Exploring the value of electric vehicles to domestic end-users

Energy Policy(2023)

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摘要
Owing to the recent ban on the sales of new petrol and diesel cars in the United Kingdom (UK) by 2030, combined with the UK’s commitment to net-zero emission of greenhouse gases by 2050, a projected increase in the growth rate of electric vehicles (EVs) is inevitable. In recent years, there has been an increase in the adoption of EVs, but not at a rate sufficient to meet net-zero targets. Although benefits do exist for current EV owners, barriers such as the availability of charging infrastructure, total cost of ownership, battery costs, amongst others still present a challenge for the required adoption rate. In this work, we therefore aim to address some of these barriers, specifically the total cost of ownership and battery costs, by exploring the value a range of EVs on the market give to domestic end-users with different usage classes. Using a techno-economic-environmental mixed integer linear optimisation model which considers local energy demands, retail electricity tariffs, local renewable energy generation and battery degradation, potential benefits for EVs adopters are analysed from a cost or Carbon dioxide (CO2) minimisation objective. This model adopted considered a range of vehicle types – EVs and non-EVs – and properties, installed PV sizes, and user travel behaviour classes, and results showed that although EVs have a relatively higher purchase costs, total cost values are comparable, in some cases cheaper, when compared with conventional non-EVs. EV users further gain from environmental benefits through a reduction in the CO2 emitted irrespective of the user’s desired goal. A dominance analysis was also carried out to determine the order of importance of key input variables to the optimisation model in predicting costs and CO2 emission quantities. The results obtained are helpful to end-users in prioritising EV features during purchase based on personal goals of cost or carbon emissions reduction.
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关键词
Electric vehicles,Optimisation,Scheduling,Net-zero,Renewable energy
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