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.


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

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