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ABSTRACT: This paper presents a coevolutionary approach to analyzing supply function equilibrium (SFE) models of an oligopolistic electricity market. Both the affine supply function model and the piece-wise affine supply function model are considered. Different parametrization cases of the affine supply function model are analyzed. The piece-wise affine supply functions that have a large number of pieces are used to numerically estimate the equilibrium supply functions of any shapes. Simulation cases of the piece-wise affine supply function model with different peak loads, nonquadratic and nonconvex costs, and different demand elasticities are studied. An example based on the cost data from the real-world electricity industry is used to validate the approach presented in this paper. Simulation results show that the coevolutionary approach rapidly converges to SFE in the affine supply function model simulation and robustly converges to SFE in all cases of the piece-wise affine supply function model simulation. The approach is robust and flexible and has the potential to be used to solve the complicated equilibrium problems in real-world electricity markets
IEEE Transactions on Power Systems 09/2006; · 2.68 Impact Factor
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ABSTRACT: This paper presents a new unified framework of electricity market analysis based on coevolutionary computation (CCEM) for both the one-shot and the repeated games of oligopolistic electricity markets. The standard Cournot model and the new Pareto improvement model are used. The linear and constant elasticity demand functions are considered. Case study shows that CCEM is highly efficient and can handle the nonlinear market models that are difficult to be handled by conventional methods. The framework presented in this paper can help to overcome the difficulties of demand function specification encountered by the Cournot models. CCEM is found to be an effective and powerful approach for electricity market analysis.
IEEE Transactions on Power Systems 03/2006; · 2.68 Impact Factor
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ABSTRACT: This paper develops a parallel evolutionary programming based optimal power flow solution algorithm. The proposed approach is less sensitive to the choice of starting points and types of generator cost curves. To improve the robustness and speed of convergence of the algorithm, population and gradient acceleration techniques are incorporated. The developed algorithm is implemented on a thirty-six-processor Beowulf cluster. The proposed approach has been tested on the IEEE 118-bus system under master-slave, dual-direction ring and 2D-mesh topologies. Computational speedup and generation costs for each parallel topology with different number of processors are then compared to those of the sequential EP approach.
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on; 09/2004
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ABSTRACT: This paper proposes a parallel evolutionary programming (EP) approach for solving the optimal power flow (OPF) problem. The parallel EP-OPF approach is less sensitive to the choice of starting points and types of generator cost curves. The developed algorithm is implemented on a Beowulf cluster with 31 Intel Pentium IV 2.66 GHz processors, which are arranged in master-slave structure. The proposed approach has been tested on the IEEE 30- and 118-bus systems. Computational speedup and performance of the master-slave topology is then compared to those of the sequential EP approach.
Electric Utility Deregulation, Restructuring and Power Technologies, 2004. (DRPT 2004). Proceedings of the 2004 IEEE International Conference on; 05/2004
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ABSTRACT: A solution method, for competitive power markets formulated as a Cournot game, that allows equilibrium to be determined without an explicit model of aggregated demand is presented. The method determines market equilibrium for all feasible demand conditions and thus provides a perspective on the market, independent of representative demand function, that reveals the inherent tendencies of producers in the market. Numerical solutions are determined by use of the new controlled genetic algorithm and constraint handling techniques. The solutions give production and demand elasticity distributions of the market at any feasible equilibrium price and volume. The solution distributions evaluated for the market with unspecified demand functions, were found to be consistent with previous results obtained from markets with specific demand functions. The ability of the new approach to find all, and arbitrary, solutions allows specific markets to be examined, as well as very general observations to be made. Generally it was observed that: no inherent price constraint exists; price is more volatile for low volumes and high prices; market dominance and power are unaffected by price; and inelastic demand can give rise to equilibrium with lower price than responsive demand.
IEE Proceedings - Generation Transmission and Distribution 10/2003; · 0.48 Impact Factor
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IEE Proceedings - Generation Transmission and Distribution 02/2003; 150(1):128- 128. · 0.48 Impact Factor
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ABSTRACT: This paper presents a new solution method for the Cournot game
equilibrium analysis. The new method allows arbitrary differentiable
cost and demand characteristics to be implemented. The solution does not
rely on conjectures about market participants' behaviour. The approach
taken transforms the search for the Cournot game equilibrium to a
problem of under-constrained, multivariate nonlinear optimisation.
Genetic algorithm techniques were adapted to numerically solve the
optimisation for various power markets. Single-consumer power markets
are examined and discussed. A new exponential-integral demand function
capable of realistically modelling volume-specific inelastic demand is
presented. Methods of applying the new approach to assess current market
operations and future restructuring options are presented
IEE Proceedings - Generation Transmission and Distribution 04/2002; · 0.48 Impact Factor
