Machine Learning-Based Power Quality Improvement of Wind-PV System Using ANFIS

Abstract

The drastic improvements in Energy utilization are rooted in the search for alternative sources for generating Electricity. Due to their advantages for the environment, the integrations of RES into the powers grids, like wind and photovoltaic (PV) systems, has received a lot of attention. The grid’s power quality is challenged by the intermittent and erratic nature of various energy sources. In this research, enhanced Random Forest and ANFIS-based intelligent control algorithms are proposed to reduce the power quality issues in the hybrid PV-integrated Directly Driven Synchronous Generator efficiently. Here, the supervised RF-ANFIS algorithms are acting as a hybrid approach of machine learning techniques that will dynamically allocate the switching sequence for the power converters connected to the grid. Finally, the THD is reduced to less than 2.25% with a time period of 3 ms and upholds voltage stability within allowable bounds. Due to this, the system successfully raises the power factor, creating a steady and dependable power supply. The advancement of more effective and dependable renewable energies integration into the powers grids will ease the transition to a future with resilient and sustainable energy sources.

Keywords:

• DDSG-PV
• random forest
• aNFIS
• DC–AC converter
• switching sequence
• tHD

Author Contributions

All authors contributed equally to this work

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Ethics Approval and Consent to Participate

No participation of humans takes place in this implementation process

Human and Animal Rights

No violation of Human and Animal Rights is involved.

Additional information

Notes on contributors

Murugan Marimuthu

Murugan Marimuthu received the Bachelor of Engineering degree in Electrical and Electronics Engineering from Alagappa Chettiar Government College of Engineering and Technology, Karikudi, Tamil Nadu, India in 2002. He received the Master of Engineering degree in Power Electronics and Drives from Government College of Technology, Coimbatore, Tamil Nadu, India in 2004. He received PhD Degree in Faculty of Electrical Engineering from Anna University, Chennai, Tamil Nadu, India in 2016. He is currently working as an Assistant Professor in the Department of Electrical and Electronics Engineering at Government College of Engineering, Bodinayakkanur, Tamil Nadu, India. His area of interests includes Power Electronics, Control of Electrical Drives, Renewable Energy Systems and Multilevel Inverter etc., He has published 16 articles in peer reviewed international journals and presented 18 papers in international conferences. He can be contacted at email: [email protected].

Shanmuganathan Chandrasekaran

Shanmuganathan Chandrasekaran currently working as an Assistant Professor in the Faculty of Engineering and Technology at SRM Institute of Science and Technology, Ramapuram, Chennai, India. He has completed his Ph.D. in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India in 2018. He received his Master of Engineering in Computer Science and Engineering from Annamalai University, Chidambaram in 2004 and he has completed his Bachelor of Engineering in Computer Science and Engineering from University of Madras in 2000. His research area includes Network Security, Mobile Computing and Machine Learning. He has published many articles in peer reviewed journals and presented papers in National/International conferences. He can be contacted at email: [email protected].

Manjunathan Alagarsamy

Manjunathan Alagarsamy received the Engineer degree in Electronics and Communication Engineering from Dr. Navalar Nedunchezhiyan College of Engineering in 2010. He received the Master degree in Embedded System Technologies from Raja College of Engineering and Technology, Madurai, Tamilnadu, India in 2013. He is currently working as an Assistant Professor in the Department of Electronics and Communication Engineering at K. Ramakrishnan College of Technology, Trichy, India. His area of interests includes Embedded Systems, Image processing, Sensors and Interfacing networks and Internet of Things. He has published 53 articles in peer reviewed International journals and presented 7 papers in International conferences. He can be contacted at email: [email protected].

Tamilnesan Pannerselvam

Tamilnesan Pannerselvam received the Engineer degree in Electrical and Electronics Engineering from Anna University Chennai in 2012. He received the Master degree in Power Systems Engineering from Anna University Regional Campus, Coimbatore, Tamilnadu, India in 2016. He is currently working as an Assistant Professor in the Department of Electrical and Electronics Engineering at Kongunadu College of Engineering and Technology (Autonomous), India. His area of interests includes Power Systems, Industrial Automation and Internet of Things. He can be contacted at email: [email protected].