基于多目标粒子群算法的双馈感应发电机波能转换系统PID控制器优化设计

A. El-Gammal
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引用次数: 7

摘要

本文介绍了基于闭环矢量控制系统的波浪能量转换系统驱动双馈感应发电机的完整建模与仿真。两个用于转子侧和定子侧变流器的脉宽调制电压源(PWM)变流器通过公共直流链路在转子终端和公用电网之间背靠背连接。闭环矢量控制系统通常由一组PID控制器控制,PID控制器对系统的动态性能有重要影响。本文利用粒子群算法和遗传算法对并网双馈感应发电机(DFIG)波浪能系统进行了多目标PID优化设计。与传统的PID控制器设计方法相比,采用粒子群算法和遗传算法对转子和电网侧变流器的控制器参数进行优化,改善了DFIG波能系统在故障状态下的暂态运行。
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Optimal Design of PID Controller for Doubly-Fed Induction Generator-Based Wave Energy Conversion System Using Multi-Objective Particle Swarm Optimization
This paper presents the complete modeling and simulation of Wave Energy Conversion System (WECS) driven doubly-fed induction generator with a closed-loop vector control system. Two Pulse Width Modulated voltage source (PWM) converters for both rotor- and stator-side converters have been connected back to back between the rotor terminals and utility grid via common dc link. The closed-loop vector control system is normally controlled by a set of PID controllers which have an important influence on the system dynamic performance. This paper presents a Multi-objective optimal PID controller design of a doubly-fed induction generator (DFIG) wave energy system connected to the electrical grid using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). PSO and GA are used to optimize the controller parameters of both the rotor and grid-side converters to improve the transient operation of the DFIG wave energy system under a fault condition as compared with the conventional methods to design PID controllers.
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