Optimal fleet replacement management under cap-and-trade system with government subsidy uncertainty

Abstract

China has taken a number of positive measures to meet the requirement of environmental protection. The switch to electricity especially in transport sector is considered as a promising way to reducing greenhouse gas (GHG) emissions and facilitating to meet China's carbon neutral target in 2060. Besides, because of the overall impact of the COVID-19 on the transport sector, the future measures imposed by the government on electric vehicles (EVs) remain in high uncertainty. Taking the characteristics of different vehicles, business models, uncertainty of government financial subsidies and environmental factors into consideration, a replacement optimization model for a taxi fleet is proposed in this study under the cap-and-trade system. We assume that the taxi company has four types of vehicles to purchase or lease and manage to maximum the pecuniary advantages and environmental benefits simultaneously. Experimental results analyze that EVs and battery-swap electric vehicles (BSVs) are highly competitive when government subsidies do not decline. During the early stage of the planning horizon, adjusting the fleet continuously and timely can help the company to realizing the maximum revenue.