Abstract

This paper focusses on the design of optimal control strategies for a variable-speed wind energy system based on Permanent Magnet Synchronous Generator (PMSG). The fractional order PI controller, denoted PIλ, is an extension of the classical PI controller, which provides greater flexibility, better performance and robustness, however the tuning of the controller parameters is challenging. In this work, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) provide approximate solutions to various problems and form a good optimization. In our system, they are used to have the PI regulator parameters and tune the parameters of the proposed controllers. The proposed controllers have been applied as maximum power point (MPPT) controllers for the wind turbine and to regulate the PMGS currents under variable weather conditions and. The results show that, among all these controllers, the fractional order PI controller optimized by the PSO leads to better performance in terms of the transient response characteristics such overshoot, rise time and settling time.

Highlights

  • In recent years, the world is experiencing a shift towards the adoption of alternative, cheaper and cleaner energy sources [1]

  • -Despite the simplicity and ease of use of the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) algorithms it presents a risk of divergence or rapid convergence which allows to stagnate in a local optimum, several improvements have been made to the base algorithm

  • For the fractional PI and PIλ tuning based on PSO and GA, the Integral of Time Absolute Error (ITAE) performance index produced the best result over the other indices and it will be used as an objective function

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Summary

INTRODUCTION

The world is experiencing a shift towards the adoption of alternative, cheaper and cleaner energy sources [1]. ProportionalIntegral (PI) controllers are simple to implement and can achieve a good transient and steady state response with small overshoot and short settling-time and have been widely used in industrial processes [10, 11]. These classical controllers may not be very effective for systems exhibiting nonlinearities and parameter variations.

Wind turbine model
FRACTIONAL PI CONTROLLER
OPTIMIZATION OF PI AND FOPI PARAMETERS USING PSO AND GA ALGORITHMS
Overview of heuristic optimization
Performance indices
SIMULATION RESULTS AND DISCUSSION
CONCLUSION
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