Hydropower station group optimized dispatching method based on improved quantum-behaved particle swarm algorithm

Abstract

The invention discloses a cascade hydropower station group optimized dispatching method based on an improved quantum-behaved particle swarm algorithm. The problems that local optimum happens to the quantum-behaved particle swarm algorithm at the later iteration period due to premature convergence for the reason that population diversity is decreased, and an obtained hydropower station group dispatching scheme is not the optimal scheme are mainly solved. The hydropower station group optimized dispatching method based on the improved quantum-behaved particle swarm algorithm is characterized by comprising the steps that first, power stations participating in calculation are selected, and the corresponding constraint condition of each power station is set; then, a two-dimensional real number matrix is used for encoding individuals; afterwards, a chaotic initialization population is used for improving the quality of an initial population, the fitness of each particle is calculated through a penalty function method, the individual extreme value and the global extreme value are updated, an update strategy is weighed, the optimum center location of the population is calculated, neighborhood mutation search is conducted on the global optimum individual, the positions of all the individuals in the population are updated according to a formula, and whether a stopping criterion is met or not is judged. The hydropower station group optimized dispatching method based on the improved quantum-behaved particle swarm algorithm is easy to operate, small in number of control parameters, high in convergence rate, high in computation speed, high in robustness, reasonable and effective in result, and applicable to optimized dispatching of cascade hydropower station groups and optimal allocation of water resources.

Description

technical field [0001] The invention relates to a method for optimal dispatching of hydropower station groups based on an improved quantum particle swarm algorithm, which is a method for optimal dispatching of water resources and belongs to the technical field of optimal dispatching of water resources and hydropower station groups. technical background [0002] The last decade or so has been a period of rapid development of my country's hydropower construction. Especially with the successive commissioning of super-large hydropower bases in southwest China represented by the Wujiang River and the Hongshui River, my country has formed the world's largest hydropower system. With the emergence of cascade hydropower station groups in super-large river basins, further research on the scientific and efficient joint optimal dispatching method of hydropower station groups has particularly important theoretical and practical significance. [0003] The optimal dispatching of hydropower...

AI Technical Summary

Problems solved by technology

In the process of application, it is found that QPSO takes the same weight for each particle when calculating the optimal position center of the population, and does not consider the fitness difference of each particle's historical optimal position, so it is difficult to give full play to the advantages of elite particles. Premature convergence occurs, falling into local optimum, and the obtained hydropower station group scheduling scheme is not the optimal scheme

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