Multi-Objective Optimization Model of Electric Power Fine Construction Based on Multi-Objective Genetic Algorithm

A multi-objective genetic algorithm is proposed to solve the problem of accurate power generation based on multi-objective genetic algorithm. The mathematical model of load distribution is analyzed, and the single objective optimization problem with constraints is transformed into two objective function optimization problems: the total coal consumption function and the degree function that violates the constraints. The algorithm uses real number coding technology, Pareto intensity value as individual evaluation index, and genetic algorithm to realize population evolution, and finally finds the optimal solution. This method is applied to a power generation system composed of 5 units and a power generation system composed of 3 units for load optimization calculation. Compared with the single-objective optimization algorithm based on penalty function, the analysis shows that this algorithm has better optimization performance on the premise of satisfying all constraints, which proves the feasibility and effectiveness of this algorithm.