Optimized configuration algorithm of independent scenery storage micronet based on improved fish swarm algorithm

Abstract

The invention discloses an optimized configuration algorithm of an independent scenery storage micronet based on an improved fish swarm algorithm, which utilizes particle flight velocity v and inertiaweight w to improve the foraging behavior, clustering behavior and tail collision behavior of the artificial fish swarm algorithm. The algorithm uses the particle swarm optimization algorithm to update the best fitness of the elite artificial fish swarm; in the artificial fish swarm optimization algorithm, the best fitness of the artificial fish is found, and the particle swarm optimization algorithm is used to update until the required accuracy or iteration times. In this case, the position obtained by iteration is obviously better than the initial point, but it requires multiple times of iteration to obtain the current best solution. Considering the overall efficiency, the termination condition of the improved PSO artificial fish swarm algorithm is constructed by using the precision anditeration times. The invention applies the algorithm to configure the independent wind-solar storage micro-grid, and the independent micro-grid optimized configuration is to meet the requirements ofthe lowest total operation cost and the lowest new energy power generation abandonment rate of the micro-grid by the normal operation of the micro-source and satisfying each constraint condition.

Description

technical field [0001] The invention relates to the application field of the improved fish swarm algorithm, in particular to an optimal configuration algorithm of an independent wind-solar-storage micro-grid based on the improved fish-swarm algorithm. Background technique [0002] Inspired by the social attributes and social behavior of fish swarms, Li Xiaolei proposed a kind of swarm intelligence optimization algorithm based on animal behavior-artificial fish swarm algorithm. Each artificial fish is an autonomous body of artificial life. It perceives the external environment through its own sensory behavior. Foraging, flocking, tail-stalking and random behavior are the basic social attributes and basic behaviors of fish in the evolution process of nature. [0003] At present, large-scale distributed wind power and photovoltaic power grid connection and consumption are difficult, and power curtailment is serious. Configuring energy storage with a reasonable capacity in the ...

AI Technical Summary

Problems solved by technology

At this stage, due to the high price of energy storage devices, the configuration of energy storage capacity should not be too large, which will significantly increase the investment cost; the configuration of energy storage capacity should not be too small, as too small energy storage capacity cannot guarantee the system Stable operation during the off-grid period is also not conducive to promoting the consumption of photovoltaics

[0004] In addition, the basic artificial fish swarm algorithm has a slow convergence speed in the later stage of optimization for high-dimensional extreme value functions, and the accuracy needs to be improved

When the basic artificial fish swarm algorithm is applied to the optimal configuration of the independent wind-solar-storage micro-grid, there is a problem of unreasonable configuration, and the utilization rate of distributed energy generation and the total configuration cost cannot meet the established requirements

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