Locational Pricing of Uncertainty Based on Robust Optimization

被引:9
|
作者
Fang, Xichen [1 ]
Du, Ershun [1 ]
Zheng, Kedi [1 ]
Yang, Jiajia [2 ]
Chen, Qixin [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
[2] UNSW, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
来源
基金
中国国家自然科学基金;
关键词
Electricity market; locational marginal price (LMP); mechanism design; robust optimization; uncertainty pricing; JOINT ENERGY; ELECTRICITY; DESIGN; RESERVES; STRATEGY; MARKETS;
D O I
10.17775/CSEEJPES.2020.03210
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
With the increasing penetration of renewables, power systems have to operate with greater flexibility to address the uncertainties of renewable output. This paper develops an uncertainty locational marginal price (ULMP) mechanism to price these uncertainties. They are denoted as box deviation intervals as suggested by the market participants. The ULMP model solves a robust optimal power flow (OPF) problem to clear market bids, aiming to minimize the system cost as a prerequisite that the reserve margin can address all the relevant uncertainties. The ULMP can be obtained as a by-product of the optimization problem from the Lagrange multipliers. Under the ULMP mechanism, renewables and consumers with uncertainty will make extra payments, and the thermals and financial transmission right (FTR) holders will be compensated. It is further shown that the proposed mechanism has preferable properties, such as social efficiency, budget balance and individual rationality. Numerical tests are conducted on the modified IEEE 5-bus and 118-bus systems to demonstrate the merits and applicability of the proposed mechanism.
引用
收藏
页码:1345 / 1356
页数:12
相关论文
共 50 条
  • [31] Locational Marginal Pricing: A Fundamental Reconsideration
    Tesfatsion, Leigh
    IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY, 2024, 11 : 104 - 116
  • [32] On The Decomposition of Locational Marginal Hydrogen Pricing
    An, Qi
    Li, Gengyin
    Wang, Jianxiao
    Song, Yiyang
    Wang, Xuanyuan
    Liu, Zhen
    He, Guannan
    2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM, 2023,
  • [33] Locational Load Shedding Marginal Pricing
    Tikdari, A. G.
    Rashidi-Nejad, M.
    Bevrani, H.
    Montazeri, M.
    2015 23RD IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE), 2015, : 1522 - 1526
  • [34] Conformal Uncertainty Sets for Robust Optimization
    Johnstone, Chancellor
    Cox, Bruce
    CONFORMAL AND PROBABILISTIC PREDICTION AND APPLICATIONS, VOL 152, 2021, 152 : 72 - 90
  • [35] Uncertainty Quantification and Robust Optimization in Engineering
    Kumar, D.
    Alam, S. B.
    Vucinic, Dean
    Lacor, C.
    ADVANCES IN VISUALIZATION AND OPTIMIZATION TECHNIQUES FOR MULTIDISCIPLINARY RESEARCH: TRENDS IN MODELLING AND SIMULATIONS FOR ENGINEERING APPLICATIONS, 2020, : 63 - 93
  • [36] Robust combinatorial optimization with knapsack uncertainty
    Poss, Michael
    DISCRETE OPTIMIZATION, 2018, 27 : 88 - 102
  • [37] Deregulated model and locational marginal pricing
    Sood, Yog Raj
    Padhy, N. P.
    Gupta, H. O.
    ELECTRIC POWER SYSTEMS RESEARCH, 2007, 77 (5-6) : 574 - 582
  • [38] Continuous locational marginal pricing (CLMP)
    Li, Fangxing
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (04) : 1638 - 1646
  • [39] A robust-based fatigue optimization method for systems subject to uncertainty
    U. L. Rosa
    A. M. G. de Lima
    L. K. S. Gonçalves
    M. H. Belonsi
    Journal of Mechanical Science and Technology, 2022, 36 : 4571 - 4581
  • [40] Integration of possibility-based optimization and robust design for epistemic uncertainty
    Youn, Byeng D.
    Choi, Kyung K.
    Du, Liu
    Gorsich, David
    JOURNAL OF MECHANICAL DESIGN, 2007, 129 (08) : 876 - 882