINIMIZATION; UNIFORM;
D O I
10.1016/j.apenergy.2023.121935
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Among the pricing schemes, locational marginal pricing is the most widely adopted scheme in current electricity markets. Despite the nice properties, theoretical study and practical experience have shown that considering the strategic bidding behaviors of market participants, locational marginal pricing may result in excessive consumer payment and prejudices market efficiency. In this paper, we propose an optimization-based partial marginal pricing method to reduce consumer payment under strategic bidding. The advantages of the locational marginal pricing method are reserved to the best extent while the remaining problems are delicately handled. To achieve this, we first analyze the characteristics and problems of the locational marginal pricing scheme and present a partial marginal pricing structure. Second, we establish an optimization-based partial marginal pricing model, in which discriminatory price components are introduced in price formulation and the pricing properties including competitive equilibrium and revenue adequacy are formulated as constraints. Third, to verify the performance of the proposed pricing scheme considering the strategic bidding, a bi-level strategic bidding problem of the generator under the proposed pricing method is established and transformed into a mixed integer linear programming problem. The numerical results indicate that under the conventional pricing methods, the consumer payments under strategic bidding can be up to 16.67 times higher than those under truthful bidding, while the proposed method can effectively reduce excessive consumer payments by 92.1% while maintaining the desired pricing properties.
引用
收藏
页数:20
相关论文
共 11 条
  • [1] Locational marginal pricing-based allocation of transmission capacity in multiple electricity markets
    Karimi Varkani, Ali
    Seifi, Hossein
    Sheikh-El-Eslami, Mohammad Kazem
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2014, 8 (05) : 983 - 994
  • [2] Optimization-Based Approach for Price Multiplicity in Network-Constrained Electricity Markets
    Alguacil, Natalia
    Arroyo, Jose M.
    Garcia-Bertrand, Raquel
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (04) : 4264 - 4273
  • [3] Optimization-Based Home Energy Management System Under Different Electricity Pricing Schemes
    Khorram, Mahsa
    Faria, Pedro
    Vale, Zita
    2018 IEEE 16TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN), 2018, : 508 - 513
  • [4] An optimization-based conjectured supply function equilibrium model for network constrained electricity markets
    Barquin, J.
    Vitoriano, B.
    Centeno, E.
    Fernandez-Menendez, F.
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2009, 60 (12) : 1719 - 1729
  • [5] A particle swarm optimization-based apporach for pricing VAR providers in the electricity market with the cosideration of voltage security
    El-Araby, E. E.
    Yorino, Naoto
    2005 INTERNATIONAL CONFERENCE ON FUTURE POWER SYSTEMS (FPS), 2005, : 723 - 728
  • [6] Solution of elliptic partial differential equations by an optimization-based domain decomposition method
    Gunzburger, MD
    Heinkenschloss, M
    Lee, HK
    APPLIED MATHEMATICS AND COMPUTATION, 2000, 113 (2-3) : 111 - 139
  • [7] Optimization of day-ahead pricing electricity markets based on a simplified methodology for stochastic utility function estimation
    Costa, Vinicius B. F.
    Bonatto, Benedito D.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2022, 143
  • [8] A Data Decomposition and End-to-End Optimization-Based Monthly Carbon Emission Intensity of Electricity Forecasting Method
    Yan, Yue
    Feng, Haoran
    Song, Jinwei
    Zhang, Shixu
    Zhang, Shize
    He, Qi
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2025, 2025 (01):
  • [9] APPLICATION OF PARTICLE SWARM OPTIMIZATION-BASED CLUSTERING METHOD TO REDUCE SMT SETUP TIME FOR INDUSTRIAL PC MANUFACTURER IN TAIWAN
    Kuo, Ren-Jieh
    Lin, Fang-Jun
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2010, 6 (08): : 3381 - 3400
  • [10] Optimizing local electricity markets: A bi-level primal-dual approach for integrating price-based demand response and distribution locational marginal pricing
    Alsaleh, Ibrahim
    Alassaf, Abdullah
    AIN SHAMS ENGINEERING JOURNAL, 2024, 15 (09)