Multi-objective, short-term hydro thermal scheduling based on two novel search techniques

摘要

This paper presents two novel algorithms for multi-objective, short-term hydrothermal scheduling. The former, a hybrid algorithm, is the offspring of union between genetic algorithm and traditional Newton-Raphson method and the latter involves mainly heuristic searches with genetic algorithm. In the hybrid algorithm, a population of weight vectors is genetically generated, for each weight vector the objective function values are computed for the optimization interval by N-R method and the overall satisfaction/fitness of the solution is found using fuzzy techniques. The population of weight vectors is modified and fitness values are computed for members of the modified population. The cycle continues till the highest fitness value obtained, attains near saturation. The major steps in both the algorithm are the same, but in heuristic search algorithm the objective function values for the optimization interval are computed by a sub-process which employs GA and Fuzzy logic. Special crossover techniques are used in all genetic searches to improve the efficiency of the algorithm. Another special feature of this paper is the introduction of coal-constrained thermal plants.