Search Results (18)

With the impact of fossil energy on the climate environment and the development of energy technologies, new energy vehicles, represented by electric cars, have begun to receive increasing attention and emphasis. The rapid proliferation of public charging infrastructure for NEVs has concurrently influenced traditional petrol station networks, creating measurable disparities in their spatial distributions that warrant systematic investigation. This research examines Wenzhou City, China, as a representative case area, employing multi-source Point of Interest (POI) data and spatial analysis models to analyse differential characteristics in spatial layout accessibility, service equity, and underlying driving mechanisms between public electric vehicle charging stations (EV) and traditional gas stations (GS). The findings reveal that public electric vehicle charging stations exhibit a pronounced “single-centre concentration with weak multi-centre linkage” spatial configuration, heavily reliant on dual-core drivers of population density and economic activity. This results in marked service accessibility declines in peripheral areas, resembling a cliff-like drop, and a relatively low spatial equity index. In contrast, traditional gas stations demonstrate a “core-axis linkage” diffusion pattern with strong coupling to urban road networks, showing gradient attenuation in service coverage efficiency along transportation arteries, fewer suburban service gaps, and more gradual accessibility reductions. Location entropy analysis further indicates that charging station deployment shows significant capital-oriented tendencies, with certain areas exhibiting paradoxical “excess facilities” phenomena, while gas station distribution aligns more closely with road network topology and transportation demand dynamics. Furthermore, the layout characteristics of public charging stations feature a more complex and diverse range of land use types, while traditional gas stations have a strong dependence on industrial land. This research elucidates the spatial distribution patterns of emerging and legacy energy infrastructure in the survey regions, providing critical empirical evidence for optimising energy infrastructure allocation and facilitating coordinated transportation system transitions. The findings also offer practical insights for the construction of energy supply facilities in urban development frameworks, holding substantial reference value for achieving sustainable urban spatial governance. Full article

Currently, the layout planning of power exchange facilities in urban areas is not perfect, which cannot effectively meet the power exchange demand of urban operating vehicles and restricts the operation of urban operating vehicles. The article proposes a vehicle power exchange demand-oriented power exchange station siting planning scheme to meet the rapid replenishment demand of operating vehicles in urban areas. The spatial and temporal distribution of power exchange demand is predicted by considering the operation law, driving law, and charging decision of drivers; the candidate sites of power exchange stations are determined based on the data of power exchange demand; the optimization model of the site selection of power exchange stations with the lowest loss time of vehicle power exchange and the lowest cost of the planning and construction of power exchange stations is established and solved by using the joint algorithm of MLP-NSGA-II; and the optimization model is compared with the traditional genetic algorithm (GA) and the Density Peak. The results show that the MLP-NSGA-II joint algorithm has the lowest cost of optimizing the location of switching stations. The results show that the MLP-NSGA-II algorithm improves the convergence efficiency by about 30.23%, and the service coverage of the optimal solution reaches 94.30%; the service utilization rate is 85.35%, which is 6.25% and 19.69% higher than that of the GA and DPC, respectively. The research content of the article can provide a design basis for the future configuration of the number and location of power exchange stations in urban areas. Full article

With the evolution of synchrotron light sources to fourth generation (diffraction-limited storage rings), the brilliance is increased by several orders of magnitude compared to third generation facilities. For example, the Swiss Light Source (SLS) has been upgraded to SLS 2.0, promising a horizontal emittance reduced by a factor of 40, and a brilliance up to two orders of magnitude (three at higher energies). A key challenge arising from the increased flux is the heightened accumulated dose in silicon sensors, which leads to a significant increase in radiation damage. This translates into an increase of both noise and dark current, as well as a reduction in the dynamic range for long exposure times, thus affecting the performance of the detector, in particular, for charge-integrating detectors. We have designed sensors with a 4 × 4 mm² pixel array featuring 16 design variations of 25 µm pitch pixels with different implant and metal sizes and tested them bump-bonded to MÖNCH 0.3, a charge integrating hybrid pixel detector readout ASIC. Following a first assessment of the functionality and performance of the different pixel designs, the assembly has been irradiated with X-rays. The variation in the tested parameters was characterized at different accumulated doses up to 100 kGy at the sensor entrance window side. The annealing dynamics at room temperature have also been measured. The results show that the default pixel design is currently not optimal and can benefit from layout changes (reduction in the inter-pixel gap area with full metal coverage of the implant). Further studies on the metal coverage over large implants could be conducted. The layout changes are, however, not sufficient for future full-sized sensors, requiring improved radiation hardness and long-term stability, and additional strategies such as focusing on detector cooling and changes in sensor technologies would be required. Full article

In order to improve the operational efficiency of a shared electric vehicle (SEV) system, this paper conducts integrated planning research from the aspects of locating and sizing SEV outlets, locating and sizing charging facilities, and operation scheduling by considering the carbon emission reduction and its benefits. Firstly, a multi-objective locating model was constructed with the optimization objectives of minimum outlet construction cost and user travel time cost and minimum carbon emissions from outlet construction and vehicle routing. Secondly, a charging demand simulation predictive model framework was designed. Finally, an SEV scheduling model with maximal operating income and minimal scheduling costs as optimization objectives was constructed considering the benefits of carbon emission reduction. By applying these models to the Chicago Sketch network and using a genetic algorithm to solve the models, it is concluded that the optimal outlet location solution considering carbon emission reduction will increase the outlet construction cost and user travel time cost. When the user loss rate is 40%, the initial number of vehicles in each outlet can make the operator’s daily income reach the maximum. The number of charging piles in each outlet is optimally configured according to 55% of the highest charging demand. Scheduling can make the distribution of charging demand more uniform and reduces the maximum charging demand by about 36.8% and the total number of charging piles by about 24.0%, at the same time, increases the average time utilization rate of charging piles at all outlets by about 15.6% and the user satisfaction rate by about 8.6%. Although scheduling increases the scheduling cost by about 3.8%, it can increase the total daily revenue of operators by 6.5%. Carbon reduction benefits can increase the total daily revenue of operators by 0.7%. Full article

With the development of new energy technologies, fuel buses with internal combustion engines are gradually being replaced by electric buses. In order to save on system costs, an optimization model is proposed to jointly design the bus service and charging facilities. Considering the complexity of the original problem, the problem is decomposed into two subproblems, i.e., bus service design and charging facilities design. The bus service design is solved by a genetic algorithm with an embedded enumeration method. The non-linear charging facilities design problem is firstly converted to a linear problem and then solved by existing solving software. Sensitivity analysis of parameters such as passenger flow demand, charging power, and bus stopping time is also conducted to reveal their impact on the optimization of electric bus lines. The results indicate that, compared to the commonly used depot charging strategy, the proposed method reduces the operating cost per unit hour from RMB 16,378.30 to RMB 8677.99, a 47% reduction, and decreases the system cost from RMB 36,386.30 to RMB 29,637.99, an 18.5% reduction. This study addresses the charging and operation problem of electric bus lines. By considering charging vehicles while in operation, a joint optimization model for the operation of electric bus lines and the layout of charging facilities is established. An algorithm based on the combination of a genetic algorithm and enumeration method is designed, combined with a linear programming solver to solve the problem. Full article

With the expansion of Chinese university campuses, electric bikes (E-bikes) have become the most sustainable and effective commuting option because they are a flexible and energy-saving travel mode. Consequently, campus E-bike charging piles have become one of the most essential public service facilities on campuses. However, since most Chinese campuses are closed and independent, the principles of urban public service facilities cannot be simply applied to the layout and use of campus charging facilities. Thus, this study focuses on Zijingang Campus at Zhejiang University, and proposes an optimization strategy for the spatial and temporal layout of E-bike charging piles on the campus. First, trip chain demand models are constructed to examine the travel patterns of E-bike users on campus and the demands for charging areas and time. Second, a space location model is constructed to locate the charging piles in areas with high demand. Finally, according to the charging times of different users, user charging time is integrated into the strategy. This study enhances the layout and utilization system of campus E-bike charging facilities by considering both temporal and spatial dimensions. Overall, this study contributes to the advancement of sustainable transportation infrastructure planning on a campus-wide scale, offering theoretical insights for the design and utilization of functional facilities in large-scale, semi-enclosed environments (e.g., university campuses). Full article

Volumetric-based pricing for irrigation water was introduced as part of a comprehensive reform of agricultural water prices in China. However, operational deficiencies and farmers’ lack of willingness to adopt the volumetric pricing policy (VPP) hinder the coordinated implementation of the reform. To address these practical challenges, we employed a binary logistic regression model to analyse farmers’ acceptance of the VPP for agricultural irrigation water usage in Suqian City, Jiangsu Province. A variable set was formed by selecting potential variables from four types of influencing factors: the subject (water users), the object (water supply departments), natural condition factors, and social condition factors. Our results revealed seven factors that determine whether farmers accept the VPP: irrigation water measurement at the water inlet of a lateral canal, the irrigation water-saving rewards scale, enforcement efforts of charging by volume, the irrigation water source type, the use of agricultural water-saving for trade, financial investment in water-saving technology, and the level of irrigation water pricing. We determined the degree of influence of the seven determining factors, among which the irrigation water-saving rewards scale and enforcement efforts of charging by volume most influence farmers’ decisions on the VPP for irrigation water. The results of this study can be used as a reference for innovation of the agricultural water-saving system in Suqian City, optimisation of an accurate fiscal subsidy scale, quantification of irrigation water rights, optimisation of the measurement facility layout, and effective implementation of agricultural water rights trading. More broadly, this study provides a valuable reference for solving the difficulties faced in the comprehensive reform of agricultural water pricing in China, which includes irrigation water pricing mechanisms, management systems, subsidy mechanisms, and water-saving incentive measures. Full article

Amid the global shift towards sustainable development, this study addresses the burgeoning electric vehicle (EV) market and its infrastructure challenges, particularly the lag in public charging facility development. Focusing on Wuhan, it utilizes big data to analyze EV charging behavior’s spatiotemporal aspects and the urban environment’s influence on charging efficiency. Employing a random forest regression and multiscale geographically weighted regression (MGWR), the research elucidates the nonlinear interaction between urban infrastructure and charging station usage. Key findings include (1) a direct correlation between EV charging patterns and urban temporal factors, with notable price elasticity; (2) the predominant influence of commuting distance, supplemented by the availability of fast-charging options; and (3) a strategic proposal for increasing slow-charging facilities at key urban locations to balance operational costs and user demand. The study combines spatial analysis and charging behavior to recommend enhancements in public EV charging infrastructure layouts. Full article

Electric vehicles invented for environmental sustainability are prone to adverse impacts on environmental sustainability due to the location and construction of their charging facilities. In this article, an artificial Physarum polycephalum colony is proposed to solve the novel challenging problem. First, the electric location-routing problem is established as a multi-objective network panning model with electric constraints to provide the optimal charging infrastructure layout, electric vehicle maintenance costs, and traffic conditions. The electric facility location problem and vehicle routing problem are integrated by integer programming, which considers the total distance, total time, total cost, total number of electric vehicles, and order fill rate. Second, an artificial Physarum polycephalum colony is introduced to solve the complex electric location-routing problem and includes the two basic operations of expansion and contraction. In the expansion operation, the optimal parent individuals will generate more offspring individuals, so as to expand the population size. In the contraction operation, only individuals with high fitness will be selected to survive through a merge sorting algorithm, resulting in a decrease in population size to the initial value. Through the iterative computing of the two main operations, the proposed artificial Physarum polycephalum colony can finally find the optimal solution to the objective function. Third, a benchmark test is designed for the electric location-routing problem by extracting the real road network from Tokyo, and the experimental results prove the effectiveness and applicability of this work. Full article

This study considers the spatial analysis and evaluation layout of electric vehicle charging infrastructures, taking the central urban area of Chongqing as an example. Mathematical model analysis, ArcGIS spatial analysis, field investigation, questionnaire measurement, and hierarchical analysis methods are utilized to discuss the current distribution characteristics and supply–demand matching of the electric vehicle charging infrastructure in this region. The resulting data can provide references for the optimal layout of charging infrastructure. The main conclusions of this study are as follows: (1) The configuration and demand of charging infrastructure in the central urban area of Chongqing have obvious spatial differentiation and show strong centrality. (2) It is a common phenomenon that the charging infrastructure in the central urban area of Chongqing is in short supply, and it is pressing that a new charging infrastructure be built. (3) In the process of construction and operation of charging infrastructure, various factors, such as economy and traffic, should be comprehensively considered; at the same time, incidents of inefficient operation, such as being crowded out by nonelectric vehicles and unmaintained facility failure, should be minimized. Full article

A compact microwave ECR ion source with low operating power was tested and commissioned for the ion injector line in the multipurpose low-energy ELASR storage ring facility at King Abdulaziz City for Science and Technology (KACST) in Riyadh. The compact ECR ion source can deliver singly charged ions with an energy of up to 50 keV and a beam current of up to 50 μA or up to 500 µA with a larger extraction aperture. The plasma in the ECR chamber is driven by a simple transmitter antenna, making the overall size of the ion source only 6 cm in diameter, which is relatively small when compared with other ECR systems. Additionally, the source operates without a high-voltage platform, which significantly reduces the overall footprint and simplifies the system operation. In this paper, the mechanical design and modeling of the ECR ion source are introduced, and the layout of the first part of the beam line is presented along with the numerical simulation results. In addition, the experimental results obtained for the first generated ion beam and commissioning of the ECR ion source are introduced and discussed. Full article

At present, the new energy vehicle industry is developing rapidly, but the relative lag in the development of its supporting infrastructure, especially charging stations, has become a bottleneck that restricts the development of the electric vehicle industry. In this paper, we propose a model for constructing a network of new energy vehicle charging facilities based on complex network theory and analyze the operation and the rationality of the layout of the new energy vehicle (NEV) charging stations in Wuhan and Hangzhou, respectively. The results show that the current layout of new energy vehicle charging stations in the city is relatively reasonable, but the allocation of charging pile resources is unreasonable. Our results of the virtual charging station network constructed by adding new charging station nodes show that the change in network structure helps to enhance the performance of the charging station system. Full article

The energy consumption of electric vehicles is closely related to the problems of charging station planning and vehicle route optimization. However, due to various factors, such as vehicle performance, driving habits and environmental conditions, it is difficult to estimate vehicle energy consumption accurately. In this work, a physical and data-driven fusion model was designed for electric bus energy consumption estimation. The basic energy consumption of the electric bus was modeled by a simplified physical model. The effects of rolling drag, brake consumption and air-conditioning consumption are considered in the model. Taking into account the fluctuation in energy consumption caused by multiple factors, a CatBoost decision tree model was constructed. Finally, a fusion model was built. Based on the analysis of electric bus data on the big data platform, the performance of the energy consumption model was verified. The results show that the model has high accuracy with an average relative error of 6.1%. The fusion model provides a powerful tool for the optimization of the energy consumption of electric buses, vehicle scheduling and the rational layout of charging facilities. Full article

In order to play the important role of electric vehicles to promote the realization of the 3060 double carbon target, electric vehicles have seen explosive growth. However, due to the tight symmetry between the number and distribution of electric vehicles and their corresponding charging facilities, the layout of charging facilities has higher requirements. This paper collects travel data in the form of a traffic travel questionnaire for electric vehicle users. Based on the vehicle parking demand model of the queuing theory and Monte Carlo simulation, the paper gives the number of stopping vehicles and the time of vehicles stopping in different places such as residential areas, workplaces, supermarket parking and roadside. In addition, based on the Bass prediction model, the main parameters are modeled in the model, and the price correction coefficient is introduced. The improved Bass model is used to predict the growth trend of electric vehicles in different regions in different years and in different incentive sites. By predicting the ownership of urban electric vehicles and accurately grasping the distribution and operation of electric vehicles, this paper can provide guidance and suggestions for the planning and construction of charging facilities in different regions, effectively reduce the investment cost of charging facilities and guide local governments to formulate reasonable planning schemes. Full article

With the development of electronic infrastructures and communication technologies and protocols, electric grids have evolved towards the concept of Smart Grids, which enable the communication of the different agents involved in their operation, thus notably increasing their efficiency. In this context, microgrids and nanogrids have emerged as invaluable frameworks for optimal integration of renewable sources, electric mobility, energy storage facilities and demand response programs. This paper discusses a DC isolated nanogrid layout for the integration of renewable generators, battery energy storage, demand response activities and electric vehicle charging infrastructures. Moreover, a stochastic optimal scheduling tool is developed for the studied nanogrid, suitable for operators integrated into local service entities along with the energy retailer. A stochastic model is developed for fast charging stations in particular. A case study serves to validate the developed tool and analyze the economical and operational implications of demand response programs and charging infrastructures. Results evidence the importance of demand response initiatives in the economic profit of the retailer. Full article