Two degrees of freedom dc voltage controller of grid interfaced PV system with optimized gains. (February 2017)

• Record Type: Journal Article
• Authors: Tripathi, Ravi Nath; Hanamoto, Tsuyoshi
• Is Part Of: International journal of electrical power & energy systems. Volume 85(2017)
• Page Start: 87
• Page End: 96
• Publication Date: 2017-02
• Subjects: Iterative tuning -- dc voltage controller -- Photovoltaic (PV) -- Particle swarm optimization; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2016.08.006
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: The dc voltage control of grid connected solar PV system using PI controller (degree of freedom). The application of data-driven controller gain tuning method i.e. FRIT for dc voltage controller. PSO based implementation of FRIT to avoid local and non-complex solution. The performance comparison of dc voltage control for optimized gains of controller. The performance is compared with fuzzy logic controller. Abstract: This paper proposes the application of fictitious reference iterative tuning (FRIT) method to optimize the gains of dc voltage controller of grid connected photo-voltaic (PV) system. It may be difficult to achieve good control of dc voltage using conventional PI controller having only one-degree-of-freedom (1-DOF) due to the trade-off between overshoot (in step response) and disturbance response. In this paper, the optimal control of dc voltage is proposed with improved disturbance response by implementing 2-DOF PI controller structure. FRIT method has been programmed in MATLAB based upon the particle swarm optimization (PSO) algorithm. The fundamental idea related to FRIT method is the extraction of input and output data, reference model setting and range of controller gains. The performance of dc voltage control for the optimized 2-DOF PI controller is also compared with the fuzzy logic controller (FLC) response.