Title :
Congestion management in nodal pricing with genetic algorithm
Author :
Nabavi, S.M.H. ; Jadid, S. ; Masoum, Mohammad A. S. ; Kazemi, A.
Author_Institution :
Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran
Abstract :
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 are presented and compared for 3-bus and 5-bus test systems.
Keywords :
genetic algorithms; power markets; pricing; Power World Simulator software; congestion management; deregulated market; genetic algorithm; locational marginal price; nodal pricing method; optimal generation level; Costs; Electricity supply industry deregulation; Energy management; Genetic algorithms; Optimization methods; Power system management; Power system modeling; Power system simulation; Pricing; System testing; Congestion management; Genetic Algorithm and optimal bidding strategy; deregulated power systems; nodal pricing;
Conference_Titel :
Power Electronics, Drives and Energy Systems, 2006. PEDES '06. International Conference on
Conference_Location :
New Delhi
Print_ISBN :
0-7803-9771-1
DOI :
10.1109/PEDES.2006.344301
