Comparison of a Novel AFPSO-SFS & PSO-SFS Approaches for Islanding Protection of Inverter-Based DGs

Abstract

The most significant of the active islanding detection techniques is “Sandia Frequency Shift” (SFS), and this employs frequency drifting to identify extra Nondetection Zone. Inappropriate tuning parameters, such as the acceleration factor and chopping factor, result in frequency drifting, which degrades the quality of the power and causes the continuous power mode to fail. The failure can be overcome by considering optimized parameters to identify the nondetection zone (NDZ) in small DG system (120 kVA) at constant power/current mode. This article discusses, a new Adaptive Fuzzy Particle Swarm Optimization-SFS (AFPSO-SFS) technique is recommended to attain optimal parameters of SFS anti-islanding detection technique for validation of the proposed algorithm Particle Swarm Optimization–SFS (PSO-SFS) is also implemented. Furthermore, the ability of this method is to identify an islanding situation which deteriorates the major scientific issues for small DG system. Thus, the optimized parameter helps to attain an anti-islanding as well as less impact on power quality. Moreover, this article concerns serious issue of the grid interconnected DG model in an islanding condition, when the utility line would be unintentionally isolated. The grid detachment is generally considered as a fault. When an islanding occurs, the DG protection system must be inactive to detect the fault. For the investigation of power mismatches, the output of considered system using the proposed methods is contrast with results obtained from PSO-SFS and conventional SFS. The recommended strategy analyzes islands more effectively and diagnoses nondetection zones more accurately. The recommended method’s reliability is calculated quantitatively and emulated with MATLAB/Simulink.

HIGHLIGHTS

• The present article proposes a novel AFPSO-based active SFS islanding approach with suitable parameters can yield almost negligible NDZ.

• A systematic investigation of active, reactive, and zero power mismatches at the point of time of isolation from the utility, along with its influence on amplitude of frequency as well as voltage.

• An examination of a very slight change, i.e., necessary to go beyond the threshold limits for different $\mathbf{\text{quality factors}}(Q_f)$ and also demand $\mathbf{\text{resonant frequencies}}(f_r)$ depicts, any kind of islanding can be easily perceived.

• A systematic various case studies have been executed.

Keywords:

• distribution generation
• Sandia Frequency Shift
• non detection zone
• Adaptive Fuzzy Particle Swarm Optimization
• Particle Swarm Optimization

Disclosure Statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Kusuma Gottapu

Kusuma Gottapu completed her B.Tech degree in Electrical and Electronics Engineering from Jawaharlal Nehru Technological University, Hyderabad, India, in 2006, followed by an M.E degree in Control Systems from Andhra University, India, in 2012, and a Ph.D. degree in Electrical Engineering from the Andhra University College of Engineering (A), India, in 2019. She currently holds the position of Assistant Professor in the Department of Electrical and Electronics Engineering at Sagi Rama Krishnam Raju Engineering College, Bhimavaram, West Godavari District, Andhra Pradesh, India. Her research interests encompass Control of Renewable Energy Systems, Power Quality, Power System Analysis, Power Flow Studies, Optimization and Control of DERs, and Soft Computing Techniques and Smart Grids. She is knowledgeable about solar energy systems and has a lot of experience configuring PV arrays. She has contributed to the development of MPPT by publishing a number of research articles and possesses the drive to implement a number of control strategies for both Wind and Solar systems.

V. V. S. Narayana Yirrinki

V. V. S. Narayana Yirrinki has received his B.Tech in Electrical and Electronics Engineering from JNT University-Kakinada, India and followed by M Tech from S.R.K.R. Engineering College (A), Bhimavaram, West Godavari District, Andhra Pradesh, India. He is currently working as an Assistant Professor in the Department of Electrical and Electronics Engineering, S.R.K.R. Engineering College (A), Bhimavaram, West Godavari District, Andhra Pradesh, India. His research interest includes Smart Grid, Power Quality, Power System Optimization techniques, Power Electronics, Flexible AC transmission systems, Power System Operation and Control, Digital Signal Processing and AI techniques.

Madeti Siva Ramakrishna

Madeti Siva Ramakrishna an accomplished scholar, earned his M.Tech and Ph.D. degrees from IIT Roorkee before pursuing a Postdoctoral fellowship at the University of Talca, South America. With a rich academic background, he contributed as an Associate Professor at the University of Santiago de Chile for three years, honing his expertise. Presently, he channels his passion for education and research as a distinguished faculty member at Gati Sakthi Vishwavidyalaya, under the esteemed Ministry of Railways, Government of India. His research interests encompass Renewable Energy, Solar Photovoltaics, Machine Learning, PV Durability, and Reliability.

Katari Deepthi

Katari Deepthi completed her post graduate degree in the department of Electrical and Electronics Engineering from JNTU Kakinada, Andhra Pradesh, India. She received the Bachelor of Technology degree in the department of Electrical and Electronics Engineering from JNTU Kakinada, Andhra Pradesh, India. She is currently working as an Assistant Professor in the Department of Electrical and Electronics Engineering, S.R.K.R. Engineering College (A), Bhimavaram, West Godavari District, Andhra Pradesh, India. Her research interest includes Power Quality, Power System Optimization techniques, Power Electronics, Flexible AC transmission systems, Power System Operation and Control, Digital Signal Processing and AI techniques.

Krishna Murari

Krishna Murari completed his B.Tech degree in Electrical Engineering from WBUT, India, in 2010, followed by an M.E degree in Power Systems from Thapar University, India, in 2014, and a Ph.D. degree in Electrical Engineering from the Indian Institute of Technology Roorkee, India, in 2019. He currently holds the position of Research Assistant Professor in the Department of Electrical Engineering and Computer Science at The University of Toledo in Toledo, Ohio, USA. Prior to this role, he worked as a Research Associate at Clarkson University, Potsdam, New York, and as a Postdoctoral Fellow with the Energy Production and Infrastructure Center (EPIC), University of North Carolina at Charlotte, North Carolina, USA. He is the recipient of the Third best-prized paper by The Industrial Automation and Control Committee of the IEEE Industry Application Society among the research articles presented in the IEEE Industry Application Society annual meeting 2021. He is a reviewer in journals, such as IEEE, IET, MDPI, and Taylor Francis journal. His research interests encompass power system analysis, power flow studies, demand-side management, optimization and control of DERs, optimal power flow, distribution network pricing, and smart grid technologies.