Novel Hybrid Evolutionary Game Theory and Differential Evolution Solution to Generator Bidding Strategies with Unit Commitment Constraints in Energy and Ancillary Service Markets

B.Durga Hari Kiran, Sailaja Kumari Matam


This paper proposes a solution to generator bidding strategy using a novel hybrid Evolutionary Game Theory (EGT) and Differential Evolution (DE) method. In restructured power system, the generating companies (GENCOs) have an opportunity to compete in energy and ancillary services markets and earn profits. This competition creates a complicated situation to System Operator (SO) in the market clearing process. This paper attempts to maximize GENCOs profit with incomplete information by adopting optimal bidding strategies in energy and ancillary service markets while considering unit commitment constraints. Supply Function Equilibrium (SFE) model is employed to compute GENCOs profit. Nash Equilibrium points were calculated in the first stage by using Evolutionary Game Theory and then optimal bidding strategies were found with the help of Differential Evolution method. Evolutionary Game Theory is best suited for GENCOs bidding strategies but leads to slow convergence due to a large number of variables. So, a novel hybrid method involving Evolutionary Game Theory with Differential Evolution is proposed in this paper. The proposed method to solve bidding strategies is employed on WSCC 9 and New England 39 bus test systems to demonstrate its merits.

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Bidding, Non-cooperative, Game theory, evolutionary programming, unit commitment, supply function equilibrium, Nash equilibrium

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Tao Li, and Mohammad Shahidehpour, “Strategic Bidding of Transmission-Constrained GENCOs with Incomplete Information,” IEEE Transactions On Power Systems, vol. 20, no. 1, pp. 437-447, Feb. 2005.

B. Bahmani-Firouzi, S. Sharifinia, R. Azizipanah-Abarghooee and T. Niknam, "Scenario-Based Optimal Bidding Strategies of GENCOs in the Incomplete Information Electricity Market Using a New Improved Prey—Predator Optimization Algorithm," in IEEE Systems Journal, vol. 9, no. 4, pp. 1485-1495, Dec. 2015.

Taher Niknam, Sajjad Sharifinia, Rasoul Azizipanah-Abarghooee, “A new enhanced bat-inspired algorithm for finding linear supply function equilibrium of GENCOs in the competitive electricity market,” Energy Conversion and Management, Volume 76, December 2013, Pages 1015-1028

H. Mohsenian-Rad, "Optimal Bidding, Scheduling, and Deployment of Battery Systems in California Day-Ahead Energy Market," in IEEE Transactions on Power Systems, vol. 31, no. 1, pp. 442-453, Jan. 2016.

P. K. Singhal, R. Naresh and V. Sharma, "Binary fish swarm algorithm for profit-based unit commitment problem in competitive electricity market with ramp rate constraints," in IET Generation, Transmission & Distribution, vol. 9, no. 13, pp. 1697-1707, Jan. 2015.

S. J. Kazempour, A. J. Conejo and C. Ruiz, "Strategic Bidding for a Large Consumer," in IEEE Transactions on Power Systems, vol. 30, no. 2, pp. 848-856, March 2015.

S. Soleymani, “Optimum Strategy of Gencos in Energy and Reactive Power Markets, Simultaneously,” Arabian Journal for Science and Engineering, Springer, vol 39, no. 2, pp 1079-1088, Feb 2014.

A Badri, M Rashidinejad “Generation Companies' Security-Constrained Optimal Bidding Strategy in Day-Ahead Pool-Bilateral Power Markets: A Cournot-Based Model,” Australian Journal of Electrical and Electronics Engineering, Taylor & Francis, Vol. 12,Iss. 1, pp. 60-72, Jan 2015.

Feng Gao, Gerald B. Sheble, Kory W. Hedman, Chien-Ning Yu, Optimal bidding strategy for GENCOs based on parametric linear programming considering incomplete information, International Journal of Electrical Power & Energy Systems, Volume 66, pp. 272-279, March 2015.

Noble, C., “Experience with bidding ancillary services in ERCOT: A modeler's perspective,” Power Systems Conference and Exposition, 200, PSCE '09, IEEE/PES, pp.1-2, 15-18 March 2009.

B. Durga Hari Kiran, M. Sailaja Kumari, “Demand response and pumped hydro storage scheduling for balancing wind power uncertainties: A probabilistic unit commitment approach,” International Journal of Electrical Power & Energy Systems, vol 81, pp. 114-122, October 2016.

Saeid Saboori, Rasool Kazemzadeh, and Hedayat Saboori, “Assessing Wind Energy Uncertainty Impact on Joint Energy and Reserve Markets by using Stochastic Programming Evaluation Metrics,” Internatıonal Journal Of Renewable Energy Research, Vol. 5, No. 4, pp. 1241-1251,2015.

Slimane Souag, and Farid Benhamida, “A Dynamic Power System Economic Dispatch Enhancement by Wind Integration Considering Ramping Constraint -Application to Algerian Power System,” Internatıonal Journal Of Renewable Energy Research, Vol. 5, No. 3, pp. 794-805, 2015.

Mohammad E. Khodayar, and Mohammad Shahidehpour, “Security-Constrained Unit Commitment for Simultaneous Clearing of Energy and Ancillary Services Markets,” IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1079-1088, May 2005.

Chuan-Ping Cheng, Chih-Wen Liu, and Chun-Chang Liu, “Unit Commitment by Lagrangian Relaxation and Genetic Algorithms,” IEEE Transactions on Power Systems, Vol. 15, No. 2, pp. 707-714,May 2000.

Hobbs, B.F., "Linear complementarity models of Nash-Cournot competition in bilateral and POOLCO power markets," IEEE Transactions on Power Systems, vol.16, no.2, pp.194-202, May 2001.

de la Torre S, Contreras, J. Conejo, A.J., "Finding multiperiod Nash equilibria in pool-based electricity markets," IEEE Transactions on Power Systems, vol.19, no.1, pp.643-651, Feb. 2004.

Contreras, J., Klusch, M. Krawczyk, J.B., "Numerical solutions to Nash-Cournot equilibria in coupled constraint electricity markets," , IEEE Transactions on Power Systems, vol.19, no.1, pp.195-206, Feb. 2004.

Pozo, D, Contreras, J., "Finding Multiple Nash Equilibria in Pool-Based Markets: A Stochastic EPEC Approach," IEEE Transactions on Power Systems, vol.26, no.3, pp.1744-1752, Aug. 2011.

J. Maynard Smith, G. R. Price, “The Logic of Animal Conflict,” Nature Publishing Group, Nature 246, pp. 15 – 18, November 1973.

Nurhan Karaboga,Bahadir Cetinkaya, “Performance Comparison of Genetic and Differential Evolution Algorithms for Digital FIR Filter Design,” Third International Conference, ADVIS 2004, Izmir, Turkey, Proceedings, pp 482-488, October 2004

David Easley and Jon Kleinberg, “Networks, Crowds, and Markets: Reasoning about a Highly Connected World,” Cambridge University Press, 2010.



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