Evolutionary algorithm based control strategy for enhanced operation of multifunction grid connected converters

Issue title: Special Section: Intelligent, Smart and Scalable Cyber-Physical Systems

Guest editors: V. Vijayakumar, V. Subramaniyaswamy, Jemal Abawajy and Longzhi Yang

Article type: Research Article

Authors: Vijayakumar, K.^{a; *} | Rajesh, K.^a | Vishnuvardhanan, G.^b | Kannan, S.^c

Affiliations: [a] Department of Electrical and Electronics Engineering, Kalasalingam University, (Kalasalingam Academy of Research and Education), Anand Nagar, Krishnankoil, Virudhunagar District, Tamil Nadu, India | [b] Department of Biomedical Engineering, Kalasalingam University, (Kalasalingam Academy of Research and Education), Anand Nagar, Krishnankoil, Virudhunagar District, Tamil Nadu, India | [c] Department of Electrical and Electronics Engineering, Ramco Institute of Technology, Ayyanar Koil Road, Venganallur, Virudhunagar District, Tamil Nadu, India

Correspondence: [*] Corresponding author. K. Vijayakumar, Department of Electrical and Electronics Engineering, Kalasalingam University, (Kalasalingam Academy of Research and Education), Anand Nagar, Krishnankoil, Srivilliputur Post-626126, Virudhunagar District, Tamil Nadu, India. Tel.: +91 9600893226, 04563 – 289042; E-mail: [email protected].

Abstract:  The Distributed Generation (DG) systems are highly useful in recent days for increasing the penetration of renewable energy, in which the design of grid connected inverters is one of the demanding and challenging task. For this reason, different controller strategies are developed in the traditional works for controlling the inverters with increased efficiency. But, it has the major limitations of increased computational complexity, steady state error and reduced compensation capability. To solve these issues, this research work aims to design a new controller by implementing a novel Monkey King Evolution Algorithm (MKEA) for grid connected converters. The motive of this work is to increase the overall effectiveness of the power system by controlling the inverter without affecting its output. Also, it aims to provide a secure and convenient controller for the power converters. Here, the information that is obtained from the system which includes real power, distorted power due to load, reactive power of load, and apparent power of inverter are taken as the input. Later, the four numbers of monkeys are initialized, which evaluates the best solution based on these parameters. Sequentially, the monkey king obtains the best solutions from the monkeys, using which the most suitable and best solution for taking the decision is selected. Based on this, the reference current is generated by performing the voltage regulation, and abc to dq0 transformation processes. During simulation, the efficiency of the controller is analyzed by using the measures of phase voltage, phase current, active power, reactive power, apparent power, grid voltage, and output voltage. The Total Harmonic Distortion (THD) is effectively reduced by using the MKEA based controller design. Extensive simulation and experimental results are presented to validate the effectiveness of the proposed controller and control strategy.

Keywords: Grid connected inverters, Distributed Generation System, Monkey King Evolution Algorithm (MKEA), Photovoltaic (PV) System, controller design, reference current generation

DOI: 10.3233/JIFS-179000

Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 5, pp. 4461-4478, 2019