Application of parallel genetic algorithms to generation expansion planning using parallel processors

This paper presents an application of parallel genetic algorithms to optimal long-range generation expansion planning. The problem can be formulated as a combinatorial optimization problem that determines the order of introduced generation units at each interval of the year. The proposed method considers introduced power limits of each technology, maximum loads at each interval, and load duration curves at each interval. Appropriate string representation for the problem is presented. Binary and decimal coding and three selection methods are compared. The method is developed on a transputer that is one of the parallel processors. The feasibility of the proposed method is demonstrated using a typical expansion problem with four technologies and five intervals. The method is then compared with conventional dynamic programming and a simple genetic algorithm with promising results.