Regulation of Load Frequency for a Hybrid Wind-Ocean Wave Energy-Based Microgrid via Advanced Fuzzy Logic-Based Control Approach

Abstract

In this article, a model of wind and ocean wave power generation-based microgrid (MG) system with diesel engine generator and battery storage system is developed. To replicate the more practical scenarios, various system non-linearities, as well as measurement time delay, are also incorporated in the designing of the considered MG system. The stochastic nature of wind and ocean, and load demands create an imbalance among sources and loads, which may lead to severe frequency fluctuation. To mitigate the effect of frequency fluctuations, an advanced fuzzy logic (FL)-based control method is proposed for load frequency regulation (LFR). The various variants of FL-based control schemes, such as fuzzy P, fuzzy P + I, fuzzy PI, cascaded fuzzy PI-PD, and fuzzy PID controllers, are designed and implemented for the LFR of the considered hybrid MG system (HMGS). A comparative analysis of HMGS with all designed and implemented controllers is performed for the identification of the suitable controller to alleviate the effect of frequency fluctuations. The obtained results show the effectiveness of the cascaded fuzzy PI-PD controller over the other designed controllers. Finally, the stability analysis of HMGS with proposed cascaded fuzzy PI-PD control approach is also performed.

Keywords:

• FL-based control
• load frequency regulation
• MG system
• renewable energy sources

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Anil Kumar Yadav

Anil Kumar Yadav received the Ph.D. degree in Instrumentation and Control Engineering from the University of Delhi, Delhi, India in 2017. He is currently working as an Assistant Professor in the Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar NIT Jalandhar, Jalandhar (Punjab), India. He has 14 years of teaching and research experience and published more than 80 research papers in Journals and Conferences of repute. His research interests include renewable energy, hybrid systems, electric vehicle, and nonlinear and intelligent control.

Praveen Kumar

Praveen Kumar is a research scholar in Electrical Engineering Department at NSUT New Delhi in self-finance mode. He received his ME in Instrumentation and Control from NITTTR Chandigarh in 2014. He has more than 19 years of teaching experience and published 5 research papers in Journals and Conferences of repute. He is currently working as assistant professor in ABES engineering college Ghaziabad (Uttar Pradesh, India). His research interest includes micro-grid, load frequency control, renewable energy and intelligent control systems.

Shyama Kant Jha

Shyama Kant Jha received B. Sc. Engineering degree in Electrical Engineering from Bhagalpur College of Engineering, Bhagalpur with Distinction marks and M.E. degree in Electrical with specialization in Control & Instrumentation from Delhi College of Engineering (DCE) [Presently Delhi Technological University (DTU)], Delhi University. He was awarded Ph.D degree from University of Delhi, New Delhi. Currently he is Professor in the Department of Instrumentation & Control Engineering at Netaji Subhas University of Technology (NSUT) [formerly Netaji Subhas Institute of Technology (NSIT)/Delhi Institute of Technology (DIT)], New Delhi. He has published/presented good number of papers in international and national journal, conferences. His teaching and research interests include optimal control, robust control, sustainable energy, bio-inspired control, and electric drives etc.

Pawan Kumar Pathak

Pawan Kumar Pathak received the Ph.D. degree in Electrical Engineering in 2021. He is currently working as an Assistant Professor in the School of Automation at Banasthali Vidyapith (Rajasthan, India). He has more than 8-years of teaching and research experience and published more than 35 research papers in Journals and Conferences of repute. His research interests include renewable energy, load frequency control, battery charger, electric vehicles, cyber-physical power systems, intelligent control, and meta-heuristics.