Hybrid self-adaptive hydropower station group intelligent optimization scheduling method and system

Abstract

The invention relates to a hybrid self-adaptive hydropower station group intelligent optimization scheduling method and system. The method comprises the following steps: determining a scheduling objective function according to a scheduling task of a hydropower station group; determining a scheduling constraint condition, and processing the scheduling constraint condition according to types; carrying out population initialization by adopting improved Tent chaotic mapping; calculating particle fitness, an individual optimal solution and a global optimal solution based on a particle swarm algorithm; calculating particle energy and a threshold thereof, and particle similarity and a threshold thereof; introducing a search strategy, searching a particle neighborhood, and updating an original solution; and updating the positions and speeds of the particles until a termination condition is reached. According to the method, Tent chaotic mapping is adopted to generate an initial population; particle energy and a threshold value thereof are introduced, particle similarity and a threshold value thereof are introduced to improve population evolution quality, continuous adaptive adjustment can be carried out along with iteration, good local refinement capability is achieved in the later period, premature is inhibited, and the defects that previous premature convergence occurs, and a solved solution is a local optimal solution instead of a global optimal solution are overcome.

Description

technical field [0001] The invention relates to the field of water conservancy engineering, in particular to a hybrid adaptive intelligent optimal scheduling method and system for a hydropower station group. Background technique [0002] Among many other clean renewable energy and new energy sources, hydropower development is relatively early, the technology is relatively mature, and it has the advantage of a high degree of development. The main content of the optimal scheduling of hydropower systems is to maximize the system benefits, using modern computer technology to obtain the optimal scheduling method to ensure the safe and economical operation of complex water conservancy and hydropower systems. [0003] With the development of society and economy, the optimal dispatch of hydropower station groups has ushered in new challenges. On the one hand, with the advancement of the development process and the growth of development demands, the hydropower system presents a deve...

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Problems solved by technology

[0005] However, at the same time, some studies have proved that the existing conventional intelligent algorithms (such as particle swarm algorithm, genetic algorithm, simulated annealing algorithm, etc.) have defects such as premature convergence, and the obtained solution is a local optimal solution rather than a global optimal solution. Good traversal uniformity and convergence speed, resulting in poor optimization accuracy and speed

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