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摘要
This study presents a new approach for solving profit-based unit commitment (PBUC) problem in a day-ahead competitive electricity market. The new approach benefits from deterministic mathematical procedures and the uncertainty and probabilistic behavior inherently associated with evolutionary methodologies such as genetic algorithm and particle swarm optimization are avoided and, as a result, the optimum solution found are same in each simulation run. To solve the PBUC problem, a fitness FT) is defined and the optimum power of each generating unit that maximizes the FT is determined (FF*). Among all generating units, the least-cost option for generating power at each hour is determined and Then, generating unit priority is specified based on FF*s. Finally, by considering hourly power price, non-profitable generating units are switched OFF, final results of PBUC are determined, and total profit is calculated. The proposed approach is applied to a 10-unit power system and in addition to a very short processing time, it is found that proposed approach results in 3.21% higher profit as compared with the Tabu search method To verify the efficiency of proposed approach in large-scale PBUC problem, the simulations included test runs for 20, 40, 60, 80 and 100 unit systems and the results are presented.
- 出版日期2010-6
