Mr. Vikash Saini | Energy | Editorial Board Member
MNIT, Jaipur | India
Author Profile
Early Academic Pursuits
Vikash Saini, hailing from MNIT Jaipur, India, embarked on an academic journey marked by excellence. Graduating in Electrical Engineering and subsequently earning an M.Tech in Power Systems, he exhibited a keen interest in cutting-edge domains.
Professional Endeavors
Vikash's professional trajectory includes roles at esteemed institutions such as IIT Kanpur, Poornima College of Engineering, and significant contributions in seismic data processing at BP. He pursued a Ph.D. at MNIT Jaipur, showcasing a commitment to advancing knowledge.
Contributions and Research Focus
His expertise spans diverse areas like RE forecasting, energy storage, battery degradation models, local energy markets, and blockchain technology. Vikash has led projects focusing on smart distributive systems, EV charging infrastructure, and the impact of electric mobility.
Accolades and Recognition
Vikash's research has earned recognition with publications in renowned journals, including Elsevier. His work on short-term wind speed forecasting and optimal battery sizing demonstrates his innovative contributions to the field.
Impact and Influence
Vikash's influence extends to various domains, evident in his work on peer-to-peer energy trading, multi-agent systems, and cloud energy storage. His projects have addressed critical aspects like energy security, carbon footprint, and optimal power flow in distribution networks.
Legacy and Future Contributions
With a solid foundation in programming (C, Python) and tools like Matlab and GAMS, Vikash has positioned himself as a thought leader. His commitment to renewable energy, blockchain, and smart grids showcases a legacy focused on sustainability and technological innovation.
Notable Publications
Short term forecasting based on hourly wind speed data using deep learning algorithms 2020 (25)
Cloud Energy Storage Systems for Consumers and Prosumers in Residential Microgrids 2020 (8)
Learning Approach for Energy Consumption Forecasting in Residential Microgrid 2022 (6)