Optimal analysis for facility configuration and energy management on electric light commercial vehicle charging

Tang, Y, Zhang, Q, Wen, Z, Bunn, D W and Nieto Martin, J (2022) Optimal analysis for facility configuration and energy management on electric light commercial vehicle charging. Energy, 246. ISSN 0360-5442

Abstract

Whilst the widespread adoption of electric vans is necessary to improve urban air quality and reduce carbon emissions, it is also self-evident that adequate charging stations are a precondition. However, the investment case for basic charging stations without public subsidies is challenging. In the context of a London case study, four business models are compared, which integrate solar power generation and new/second-life battery storage system with the basic charging facilities. Considering the uncertainties of electricity tariff and solar generation, the optimal infrastructure investment and operational planning has been formulated as a two-stage stochastic optimization model. The results show that: (i) in the integrated business models, the return on investment and charger installations could be increased by up to 5.39% and 17.06% respectively, and the carbon intensity could be reduced by up to 8.13%; (ii) the nondiscriminatory grant annualized as 50 £ is not sufficient, and a differentiated government subsidy policy may be more conducive to achieving a positive return on investment, such as 50 £ for fast chargers and 100 £ for rapid chargers; (iii) in the integrated business models, fast chargers undertake more vehicle-to-grid electricity exchange with the pattern adoption rate increased by up to 52.38%, while rapid chargers mainly ensure the timely charging completion with the usage frequency increased by up to 2.82%.

More Details

Item Type:	Article
Subject Areas:	Management Science and Operations
Funder Name:	National Social Science Foundation of China, National Social Science Foundation of China
Date Deposited:	09 Feb 2022 09:49
Date of first compliant deposit:	09 Feb 2022
Last Modified:	12 Nov 2024 16:45
URI:	https://lbsresearch.london.edu/id/eprint/2225

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