A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions. (12th July 2017)

• Record Type: Journal Article
• Authors: Kabatepe, Bora; Türkay, Metin
• Is Part Of: Computers & chemical engineering. Volume 102(2017)
• Page Start: 156
• Page End: 168
• Publication Date: 2017-07-12
• Subjects: Electric vehicles -- Impact analysis -- Greenhouse gases -- Bi-criteria optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2016.11.026
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Impact assesment of electric vehicles. A bi-criteria optimization model is constructed for electricity dispatching needs for charging electric vehicles. Pareto solutions considering the levelized cost of electricity and GHG emissions depending on the source of marginal electricity are generated. Application on a real life case of Turkey. Abstract: Electric vehicles (EV) are emerging as a mobility solution to reduce emissions in the transportation sector. The studies environmental impact analysis of EVs in the literature are based on the average energy mix or pre-defined generation scenarios and construct policy recommendations with a cost minimization objective. However, the environmental performance of EVs depends on the source of the marginal electricity provided to the grid and single objective models do not provide a thorough analysis on the economic and environmental impacts of EVs. In this paper, these gaps are addressed by a four step methodology that analyzes the effects of EVs under different charging and market penetration scenarios. The methodology includes a bi-criteria optimization model representing the electricity market operations. The results from a real-life case analysis show that EVs decrease costs and emissions significantly compared to conventional vehicles.