Research On Thermal Power Units Load Optimal Distribution Based On Genetic Algorithm

Load optimal distribution is a hot research issue all along in power system. On the premise of giving the unit commitment and all constraint conditions, load optimal distribution studies how to dispatch load to operating sets to makes the total operating fees lowest in power station. This paper has deeply studied optimal modes and optimal algorithms on load optimal distribution.At first, the paper analyzes the economic indexes which are generally adopted in power station, and defines standard coal consumption as the optimal objective. The shortage of simple genetic algorithm solving economic load dispatch is researched. On the basis of the simple genetic algorithm, some improved solutions are proposed, which include increasing boundary constraint to initial population, ranking selection operator, adaptive crossover operator and optimization preservation strategy. The improved genetic algorithm is applied to three generating units, and the results shown that the improved genetic algorithm has better optimization effect.Next, a real code genetic-tabu search hybrid algorithm is presented. Genetic algorithm is characterized by the capability of global searching, and tabu search is characterized by the capability of mountain climbing, so the advantages of two algorithms complement each other and the hybrid algorithm can avoid pre-maturity after combination. In order to fully utilize tabu search’s local search ability, and also avoid using tabu search too much bringing about time complexity increasing, this paper proposes the key to combination of the two algorithms is breaking local optimum by tabu search when the genetic algorithm tends to prematurity. A simple and reliable method is advanced to estimate. prematurity, which compare the population change by sample variance. A new method is put forward to produce the neighborhood solution of tabu search. The effect of optimization is compared by case analysis, and the results demonstrate the effectiveness and viability of the algorithm.Then, load optimal dispatch is a single objective optimization question with constraints. The question is turned into a multi-objective optimization question in this paper. One objective is the total coal consumption function, and the other is the constraint violation degree function, so that the two-objective mathematic mode is built. Some improved measures are proposed in evaluation strategy, genetic operators, etc. The evaluation function is the individual pareto strength, and the population evolution depends on genetic algorithm. This algorithm provides a new and effective method to load economic dispatch. Finally through the simulation the performance of simple genetic algorithm, improved genetic algorithm, hybrid genetic and tabu search algorithm are compared and analyzed.