Congestion Management using Genetic Algorithm in Deregulated Power Environments

Congestion cost allocation is an important issue in congestion management. This paper presents a genetic algorithm (GA) to determine the optimal generation levels in a deregulated market. The main issue is congestion in lines, which limits transfer capability of a system with available generation capacity. Nodal pricing method is used to determine locational marginal price (LMP) of each generator at each bus. Simulation results based on the proposed GA and the Power World Simulator software is presented and compared for the IEEE 30-bus test system.

[1]  N. S. Rau,et al.  Transmission loss and congestion cost allocation-an approach based on responsibility , 2000 .

[2]  A. David,et al.  Transmission congestion management in an electricity market , 1999 .

[3]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[4]  Enrico Carpaneto,et al.  The role of load demand elasticity in congestion management and pricing , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[5]  J.M. Ramirez,et al.  Alleviating congestion of an actual power system by genetic algorithms , 2004, IEEE Power Engineering Society General Meeting, 2004..

[6]  J. H. Malinowski,et al.  Evaluation of Transmission Network Capacity Use for Wheeling Transactions , 1989, IEEE Power Engineering Review.

[7]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[8]  I. Pérez-Arriaga,et al.  Marginal pricing of transmission services: an analysis of cost recovery , 1995 .

[9]  J. Frame.  Locational marginal pricing , 2001, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[10]  S. Plumel,et al.  Genetic algorithm associated to game theory in congestion management , 2005, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[11]  Zuyi Li,et al.  Market Operations in Electric Power Systems : Forecasting, Scheduling, and Risk Management , 2002 .

[12]  F. Ashcroft,et al.  VIII. References , 1955 .

[13]  A. Papalexopoulos,et al.  Transmission congestion management in competitive electricity markets , 1998 .

[14]  John Haffner.  Market Power Mitigation in Electricity Markets: A Framework for Making Choices , 2005 .

[15]  T. W. Gedra,et al.  On transmission congestion and pricing , 1999 .

[16]  Anastasios G. Bakirtzis,et al.  Aumann-Shapley transmission congestion pricing , 2001 .

[17]  Yixin Ni,et al.  Optimal bidding strategies for generation companies in electricity markets with transmission capacity constraints taken into account , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[18]  Y. H. Song,et al.  Apply Lagrangian relaxation to multi-zone congestion management , 2001, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[19]  S. M. Shahidehpour,et al.  Fixed transmission rights for zonal congestion management , 1999 .

[20]  Y. H. Song,et al.  Primal-dual interior point linear programming optimal power flow for real-time congestion management , 2000, 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077).

[21]  Timothy D. Mount,et al.  A uniform price auction with locational price adjustments for competitive electricity markets , 1999 .

[22]  H. Rudnick,et al.  Marginal pricing and supplement cost allocation in transmission open access , 1995 .

[23]  Mesut Baran,et al.  A transaction assessment method for allocation of transmission services , 1999 .

[24]  A. Vojdani,et al.  Transmission dispatch and congestion management in the emerging energy market structures , 1998 .