Scheduling graph optimizing method based on multi-target genetic algorithm

Abstract

The invention relates to a scheduling graph optimizing method based on a multi-target genetic algorithm. The scheduling graph optimizing method comprises the steps of: scheduling graph simulation model, scheduling graph generalization, the realization form of the multi-target genetic algorithm NSGA-II (nondominated sorting genetic algorithm II): NSGA-II (nondominated sorting genetic algorithm II) algorithm, the generation of an initial population, and the cross heteromorphosis method. In the scheduling graph optimization, the scheduling graph optimizing method adopts the multi-target genetic algorithms, such as the NSGA-II algorithm. The NSGA-II algorithm is known as the algorithm having the best multi-target optimizing effect. The NSGA-II algorithm adopts a rapid domination-free stratified sorting and eliminating mechanism, and introduces in an elite retention strategy, so that the diversity of the results can be ensured so as to make the results widely and uniformly adjacent to the optimal leading edge of Pareto. The multi-target genetic algorithm is relatively nature and stable, which can present stronger optimizing ability no matter in the theoretical test function or the actual production problem. The multi-target genetic algorithm does not need to coordinate a plurality of targets, and moreover, the multi-target genetic algorithm can directly search the non-inferior solutions and provide a mixed coding method. The multi-target genetic algorithm has wide application and strong expandability.

Description

technical field [0001] The invention relates to a scheduling diagram optimization method based on a multi-objective genetic algorithm, is a cascade reservoir group optimization scheduling method, and relates to a cascade reservoir group scheduling diagram optimization model construction and solution method considering multi-objective optimization. Background technique [0002] The conventional dispatching map formulation method is usually to select a typical year (or a typical series) and calculate it through runoff adjustment. It can fully integrate the experience of the dispatching manager when it is used, and because of its simple, practical and easy-to-operate features, it has become the current application The broadest general scheduling method. However, the main problems of using the dispatching chart to guide the reservoir dispatching are: some unavoidable shortcomings such as not considering the forecasted inflow, the normal output area is too large, and it is diffic...

AI Technical Summary

Problems solved by technology

However, the main problems of using the dispatching chart to guide the reservoir dispatching are: some unavoidable shortcomings such as not considering the forecasted inflow, the normal output area is too large, and it is difficult to achieve the global optimum and quasi-global optimum. More scholars hope to use the new model And the optimization algorithm is improved, and then the optimal scheduling graph is proposed

Reservoir scheduling diagram optimization is a complex multi-objective optimization problem, so it is not enough to only consider single objectives such as maximum power generation or maximum water supply in scheduling diagram optimization

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