Multi-Objective, Short-Term Hydrothermal Scheduling Based on Weighting Method Using Particle Swarm Optimization

Abstract

This paper describes an algorithm to solve multi-objective, short term hydrothermal scheduling problem incorporating a few new techniques to make it more simple and fast. Multi-objective hydrothermal scheduling problem allocates the system generation among the available hydro and thermal generators such that an overall satisfactory solution to the problem of optimizing the objectives viz. cost of generation, emission of NOx, emission of CO2 and emission of SO2 is obtained. There are several methods to solve this problem but ‘Weighting method’ stands out of all. In weighting method, a composite objective function, combining all the given objectives, is formed assigning a suitable weight to each objective provided that the sum of the weights is equal to one. Normal practice is to assume a set of weight vectors, solve the problem considering each weight vector and go for the best overall satisfactory solution. In the method described in this paper,a set of weight vectors are randomly generated and the problem is solved for each weight vector. Further the weight vectors are modified and the problem is solved for each modified weight vector. This process is continued till the index of satisfaction is the highest. Modification of the weight vectors is done incorporating a new technique called ‘search space reduction technique’and introducing fuzzy acceleration factors. With modification of weight vectors using PSO highly efficient weight vectors/best possible solution to the hydrothermal scheduling problem can be obtained in minimum number of trials. The algorithm developed is tested on different systems and satisfactory solutions are obtained. The algorithm is simple and fast and gives a set of solutions with index of satisfaction falling in a narrow range for the multi-objective, short term hydrothermal scheduling problem.