Q-Learning Based Commercial Electric Vehicles Scheduling in a Renewable Energy Dominant Distribution Systems

Abstract

The increasing prevalence of commercial electric vehicles (CEVs) for ferrying passengers has become popular in recent times. This scenario strains the distribution system (DS) during the system charging cycle. However, the design becomes beneficial if the CEVs support the utility based on the needs. This work aims to efficiently schedule the operational modes of CEVs to decrease power loss in the DS in the presence of distributed generation (DG). The CEVs are modeled by considering the uncertainty in their travel patterns. This work proposes a combined approach to reduce power loss and enhance voltage quality by adopting internet of Things (IoT) enabling technologies. This method combines Voltage Stability Index (VSI), Q-learning method, and enhanced moth flame optimization (EMFO) for efficient operation of DS. The DS considers IoT-enabled EV charging stations (EVCSs), DGs, and CEVs for 3-way communication. Various case studies are presented to show the efficacy of the proposed technique compared to existing methods in the literature.

Keywords:

• IoT-enabled EVCS
• Q-learning
• CEVs
• G2V
• V2G
• eMFO
• distribution system

Disclosure statement

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

Additional information

Notes on contributors

Suresh Velamuri

Suresh Velamuri (Senior Member, IEEE) is working as a Senior Engineer – Power Systems at Eaton Research Labs. In this role, he is advancing technologies under Grid Intelligence & DERMS themes. Suresh has a Ph.D. degree in Electrical Engineering with an emphasis on Power system planning and operation from VIT University, Vellore. He received his B.Tech. in Electrical & Electronics Engineering and MTech. in Power Systems from JNTU, Kakinada. Prior to joining Eaton, Suresh worked in areas related to Energy management in microgrids/smart grids, demand side management, and the application of AI techniques to power system problems. He is a Senior Member of IEEE and has published more than 40 research articles in international journals and conferences. He has received various awards such as the “VIT Research Award 2016”, and “Best Paper Award – ICICS2018” for his research contributions. He serves as a reviewer for many international journals and a technical committee member of international conferences.

Suresh Kumar Sudabattula

Suresh Kumar Sudabattula completed his Ph.D. at the Vellore Institute of Technology, Vellore in 2018. He received his B.Tech and M.Tech in Electrical and Electronics Engineering from JNTU, Kakinada in 2007 and 2011 respectively. He is currently an Associate Professor in the School of Electronics and Electrical Engineering, at Lovely Professional University, Punjab, India. His research interests include distributed generation, electric vehicles, and power system optimization.

M. V. V. Prasad Kantipudi

M. V. V. Prasad Kantipudi is working as an Associate Professor in the Dept. of E&TC, Symbiosis Institute of Technology, Pune. He received his B.Tech. (Electronics and Communications) (2009) & M.Tech. (Digital Electronics and Communication Systems) (2011) degrees from Jawaharlal Nehru Technological University, Kakinada. He received his Ph.D. (Signal Processing specialization) from BITS, VTU, Belagavi (2018). He, previously worked as the Director of Advancements for Sreyas Institute of Engineering & Technology, Hyderabad, and also as an Associate Professor with R.K. University, Rajkot. He has teaching experience of around 12.2 years. He is recognized as a technical resource person for Telangana state by the IIT Bombay Spoken tutorial team. He conducted key Training Workshops on Open-Source Tools for education, Signal Processing and Machine Learning focused topics, Educational Technology, etc. He has authored and co-authored many papers in International Journals, International Conferences, and National Conferences and published five Indian Patents. Prasad is a Senior Member of IEEE (Membership ID: #93513961) and an active member of Machine Intelligence Research Labs and USERN (Universal Scientific Education and Research Network) (April 2020 – present). He is one of the active reviewers for Wireless Networks, Journal of Springer Nature. His name is listed at 19th position in Top 100 Private University's Authors Research Productivity Rankings given by the Confederation of Indian Industry (CII) based on the "Indian Citation Index" Database 2016. His current research interests are in Signal Processing with Machine Learning, Education and Research.

Natarajan Prabaharan

Natarajan Prabaharan (Senior Member, IEEE) received his BE in Electrical and Electronics Engineering and the ME in Power Electronics and Drives from Anna University, Chennai, India in 2012 and 2014, respectively. He received his Ph.D. from Vellore Institute of Technology (VIT), Vellore, India, in 2017. He is currently an Assistant Professor at the Department of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur, India. He serves as an Associate Editor for many journals including IET RPG, IEEE Access, and the Journal of Power Electronics. His research interest includes electric vehicle, power electronics converter (DC-DC converter and multilevel inverter), grid integration of renewable energy sources and its controllers, photovoltaic system, microgrid, Energy trading, and demand side management.