Authors : Attia A. El-Fergany and Mahdi El-Arini
Abstract: This study presents an integrating Genetic Algorithm (GA) and Pattern Search (PS) approaches to solve the Combined Emission/Economic Dispatch (CEED) problems with multi-objectives have been developed. This integration will combine the strengths of GA and PS to solve this problem. The PS performance is highly dependent on the initial/starting point. To tackle this issue, GA was utilized to initiate the starting point for PS and to validate the obtained result of PS as well. The weighted multi-objective function with penalty factor is used in this study. The proposed weighting factor plays significant part on the problem solution. The proposed methodology considers operational power constraints of generating units, value-point loading ripple effects with non-convex characteristics and line losses as well for practical applications. The proposed integrating algorithms were intensively demonstrated, tested and verified on several cases. The obtained results prove high quality and effectiveness of proposed integrated GA-PS algorithm to solve CEED problems with reduced execution time.
Attia A. El-Fergany and Mahdi El-Arini, 2012. Emission/Economic Load Dispatch Using Combination of Evolutionary Algorithms. International Journal of Soft Computing, 7: 256-263.