Optimal dispatch using improved ℷ-based genetic algorithm suitable for utility systems

The objective of this paper is to evolve simple and effective methods for the optimal dispatch problem in thermal units, which are capable of obtaining optimal power generations for a large-scale system. In an improved lambda-based genetic algorithm (GA), the encoding parameter is normalized system incremental cost lambda(nm). This approach takes network losses, ramp rate limits, and prohibited zone(s) into account because of GA's flexibility. The features of a refined genetic algorithm are also incorporated in the lambda-based GA approach. The probability of mutation and crossover is exponentially varied in each generation. Probability of limits has been fixed for mutation and crossover. The results of the lambda-based GA and improved lambda-based GA are compared. The latter is simple and effective. In the proposed improved lambda-based GA, an optimal solution is obtained neglecting losses in the first stage. The resulting solution is given to load flow, and the network transmission loss is computed from load flow in the next stage. Then using the participation factor method, the loss is distributed to the units, and a new optimal solution is obtained. Another load flow analysis is made to check for voltage and capacity limit violation. Use of the participation factors in conjunction with the improved lambda-based GA approach is suitable for a practical utility system. The algorithm is tested on an IEEE-30 bus system and a 66-bus utility system, and the results are presented.