Optimal bidding strategy of wind power producers in pay-as-bid power markets

This paper presents a method to determine the optimal bidding strategy of the wind power producers with market power for a strategic presence in the day-ahead market with pay as bid method. Since the wind power producer is not capable of exact prediction of his power production, he has to trade the difference between the amount won in the day-ahead market and the actual production value in the balancing market. Uncertainties related to power generation is modeled by likely scenarios. However in order to model the punitive effect of trade in balancing market, the balancing market price is considered as a factor of the day-ahead market's clearing price. In the proposed model, optimal bidding strategy is formulated via a bi-level problem including the upper-level and lower-level sub-problems. The purpose of the upper-level sub-problem is to maximize the wind power producer's earning while the purpose of the lower-level sub-problem is to clear the day-ahead market. To solve both upper-level and lower-level problems, particle swarm optimization algorithm is applied. The results of three-bus test system and IEEE 24-bus RTS shows the efficiency of the proposed method.

[1]  P. K. Chattopadhyay,et al.  Biogeography-Based Optimization for Different Economic Load Dispatch Problems , 2010, IEEE Transactions on Power Systems.

[2]  Javier Contreras,et al.  Price maker self-scheduling in a pool-based electricity market: a mixed-integer LP approach , 2002 .

[3]  Federico Silvestro,et al.  INFLUENCE OF FEASIBILITY CONSTRAINS ON THE BIDDING STRATEGY SELECTION IN A DAY-AHEAD ELECTRICITY MARKET SESSION , 2009 .

[4]  Rohit Bhakar,et al.  Strategic bidding for wind power producers in electricity markets , 2014 .

[5]  Majid Nili Ahmadabadi,et al.  Model-Based and Learning-Based Decision Making in Incomplete Information Cournot Games: A State Estimation Approach , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[6]  Xiuli Qu,et al.  Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market , 2011 .

[7]  J. Catalão,et al.  A Stochastic Multi-Layer Agent-Based Model to Study Electricity Market Participants Behavior , 2015, IEEE Transactions on Power Systems.

[8]  Vahid Vahidinasab,et al.  Normal boundary intersection method for suppliers’ strategic bidding in electricity markets: An environmental/economic approach , 2010 .

[9]  Morteza Rahimiyan,et al.  Risk analysis of bidding strategies in an electricity pay as bid auction: A new theorem , 2007 .

[10]  Vinay Kumar Jadoun,et al.  Enhanced Particle Swarm Optimization for Short-Term Non-Convex Economic Scheduling of Hydrothermal Energy Systems , 2015 .

[11]  Mojtaba Shivaie,et al.  An environmental/techno-economic approach for bidding strategy in security-constrained electricity markets by a bi-level harmony search algorithm , 2015 .

[12]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[13]  Xiuchen Jiang,et al.  A supply function model for representing the strategic bidding of the producers in constrained electricity markets , 2010 .

[14]  Yao Zhang,et al.  Flexible Transmission Expansion Planning for Integrating Wind Power Based on Wind Power Distribution Characteristics , 2015 .

[15]  Lalit Chandra Saikia,et al.  Load frequency control of a hydro-thermal system under deregulated environment using biogeography-based optimised three-degree-of-freedom integral-derivative controller , 2015 .

[16]  J. Contreras,et al.  Finding multiperiod Nash equilibria in pool-based electricity markets , 2004, IEEE Transactions on Power Systems.

[17]  Ali Azadeh,et al.  An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets: Agent-based simulation , 2010 .

[18]  Yong-Beom Yoon,et al.  Vertical integration and market power: A model-based analysis of restructuring in the Korean electricity market , 2010 .

[19]  M. Hosseini-Firouz.  Optimal offering strategy considering the risk management for wind power producers in electricity market , 2013 .

[20]  H. Madsen,et al.  Pool Strategy of a Price-Maker Wind Power Producer , 2013, IEEE Transactions on Power Systems.

[21]  Mohammad Bagher Naghibi-Sistani,et al.  Application of Q-learning with temperature variation for bidding strategies in market based power systems , 2006 .

[22]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[23]  Mahmud Fotuhi-Firuzabad,et al.  Bidding strategy in pay-as-bid markets based on supplier-market interaction analysis , 2010 .

[24]  Víctor Manuel Fernandes Mendes,et al.  Self-scheduling and bidding strategies of thermal units with stochastic emission constraints , 2015 .

[25]  Víctor Manuel Fernandes Mendes,et al.  Bidding strategy of wind-thermal energy producers , 2016 .

[26]  Ashkan Rahimi-Kian,et al.  The role of market pricing mechanism under imperfect competition , 2008, Decis. Support Syst..

[27]  Gerald B. Sheblé,et al.  Electricity market equilibrium model with resource constraint and transmission congestion , 2010 .

[28]  Joao P. S. Catalao,et al.  A stochastic programming approach for the development of offering strategies for a wind power producer , 2012 .

[29]  Nam-Sung Ahn,et al.  Modeling market power in Korea's emerging power market , 2007 .

[30]  J. I. Muñoz,et al.  Optimal coordinated wind-hydro bidding strategies in day-ahead markets , 2013, IEEE Transactions on Power Systems.

[31]  Toshiyuki Sueyoshi.  An agent-based approach equipped with game theory: Strategic collaboration among learning agents during a dynamic market change in the California electricity crisis , 2010 .

[32]  Fushuan Wen,et al.  Towards the development of risk-constrained optimal bidding strategies for generation companies in electricity markets , 2005 .

[33]  Damien Ernst,et al.  A comparison of Nash equilibria analysis and agent-based modelling for power markets , 2006 .

[34]  J. B. Cruz,et al.  Bidding strategies in oligopolistic dynamic electricity double-sided auctions , 2005, IEEE Transactions on Power Systems.

[35]  Stanley S. Reynolds,et al.  Supply function equilibria with capacity constraints and pivotal suppliers , 2011 .

[36]  Sayyad Nojavan,et al.  A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market , 2015 .

[37]  Jenny Lieu,et al.  Design of the incentive mechanism in electricity auction market based on the signaling game theory , 2010 .

[38]  A. Conejo,et al.  Strategic Offering for a Wind Power Producer , 2013, IEEE Transactions on Power Systems.

[39]  Xiaodai Dong,et al.  Modeling the bids of wind power producers in the day-ahead market with stochastic market clearing , 2016 .

[40]  Dong-Joo Kang,et al.  Supplier bidding strategy based on non-cooperative game theory concepts in single auction power pools , 2007 .

[41]  A. Bakirtzis,et al.  Bidding strategies for electricity producers in a competitive electricity marketplace , 2004, IEEE Transactions on Power Systems.