Robust bidding strategy for demand response aggregators in electricity market based on game theory

被引:67
作者
Abapour, Saeed [1 ]
Mohammadi-Ivatloo, Behnam [1 ,2 ]
Hagh, Mehrdad Tarafdar [1 ,3 ]
机构
[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
[2] Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam
[3] Near East Univ, Engn Fac, Mersin 10, TR-99138 Nicosia, North Cyprus, Turkey
关键词
DR aggregator; Game theory; Nash equilibrium; Robust optimization (RO) method; INCOMPLETE-INFORMATION; UNCERTAINTY;
D O I
10.1016/j.jclepro.2019.118393
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
One of the ways to manage and provide flexibility in power systems is demand response (DR). A large number of end-users as DR sources must be aggregated by an intermediate entity called DR aggregator. This paper proposes an approach based on game theory to obtain the best bidding strategy of DR aggregators in electricity market. In the presented scheme, an economic responsive load model is employed for DR approach which is based on customer benefit function and price elasticity. In this paper, the network operator receives DR services from the DR aggregator. It is considered that all bids from aggregators are assembled by a network operator which calculates the share of each aggregator in DR programs by revenue function optimization. Furthermore, the network operator offers rewards to DR aggregators to achieve this purpose. The robust optimization (RO) method is used handling price uncertainty. It is used to optimize the robustness of the decision-making strategies. A non-cooperative game is used to model the competition among DR aggregators. The Nash equilibrium idea is employed to solve this game. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:13
相关论文
共 34 条
  • [1] Modeling and prioritizing demand response programs in power markets
    Aalami, H. A.
    Moghaddam, M. Parsa
    Yousefi, G. R.
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2010, 80 (04) : 426 - 435
  • [2] Demand response modeling considering Interruptible/Curtailable loads and capacity market programs
    Aalami, H. A.
    Moghaddam, M. Parsa
    Yousefi, G. R.
    [J]. APPLIED ENERGY, 2010, 87 (01) : 243 - 250
  • [3] Game Theory Approaches for the Solution of Power System Problems: A Comprehensive Review
    Abapour, Saeed
    Nazari-Heris, Morteza
    Mohammadi-Ivatloo, Behnam
    Tarafdar Hagh, Mehrdad
    [J]. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2020, 27 (01) : 81 - 103
  • [4] [Anonymous], 2013, Spot Pricing of Electricity
  • [5] Optimal Bidding Strategy for a DER Aggregator in the Day-Ahead Market in the Presence of Demand Flexibility
    Di Somma, Marialaura
    Graditi, Giorgio
    Siano, Pierluigi
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (02) : 1509 - 1519
  • [6] A Two-Stage Robust Reactive Power Optimization Considering Uncertain Wind Power Integration in Active Distribution Networks
    Ding, Tao
    Liu, Shiyu
    Yuan, Wei
    Bie, Zhaohong
    Zeng, Bo
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2016, 7 (01) : 301 - 311
  • [7] First time real time incentive demand response program in smart grid with "i-Energy" management system with different resources
    Eissa, M. M.
    [J]. APPLIED ENERGY, 2018, 212 : 607 - 621
  • [8] Application of games with incomplete information for pricing electricity in deregulated power pools
    Ferrero, RW
    Rivera, JF
    Shahidehpour, SM
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1998, 13 (01) : 184 - 189
  • [9] Games with incomplete information played by Bayesian players, I-III part I. the basic model
    Harsanyi, John C.
    Myerson, Roger B.
    [J]. Management Science, 2004, 50 (12 SUPPL.) : 1804 - 1824
  • [10] Participation of Demand Response Aggregators in Electricity Markets: Optimal Portfolio Management
    Henriques, Rodrigo
    Wenzel, George
    Olivares, Daniel E.
    Negrete-Pincetic, Mathis
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (05) : 4861 - 4871