Title :
An Improved Genetic Algorithm for unit commitment problem with lowest cost
Author :
Jalilzadeh, S. ; Pirhayati, Y.
Author_Institution :
Electr. Eng. Dept., Zanjan Univ., Zanjan, Iran
Abstract :
In this paper an improved genetic algorithm (IGA) for unit commitment problem with lowest cost is presented. The unit commitment problem (UCP) has an important role in power systems, due to improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimization problems in power systems, because this problem has many constraints. Moreover, search space is vast. To overcome these problems, a genetic operator based on unit characteristic classification technique are proposed. From simulation results, better solutions are obtained in comparison with previously reported results.
Keywords :
cost reduction; genetic algorithms; power generation dispatch; power generation scheduling; power systems; commitment schedules; genetic operator; improved genetic algorithm; operating cost reduction; optimization problems; power systems; unit characteristic classification; unit commitment problem; Biological cells; Constraint optimization; Costs; Genetic algorithms; Job shop scheduling; Power demand; Power engineering and energy; Power generation economics; Power system simulation; Power systems; genetic; optimization; unit commitment;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357777