Location Selection for Wireless Electric Vehicle Charging Lanes Using an Integrated TOPSIS and Binary Goal Programming Method: A UAE Case Study

Abstract

To address range anxiety concerns of current and potential EV drivers, on-the-move charging of electric vehicles (EV) is introduced through the development of roadway electrification solutions, i.e., wireless charging lanes (WCLs). These lanes allow EVs to recharge their batteries and compensate for the energy consumed during their motion. Nevertheless, the high deployment and operational costs of WCLs raise concerns about their expected utilization and returns on the investment. This calls for a detailed analysis of the potential locations for WCL implementation. This work proposes a two-staged multi-criteria decision making (MCDM) framework that integrates the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with binary goal programming (BGP), to evaluate potential locations for WCL implementation according to geospatial, environmental, technical and economic criteria. In the first stage, the TOPSIS method is utilized to rank several alternative locations according to their geospatial, environmental and technical specifications. The alternatives with the highest ranking are then shortlisted and evaluated using a mathematical BGP model, to provide recommendations on the most optimal locations and the corresponding WCL lengths that meet budget constraints according to the economic evaluation criteria. The proposed integrated TOPSIS-BGP model offers a comprehensive decision-making approach by acknowledging diverse criteria that are otherwise difficult to integrate into a single combinatorial mathematical program. A case study of major UAE cities, namely Dubai and Sharjah, is presented to illustrate the implementation of the proposed framework.