A realistic framework to a greener supply chain for electric vehicles

Abstract

Summary The quantity of electric vehicles in the transport sector has steadily risen over the last 10 years. Most developed countries and China have laid out ambitious plans for electric vehicles penetration. However, there are several challenges that must be addressed on the supply‐chain side of the problem for a successful transition toward an alternative and less environmentally harmful transport system. This study proposes a methodology for the optimal plan and decision making of primary energy sources, electricity generation, electricity distribution to vehicles' charging stations, carbon capture and sequestration, and electric vehicles' charging stations network to satisfy the electricity demand of the overall economy including electric vehicles at a regional/countrywide level under operation and green constraints. The optimization problem was modeled as a mixed integer program in general algebraic modeling system (GAMS). The formulation was employed to propose the upcoming electricity supply chain for electric vehicles in the most populous German state (North Rhine‐Westphalia) in 2025. The optimization show that fossil‐based power still controls the generation in 2025, while carbon capture and sequestration along with higher renewable penetration help meeting the state's greenhouse gases (GHG) emission target. The charging stations network expansion consists of 12 820 charging points mainly alternating current (AC) chargers (22‐kW capacity).

Decentralized scheduling optimization for charging‐storage station considering multiple spatial‐temporal transfer factors of electric vehicles

“…Thus let P st denote the transition probability, st {2, 3, …, n − 1, n, n + 1}. Then the transition probability from node 1 to node r, that is, p (rj1, a r ), can be derived via Equations (2) and (3), where r {2, 3, …,n-1, n, n + 1} 31 :…”

“…Electric vehicle (EV) industry not only provides strong drivers to the economic growth of various countries but also helps reduce greenhouse gas emissions to cope with climate change and improve the global ecological environment. 1,2 Furthermore, the industry has been entering a new stage of accelerated development. It is estimated Abbreviations: AC, air conditioning; AR, access road; CC, central controller; CS, charging station; CSS, charging-storage station; ESB, energy storage battery; ESS, energy storage station; EV, electric vehicle; EW, expressway; ILDRM, improved Lagrange dual relaxation method; LC, local controller; LDRM, Lagrange dual relaxation method; MDP, Markov decision process; PVD, peak-valley difference; SD, standard deviation; SOC, state of charge; STR, secondary trunk road; TR, trunk road.…”

“…Electric vehicle (EV) industry not only provides strong drivers to the economic growth of various countries but also helps reduce greenhouse gas emissions to cope with climate change and improve the global ecological environment 1,2 . Furthermore, the industry has been entering a new stage of accelerated development.…”

Neural network‐based energy management of multi‐source (battery/UC/FC) powered electric vehicle

“…3 Electric vehicles (EVs) are regarded as a potential solution to environmental pollution, energy source shortages and global climate issues, highly concerned worldwide caused by transportation with fast development of automobile industry and increasing car ownership. 4,5 Electric vehicles with internal combustion engine (ICE) are called as hybrid electric vehicle (HEV) [6][7][8] and result low-emission 9,10 compared to conventional ones. However, the goal is to have zero-emission vehicles (ZEVs) 11 which has no ICE in its powertrain.…”

Environmental impact assessment of green energy systems for power supply of electric vehicle charging station

“…Power plants and transmission lines are modeled and simulated using a georeferenced optimal power flow. Betancourt‐Torcat, et al formulate in Reference 45 an optimal decision‐making methodology using a general algebraic modeling system for satisfying the overall electricity demand, considering carbon capture and distribution of electricity to EV‐CS. De Tena and Pregger investigate in Reference 46 the impact of electro mobility on power systems in Europe, especially in Germany by 2050.…”