Forecasting of solar and wind power using LSTM RNN for load frequency control in isolated microgrid

ABSTRACT

Renewable sources such as solar PV and wind are stochastic in nature, hence their integration with emerging isolated microgrid (MG) is challenging especially with regards to stability issues. An accurate prediction model of wind and solar sources is necessary to analyze the uncertainty in MG system and to encourage the reliable participation of wind and solar power in the energy market. The advancement in deep learning methods has made it possible to develop a multi-step forecasting model unlike shallow neural networks (SNNs). The time series forecasting using SNN and Recurrent Neural Network (RNN) suffers from the problem of vanishing/exploding gradient while training. To eliminate this problem the long short-term memory (LSTM) RNN has been used in this study for wind speed and solar irradiance prediction. The forecasted solar and wind power is applied to analyze the load frequency behavior and the response of nonrenewable sources for sudden rise and fall in load power demand and PI controller is used to mitigate frequency deviation to ensure the stability of the MG power system.

KEYWORDS:

• Deep learning
• time series forecasting
• LSTM recurrent neural network
• microgrid
• load frequency control

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Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research work is supported by the Department of Science and Technology, New Delhi under the ICPS scheme through letter no. [DST/CPS/CLUSTER/IoT/2018/General].

Notes on contributors

Dhananjay Kumar

Dhananjay Kumar received the B.E. degree from Rajiv Gandhi Proudyogiki Vishwavidyalay (RGPV), Bhopal, India in 2009 and M.E. (Power Electronics) degree from Samrat Ashok Technological Institute, Vidisha under RGPV Bhopal in 2013. He is currently a full-time research scholar and pursuing Ph.D. degree at department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, Pilani campus, Rajasthan, India. His research interests include small signal modelling and stability control in microgrids, renewable energy integration to MG, forecasting of renewable power, robust control synthesis for frequency control in microgrids. He has authored 3 research articles in peer-reviewed international journals of repute and his 7 papers have been presented in IEEE sponsored international and top national conferences.

H. D. Mathur

H. D. Mathur received B.E. degree from Nagpur University, Nagpur, India, in 1998; M.E. degree from Malaviya Regional Engineering College, Jaipur, India, in 2000; and the Ph. D. degree from Birla Institute of Technology and Science (BITS), Pilani, India in 2007 and He was Post-Doctoral Fellow in Supelec, Paris, France in 2013. He was also visiting scientist to Centralesupelec, France in May- June of 2015 and May- June of 2019. Currently, He is Associate Professor in the Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani. He is having teaching and research experience of more than 20 years. Prof. Mathur is Associate Editor of IET Renewable Power Generation as well as in editorial board and reviewer of various journals mainly in field of electrical power system, renewable energy. He is a Senior member IEEE, Fellow of Institution of Engineers (India), Chartered Engineer and life member of Indian Society of Technical Education. He has published more than 65 papers in national/international journals and conference proceedings. His research interests include power system control of isolated and interconnected power systems, power system optimization, automatic generation control and artificial intelligence techniques applications in power systems and distributed generation (DG) with grid interconnection issues. He is handling research projects related to area of electrical power system, renewable energy integration, energy management in V2G etc. funded by Govt. agencies.

S. Bhanot

S. Bhanot obtained B.E. (Hons) Mechanical Engineering and M.Phil (instrumentation) from BITS, Pilani, and PhD from IIT Roorkee (then University of Roorkee). She has 17 years of teaching experience in BITS Pilani, and 19 years in Thapar University. She is presently Professor at EEE Department BITS Pilani. Her teaching and research areas are sensors, industrial instrumentation & automation, biomedical instrumentation, application of AI techniques in process modelling, control, image processing. She has been guiding projects/theses at first degree, higher degree and PhD level and has published research articles in international, national journals and conferences. She has published a book “Process Control, Principles and applications” with Oxford University press. She is reviewer of many books, research papers and sponsored projects. She received best teacher award at Thapar university and nominated by globally dispersed BITS alumni as a teacher that they would especially like to recognise.

Ramesh C. Bansal

Ramesh C. Bansal has more than 25 years of teaching, research, academic leadership, and industrial experience. Currently he is Professor in the Department of Electrical Engineering at University of Sharjah, Sharjah, United Arab Emirates. In previous postings, he was Professor and Group head (Power) in the Department of Electrical, Electronic and Computer Engineering at the University of Pretoria, South Africa and worked with the University of Queensland, Australia; University of the South Pacific, Fiji; Birla Institute of Technology and Science, Pilani, India; and Civil Construction Wing, All India Radio. Prof. Bansal has published over 300 journal articles, presented papers at conferences, and has published several books and chapters in books. He has Google citations of over 9000 and h-index of 44. He has supervised 20 PhD and 4 Post Docs and currently supervising several PhD students. He is an Editor/Associate Editor of member many reputed journals including IEEE Systems Journal, IET-Renewable Power Generation, Technology and Economics of Smart Grids and Sustainable Energy. He is a Fellow, and CP Engg. IET-UK, Fellow Institution of Engineers (India), and Senior Member IEEE. He has diversified research interests in the areas of Renewable Energy, Power Systems and Smart Grid.