Optimization of Fuzzy Controller of a Wind Power Plant Based on the Swarm Intelligence

TL;DR

This paper presents a method to optimize fuzzy control rules for wind power plants using Particle Swarm Optimization, improving power output by refining the fuzzy rule base.

Contribution

It introduces a novel optimization approach for fuzzy rule bases in wind power control systems using swarm intelligence techniques.

Findings

Optimized fuzzy rule base enhances wind power plant performance.

Particle Swarm Optimization effectively adjusts fuzzy rules.

The method achieves near-optimal control in experimental setups.

Abstract

The article considers the problem of the optimal control of a wind power plant based on fuzzy control and automation of generating the fuzzy rule base. Fuzzy rules by experts do not always provide a maximum power output of the wind plant and fuzzy rule bases require an adjustment in the case of changing the parameters of the wind power plant or the environment. This research proposes the method for optimizing the fuzzy rules base compiled by various experts. The method is based on balancing weights of fuzzy rules into the base by the Particle Swarm Optimization algorithm. The experiment has shown that the proposed method allows forming the fuzzy rule base as an exemplary optimal base from a non-optimized set of fuzzy rules. The optimal fuzzy rule base has been taken under consideration for the concrete control loop of wind power plant and the concrete fuzzy model of the wind.