Autonomous group particle swarm optimisation tuned dynamic voltage restorers for improved fault‐ride‐through capability of DFIGs in wind energy conversion system. Issue 4 (1st December 2020)

• Record Type: Journal Article
• Authors: Swain, Snehaprava; Ray, Pravat Kumar
• Is Part Of: IET energy systems integration. Volume 2:Issue 4(2020)
• Page Start: 305
• Page End: 315
• Publication Date: 2020-12-01
• Subjects: power grids -- wind power plants -- asynchronous generators -- particle swarm optimisation -- power convertors -- harmonic distortion -- power supply quality -- PI control -- rotors -- power generation faults -- wind turbines -- stators -- power generation control -- electric current control -- power system restoration -- voltage control -- control system synthesis -- machine protection -- power generation protection -- search problems -- power generation reliability -- compensation; optimised controller -- enhanced FRT capability -- improved fault‐ride‐through capability -- wind energy conversion system -- multiobjective tuning algorithm -- grid‐connected doubly‐fed induction generators -- DFIG stator -- grid faults -- multiple proportional–integral controllers -- DVR control circuit -- optimised PI controllers -- autonomous group particle swarm optimisation tuned dynamic voltage restorers -- voltage‐current controllers -- fault‐ride‐through capability -- FRT capability -- point of common coupling -- ride‐through capability -- wind energy conversion systems -- ptimisation algorithm‐based PI controllers -- randomised search -- power quality -- system reliability -- voltage sag compensation -- total harmonic distortion -- Matlab -- power 1.5 MW; Power resources -- Periodicals; Energy conservation -- Periodicals; Power resources; Energy conservation; Periodicals; 333.79
• DOI: 10.1049/iet-esi.2020.0004
• Languages: English
• ISSNs: 2516-8401

Abstract

Abstract : In this paper, a multi‐objective tuning algorithm is proposed for the voltage/current controllers of the dynamic voltage restorer (DVR) in an optimal manner in order to improve the fault‐ride‐through (FRT) capability of the grid‐connected doubly‐fed induction generators. An active crowbar protection (ACB_P) coupled with the rotor of the DFIG, provides a very little compensation, on blocking the high rotor current during fault condition. Control of DVR is achieved through use of multiple PI controllers. This paper presents a novel multi‐objective tuning known as Autonomous Group Particle Swarm Optimisation (AGPSO) to optimally tune the PI controllers. The optimisation algorithm uses diverse autonomous groups confined within a common target to achieve more directed and randomised search results for any population. Voltage sag compensation, total harmonic distortion (THD), RMS value of signal are the three major indices for comparison study during fault. Finally, the performance improvement in FRT of the DFIG with optimised controller was studied through DFIG responses on comparing with normal controller. Efficacy of the proposed controller proposed is verified by a simulation model of DFIG System with 1.5 MW rating in MATLAB. The results are analysed and comparative data are placed to ensure the enhanced FRT capability of the system.