A PARALLEL GENETIC ALGORITHM FOR GENERATION EXPANSION PLANNING

This paper presents an application of parallel genetic algorithm to op timal long-range generation expansion planning. The problem is formula ted as a combinatorial optimization problem that determines the number of newly introduced generation units of each technology during differ ent time intervals. A new string representation method for the problem is presented. Binary and decimal coding for the string representation method are compared. The method is implemented on transputers, one of the practical multi-processors. The effectiveness of the proposed met hod is demonstrated on a typical generation expansion problem with fou r technologies, five intervals, and a various number of generation uni ts. It is compared favorably with dynamic programming and conventional genetic algorithm. The results reveal the speed and effectiveness of the proposed method for solving this problem.