Deep learning assisted solar forecasting for battery swapping stations

ABSTRACT

For the development of renewable energy generation as a viable alternative to fossil fuel-based generation, solar power has received widespread acceptance. An increase in solar power usage can mitigate the impact of climate change, energy demand, and cost-effective dispatch. To use solar power efficiently and ensure grid consistency, reliable and accurate forecasting of information becomes very crucial. Hence, the main purpose of this work is to get the best suitable solar irradiance forecasting model and to implement the forecasted solar power to the designed hybrid battery swapping stations. Each year, new techniques and approaches are used to improve the model accuracy with the critical aim of lowering the variability of predictions. This paper takes a close look at different deep-learning methods to predict solar irradiance for a certain period of time. The real-time time series data is used, and for analyzing the time series data, the statistical ARIMA model, LSTM-based RNN technique, and Dual Attention-based Recurrent Neural network have been used. These models are implemented using Jupyter Notebook with Python programming language. To analyze the efficiency and evaluate the performance of real-time data of the models, a comparative study has been done on the different error metrics. This paper reveals that the LSTM model is providing the best solar power forecasting with the least error metrics like MSE of .0091, MAE of .0525, RMSE of .0953, and MSLE of .0047.

KEYWORDS:

• Solar PV
• solar forecasting
• LSTM
• ARIMA
• DA-RNN

Acknowledgements

The authors would like to acknowledge the National Renewable Energy Laboratory (NREL) and the School of Advanced Materials, Green Energy & Sensor Systems (SAMGESS), IIEST Shibpur for providing the irradiance and weather data for this research work.

Disclosure statement

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

Additional information

Notes on contributors

Sandeep Kumar Chawrasia

Sandeep Kumar Chawrasia holds the esteemed position of Senior Research Fellow within the vibrant academic community of the Electrical Engineering Department at the Indian Institute of Engineering Science and Technology, Shibpur, India. His professional expertise spans a diverse array of fields, with a particular emphasis on pioneering developments in electric vehicles (EVs), including advancements in battery technology, efficient charging infrastructure, and innovative swapping stations. Through his diligent research efforts, Chawrasia is at the forefront of addressing critical challenges facing the widespread adoption of EVs, paving the way for a more sustainable and environmentally friendly transportation landscape. Furthermore, Chawrasia’s academic pursuits extend beyond his primary research interests, encompassing broader themes within electrical engineering. His multidisciplinary approach and dedication to scholarly inquiry enrich the academic community at the Indian Institute of Engineering Science and Technology, Shibpur, fostering a culture of innovation and excellence.

Debmalya Hembram

Debmalya Hembram professional journey is anchored in his role as a Graduate Engineer Trainee (GET) at TATA Power Solar System Limited, where he contributes his skills and expertise to the forefront of solar energy innovation and implementation. Building upon a solid foundation laid during his academic pursuits, Hembram graduated with distinction from the prestigious Electrical Engineering Department at the Indian Institute of Engineering Science and Technology, Shibpur, India. Hembram’s areas of expertise align closely with the evolving landscape of energy systems, with a particular emphasis on power systems. Through his work at TATA Power Solar System Limited, he actively engages in the design, optimization, and implementation of robust power systems that underpin the efficient generation, transmission, and distribution of solar energy. His contributions in this domain are instrumental in advancing the company’s goals of enhancing energy access, reliability, and sustainability.

Dipanjan Bose

Dipanjan Bose occupies the esteemed position of Senior Research Fellow within the distinguished Electrical Engineering Department at the Indian Institute of Engineering Science and Technology, Shibpur, India. At the core of Bose’s scholarly pursuits lies a profound interest in enhancing power system resilience and addressing critical vulnerabilities inherent in contemporary energy infrastructures. Through rigorous investigation and pioneering methodologies, he endeavors to fortify power grids against unforeseen disruptions and external threats, thereby ensuring the reliable and uninterrupted delivery of electricity to communities and industries alike. Furthermore, Bose’s scholarly pursuits extend beyond the confines of his primary research interests, encompassing interdisciplinary collaborations and holistic approaches to addressing complex energy challenges.

Chandan Kumar Chanda

Dr. Chandan Kumar Chanda is working as a Professor (Higher Administrative Grade) in the Department of Electrical Engineering, IIEST, Shibpur, India. He has earned Ph.D. degree from the Department of Electrical Engineering, B.E. College (DU), Shibpur, India with specialization in Power Systems. Dr. C. K. Chanda has over 34 years of teaching and research experience in the diverse field of Power Systems Engineering and almost 5 years’ experience in industry. His areas of interest include Renewable Energy, Smart Grid, Resiliency, Power System Stability etc. He is a recipient of Tata Rao Gold Medal. He is actively involved in various research projects funded by Centrally Funded Organizations like DST, UGC. He has published more than 200 research articles in reputed National/International journals and conferences including 65 research papers in SCI /SCOPUS -indexed journals.