Active distribution network dynamic topology reconstitution method based on mixed artificial intelligence

Abstract

The invention discloses an active distribution network dynamic topology reconstitution method based on mixed artificial intelligence. Multiple improved artificial intelligence methods are adopted for optimizing solving, the superiority of various algorithms can be integrated, meanwhile the various artificial intelligence methods are improved during the process of combining various optimization algorithms, furthermore the astringency of the algorithms is improved, the defects such as locally optimal solution are avoided, three object functions are integrated in the optimization process, three different optimization objects are considered, and a corresponding Pareto optimal solution set is solved out; Since measurements of indexes such as on-off operation times and power supply volume are not constant, in order to establish a unified measurement model, all the indexes are converted into loss indexes according to respective conversion relations, and finally a dynamic analytic hierarchy process is adopted for deciding solutions in the Pareto optimal solution set, so that the optimal solution representing an optimal distribution network structure is obtained.

Description

technical field [0001] In the field of power system smart grid optimization technology, it specifically relates to a dynamic topology reconfiguration method for active distribution networks based on hybrid artificial intelligence. Background technique [0002] Artificial Intelligence (Artificial Intelligence), the English abbreviation is AI. It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a manner similar to human intelligence. Research in this field includes robotics, language recognition, image recognition, natural language processing and expert systems, etc. Today, the main material basis for studying artificial intelligence and the machine that can realize the technical platform o...

AI Technical Summary

Problems solved by technology

A chaotic system is often a self-feedback system. Things that come out will go back and be transformed and come out again. Any small difference in the initial value will be amplified exponentially, so the system is inherently unpredictable in the long run.

[0005] For particle swarm optimization, due to the randomness of initializing particles, when the positions of some particles and their historical optimal solutions are close to the optimal solution of the group, these particles will be far away from the optimal solution because their previous speed and inertia factor are not zero. When the speed is getting smaller and closer to zero, the population diversity will slowly disappear, and the particles will become inert. As the iterative process progresses, other particles will soon gather near these inert particles. And stop moving, the particles appear to stagnate, which leads to the prematurity of the algorithm and affects the convergence of the algorithm

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