Open AccessMitigating load burden on smart grid via EVs
Author(s) -
Ramesh Singh,
Aman Jolly,
Ritika Gour
Publication year - 2022
Publication title -
international journal of health sciences (ijhs) (en línea)
Language(s) - English
Resource type - Journals
eISSN - 2550-6978
pISSN - 2550-696X
DOI - 10.53730/ijhs.v6ns1.5500
Subject(s) - electrification , smart grid , carbon footprint , electricity , environmental economics , tariff , energy storage , electric vehicle , work (physics) , rural electrification , energy consumption , population , grid , automotive engineering , computer science , engineering , business , electrical engineering , economics , greenhouse gas , mathematics , mechanical engineering , ecology , power (physics) , physics , demography , quantum mechanics , sociology , international trade , biology , geometry
World energy consumption is quickly rising as a result of population and economic expansion, particularly in big emerging economies, which will account for 90% of energy demand increase through 2035. Electric vehicles (EVs) are critical components of the electrification revolution aimed at reducing the carbon footprint. In this case study, a completely different side of EVs is explored where EVs can be used as an energy storage unit that has the potential to meet the demands of high energy needs in a variable electricity tariff setting. The study proposed in this work suggests that energy stored in EVs can also be used back in the smart grid at the time of high energy requirements which can significantly decrease the load shedding in both urban and rural areas. The simulation model presented on MATLAB shows a significant dip in energy demand after electricity stored in the Electric vehicles is used back in the smart grid. The study also proposed an ensemble model that is able to predict the overload in the Grid. The ensemble model achieving the R2 score of 0.87 and RMSE value of 0.06.