Optimum Power Forecasting Technique for Hybrid Renewable Energy Systems Using Deep Learning

Abstract

Power forecasting in large-scale electrical systems, comprising photovoltaic (PV), solar, and wind power, faces challenges due to geographical diffusion and temporal variations. Despite numerous studies, the disparity between predicted and actual generation remains a significant issue. This study utilizes historical power and atmospheric data from diverse plants, employing preprocessing techniques to enhance quality and reduce noise. K-Means clustering is applied to the dataset, optimizing deep learning training periods and increasing accuracy. A resilient hybrid deep learning model is proposed for microgrid (MG) power forecasting, encompassing preprocessing, model training, and assessment stages. Mathematical models for PV systems, battery storage, and wind systems, along with a K-means clustering algorithm, contribute to accurate forecasting. The recurrent neural network based on gated recurrent unit architecture outperforms traditional algorithms, demonstrating superior accuracy, and reduced errors in extensive experimental analyses. Pearson coefficients reveal associations between different power production forms, emphasizing the potential of hybrid renewable energy clusters to enhance forecasting. Case studies illustrate the partial controllability of concentrated solar power production, reducing overall renewable energy cluster unpredictability. The proposed method showcases the efficacy of the hybrid model in addressing challenges and improving accuracy in large-scale power forecasting.

Keywords:

• PV system
• power forecasting
• deep learning
• renewable energy system

Acknowledgment

There is no acknowledgement involved in this work.

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.

Author Contributions

All authors contributed equally to this work.

Data Availability Statement

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

Disclosure Statement

Conflict of interest is not applicable in this work.

Additional information

Funding

No funding is involved in this work.

Notes on contributors

Shashank Singh

Shashank Singh obtained his B.Tech., M.Tech and PhD form reputed university and has 17 years of Administration, Teaching and Research Experience. His area of interest includes Networks, Object oriented Programming, C, C++ and Java. He has published 11 patents and 49 research papers in various international journals and published 7 books. He is an administrator teacher, trainer and consultant in the field of Computer Science and Information Technology. He is SUN certified java Programmer. His current affiliation includes being a Proctor and Professor in Department of Computer Science & Engineering, SRIMT, BKT, Lucknow.

V. Subburaj

V. Subburaj MCA., M.Phil., M.E., Ph.D, currently working as professor in Dept of CSE, VEMU Institute of Technology, Chittoor, Andhrapradesh. Earlier served as Director in Dept of MCA at VVV College for Women, Virudhunagar, Tamilnadu. He has around 15 years of experience in academics and 4 years of experience in IT industry. He has around 120 articles in the form of conference, articles and journals in both national and international publication. He has solid number in both national and international patents in his name and a reputed trainer in AI, Data science, mobile and cloud apps development.

K. Sivakumar

K. Sivakumar working as an Associate Professor in the Department of Computer Science and Engineering, Nehru Institute of Engineering and Technology, Coimbatore. He has about 17 years of teaching experience. He received his B.E. degree in Computer Science and Engineering from Bharathiyar University, Coimbatore and M.E. degree in Computer Science and Engineering from Anna University, Coimbatore and also he received his Ph.D degree in Computer Science and Engineering from the Anna University, Chennai. He has published 16 research papers in refereed international journals and 13 research papers in various international conferences. He has received Innovative Technologist and Dedicated Teaching Professional Award and Young Research awards for his research papers at various professional bodies. He has 4 Indian patents, one book chapter and one book titled on “Cyber Forensics”. He is the reviewer of International Computer Science and Engineering Society and International Journal of Scientific Progress and Research. His areas of research include Theoretical Computation, Cryptography and Network Security, Cyber Security and Machine Learning. He is an active member of ISTE and CSI.

R. Anil Kumar

R. Anil Kumar is currently working as an associate professor in the electronics and communication engineering department at Aditya College of Engineering Technology, Surampalem. He received a doctoral degree from JNTUK University, Kakinada. He published 20 technical papers in various international journals and presented seven technical papers at various conferences. He is an expert in wireless communications, signal processing, and ML and DS. He published six patents. He is an associate member of IETE and ISTE.

M. S. Muthuramam

M. S. Muthuramam (B.Sc., M.Sc., M.Phil., Ph.D in Mathematics) is currently working as Professor, Department of Mathematics, PSNA College of Engineering and Technology (Autonomous), Dindigul, Tamilnadu, India. He is the author of 50 papers published in reputed journals and in proceedings of conferences, with many references from other researchers. His interests include Fuzzy Algebra, Discrete Mathematics.

Ravi Rastogi

Ravi Rastogi (B.Tech, M.Tech, Phd Pursuing) presently serving as Scientist- D and Head of Department of Electronics Division at National Institute of Electronics and Information Technology, Gorakhpur, UP India, an autonomous body governed by Ministry of Electronics and Information Technology, Govt of India. He has more than 9 years of experience in teaching and research. He has successfully executed industrial consultancy project and capacity building projects funded by both industry and central & state Govt. He has published more than 20 articles in national and international journals, guided several M.Tech students and implemented various projects. His area of research includes VLSI Design, Digital Signal and Image processing, Embedded Systems, Device Modeling, and Cyber Security.

Vishal Ratansing Patil

Vishal Ratansing Patil received B.E. degree in Computer Engineering from North Maharashtra University, India, and M.Tech in Software System from Rajiv Gandhi Prodyogiki Vishwavidyala and Ph.D. degrees in Computer Science and Engineering from Madhyanchal professional University, Bhopal, India. He was an Assistant Professor, in the Department of Computer Engineering from 2011 to 2021 Since 2011 November he has worked for many colleges like Sardar patel Institute of engineering, KJ Somaiya Institute of Engineering, Usha Mittal Institute of Engineering College as a Assistant Professor in the Department of Computer Engineering. He is currently working as a Assistant Professor in the Department of Computer Science and Engineering (AIML), Pimpri Chinchwad College of Engineering,Pune, India. He has published many papers in refereed journals and international conferences. His main research interests include Deep learning, Machine Learning, Cloud computing, Blockchain, Data science etc.

A. Rajaram

A. Rajaram received the B.E. degree in Electronics and Communication Engineering from the Government, College of Technology, Coimbatore, Anna University, Chennai, India, in 2006, the M.E. degree in Applied Electronics from the Government College of Technology, Anna University, Chennai, India, in 2008 and he received the Full Time Ph.D. degree in Electronics and Communication Engineering from the Anna University of Technology, Coimbatore, India in March 2011. He is currently working as a professor in Department of Electronics and Communication Engineering, E.G.S Pillay Engineering College, Nagapattinam. His research interests include Mobile Ad Hoc networks, wireless communication networks (WiFi, WiMax HighSlot GSM), novel VLSI NoC Design approaches to address issues such as low-power, cross-talk, hardware acceleration, Design issues includes OFDM MIMO and noise Suppression in MAI Systems, ASIC design, Control systems, Fuzzy logic and Networks, AI, Sensor Networks.