Construction Of Charging Facilities Research Articles

Collaborative Planning of Community Charging Facilities and Distribution Networks

The construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem, this paper proposes a collaborative planning method for urban community charging facilities and distribution networks. First, based on the load density method and occupancy rate to predict the base electricity load in the community, the Bass model and charging probability are used to predict the community’s electric vehicle charging load. Taking the minimum annual construction and operation costs of the community distribution network as the objective function, the power supply topology of the distribution network for a new community is optimized by using Prim and single-parent genetic algorithms. Finally, the proposed scheme is verified by using the actual community data of a certain city in China as an analysis example, and the scheme of one-time planning of the distribution network and yearly construction of charging facilities is given.

The market for electric vehicles in China: modelling the abolition of policy incentives

ABSTRACT Government policies that contain incentives have promoted the development of China’s electric vehicle (EV) market from its inception. However, following the dramatic evolution of the EV market, the incentives impose a considerable burden on the State. It is time to consider abolishing various policy incentives. This paper uses the discrete choice experiment (DCE) model to study how consumer behaviours are influenced by the different policies. A system dynamics simulation model is constructed to simulate long-term EV development trends while considering the impacts of these policies. The simulations use the results from the DCE model to measure the sensitivity to policy changes of consumer purchase intentions (measured by consumers’ willingness to purchase EVs). Finally, in relation to likely future policy trends, this study designs policy portfolio scenarios that are a strong mix, mid-mix, weak mix, or fully market-oriented with varied timing for policy implementation, and that are likely to affect the growth of China’s EV market. The results of the simulation indicate that the optimal policies: (1) continue to increase government expenditure and support for the construction of charging facilities; (2) make charging more accessible and convenient; and (3) implement bans on the sale of fossil-fuelled cars. The results also show that the ideal timing for banning the sale of fossil-fuelled cars and, in parallel, cancelling current incentive policies (e.g. consumer purchase subsidies) is around 2025. These changes could reduce government expenditure and thus confer substantial financial savings, and they would effectively promote a significant increase in EV sales. Key policy insights Increasing support for the construction of charging facilities, improving the access and convenience of charging, and implementing bans on the sale of fossil-fuelled cars could increase consumer willingness to purchase EVs in China. Support for the construction of basic charging facilities should continue to increase and accelerate leading up to 2025; this would promote a significant increase in EV sales. To send clear near-term signals to the EV market – both consumers and producers, the Chinese government could usefully implement a ban on the sale of fossil-fuelled cars by around 2025 and in parallel abolish the current incentives policy for EVs. Abolishing current policy incentives (e.g. subsidies and VAT tax exemption) in the same time frame as other policies (e.g. support for charging infrastructure and a ban on fossil-fuelled cars), could lead to substantial financial savings to the government and a rapid scaling in the market for EVs. Lessons learned from China’s potentially large and rapidly growing EV market will have implications for other countries in Asia and beyond.

Electric Vehicle Charging Facility Planning Based on Flow Demand—A Case Study

The location of electric vehicle charging facilities is of great significance in promoting the use of electric vehicles. Most existing electric vehicle location models, including the flow refueling location model (FRLM) and its flexible reformulation (FRFRLM), are based on flow demand. At present, these models cannot effectively deal with large-scale traffic networks within a limited time, and there has been little comparison of their relative benefits and limitations. Additionally, there have been few evaluations of the actual construction and location of charging facilities in cities. This paper describes an algorithm that can solve the large-scale transportation network problem within a reasonable time. Using this algorithm, the FRLM and FRFRLM models are compared in a case study focused on Jiading District, Shanghai, China, which provides some direction for the future development of flow demand models. Finally, to evaluate the actual construction of urban charging facilities, this paper presents an algorithm that can map the actual charging facilities to the transportation network, and compares the actual construction situation with the model output. This enables a comprehensive evaluation of the actual construction of charging facilities and provides guidance for future construction.