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We analyze the effect of four determinants of electric vehicle diffusion in China for a panel of 31 regions for the period 2010–2016. We analyze diffusion of four different electric vehicle types, namely battery electric cars and buses as well as plug-in hybrid electric cars and buses. System GMM panel estimation results show that total monetary subsidies have a positive effect only on the diffusion of battery electric cars. A closer look reveals that subsidies provided by regional governments are decisive for all types of vehicles but the subsidy provided by the central government and its degression over time dilute the overall effect of subsidies and is partly detrimental. Non-monetary ownership policies, such as license-plate lotteries, show a positive effect only for battery electric cars. Availability of public charging infrastructure increases diffusion of all vehicle types. Charging points are relevant for cars, while charging stations are especially decisive for the diffusion of electric buses. Using local environmental conditions as a novel determinant for the diffusion of electric vehicles reveals that the local air pollution influences the diffusion of buses, but not of cars.

In the pursuit of sustainable urban transportation, electric buses (EBs) have emerged as a promising solution to reduce emissions. The increasing adoption of EBs highlights the critical need for accurate energy consumption prediction. This study presents a comprehensive methodology integrating traction modeling with a Light Gradient Boosting Machine (LightGBM)-based trip-level energy consumption prediction framework to address challenges in power system efficiency and passenger load estimation. The proposed approach combines transmission system efficiency evaluation with dynamic passenger load estimation, incorporating temporal, weather, and driving pattern features. The LightGBM model, hyperparameter tuned through Bayesian Optimization (BO), achieved a mean absolute percentage error (MAPE) of 3.92% and root mean square error (RMSE) of 1.398 kWh, outperforming traditional methods. SHAP analysis revealed crucial feature impacts on trip-level energy consumption predictions, providing valuable insights for operational optimization. The model’s computational efficiency makes it suitable for real-time IoT applications while establishing precise parameters for future optimization strategies, contributing to more sustainable urban transit systems.

China and India together have more than one third of the world population and are two emerging economic giants of the developing world now experiencing rapid economic growth, urbanization, and motorization. The urban transportation sector is a major source of carbon dioxide (CO 2 ) emissions in China and India. The goal of this study is to analyze the characteristics and factors of CO 2 emissions produced by commuters in Chinese and Indian cities and thus to identify strategies for reducing transportation CO 2 emissions and mitigating global climate change. Xi’an in China and Bangalore in India were chosen as two case study cities for their representativeness of major cities in China and India. The trends of CO 2 emissions produced by major traffic modes (electric motors, buses, and cars) in major cities of China and India were predicted and analyzed. The spatial distributions of CO 2 emissions produced by commuters in both cities were assessed using spatial analysis module in ArcGIS (Geographic Information System) software. Tobit models were then developed to investigate the impact factors of the emissions. The study has several findings. Firstly, in both cities, the increase of vehicle occupancy could reduce commuting CO 2 emissions by 20 to 50 % or conversely, if vehicle occupancy reduces, an increase by 33.33 to 66.67 %. It is estimated that, with the current increasing speed of CO 2 emissions in Xi’an, the total CO 2 emissions from electric motors, buses, and cars in major cities of China and India will be increased from 135 × 10 6  t in 2012 to 961 × 10 6  t in 2030, accounting for 0.37 to 2.67 % of the total global CO 2 emissions of 2013, which is significant for global climate change. Secondly, households and individuals in the outer areas of both cities produce higher emissions than those in the inner areas. Thirdly, the lower emissions in Xi’an are due to the higher density and more compact urban pattern, shorter commuting distances, higher transit shares, and more clean energy vehicles. The more dispersed and extensive urban sprawl and the prevalence of two-wheeler motorbikes (two-wheeler motorbike is abbreviated as “two-wheeler” in the following sections) fueled by gasoline cause higher emissions in Bangalore. Fourthly, car availability, higher household income, living outside the 2nd or Outer Ring Road, distance from the bus stop, and working in the foreign companies in Bangalore are significant and positive factors of commuting CO 2 emissions. Fifthly, “70-20” and “50-20” (this means that generally, 20 % of commuters and households produce 70 % of total emissions in Xi’an and 20 % of commuters and households produce 50 % of total emissions in Bangalore) emission patterns exist in Xi’an and Bangalore, respectively. Several strategies have been proposed to reduce urban CO 2 emissions produced by commuters and further to mitigate global climate change. Firstly, in the early stage of fast urbanization, enough monetary and land investment should be ensured to develop rail transit or rapid bus routes from outer areas to inner areas in the cities to avoid high dependency on cars, thus to implement the transit-oriented development (TOD), which is the key for Chinese and Indian cities to mitigate the impact on global climate change caused by CO 2 emissions. Secondly, in Bangalore, it is necessary to improve public transit service and increase the bus stop coverage combined with car demand controls along the ring roads, in the outer areas, and in the industry areas where Indian foreign companies and the governments are located. Thirdly, Indian should put more efforts to provide alternative cleaner transport modes while China should put more efforts to reduce CO 2 emissions from high emitters.

Climate change is one of the problems that affects the climate, natural disasters, and lives, economies, and industries around the world. Since the main cause is the combustion of fossil fuels, the transportation sector is a significant factor in causing these problems. Therefore, many countries, including Thailand, have policies to promote the increased use of electric vehicles. However, past measures have focused mostly on promoting the use of personal electric vehicles. For public transportation, buses are a major part of creating pollution and the problems of particulate matter with a diameter of less than 2.5-micron (PM 2.5), which is another major problem in Thailand because Thailand has many old buses. However, pushing transport operators to switch from internal combustion engine (ICE) buses to electric buses requires a large budget. Therefore, the conversion of old ICE buses into electric buses is one approach that can help promote the use of electric buses to become more possible. Another issue that makes transport operators afraid to switch from ICE buses to electric buses is the shortage of maintenance personnel. Therefore, this action research focuses on creating knowledge and practical skills related to electric vehicle modification and maintenance in the education sector. From the results of this practical research, the researcher was able to modify the old ICE bus into an electric bus and passed the test according to the research objectives.

To solve the voltage stability problem of electric vehicles connected to the distribution network in the limit state, a reactive power compensation strategy based on the holomorphic embedding method and electrical distance is proposed. Firstly, the load model of the electric vehicle charging station is constructed, and the limit of the charging power of the electric vehicle connected to a certain bus is obtained. Then, the power flow embedding equation of the power system is constructed by the holomorphic embedding method, and the analytical expression of the voltage rational function is introduced based on the Padé approximation algorithm. The voltage collapse point is solved by the distribution of zeros and poles of the rational function. Then, a method of reactive power and voltage control partition based on electrical distance is proposed. According to the principle of weak regional coupling and strong interval coupling, the power system is divided into several regions by spectral clustering and a k-means clustering algorithm. The order of the voltage stability margin value s is obtained by connecting the limit charging power to each bus of the power system. In this paper, the reactive power compensation strategy proposes to add reactive power compensation devices to the buses with the weakest voltage stability margin in different zones. Finally, compared with other reactive power compensation strategies 1 and 2, the reactive power compensation strategy provided in this paper is increased by 1.626121813 and 1.160494345 times, respectively. The superiority of this method is verified by simulation.

This work provides a new solution for high-power quality traction power systems. The rapid development of electrified railways not only promotes economic development, but also seriously restricts the improvement of electric locomotive operation performance due to power quality problems, such as second harmonic distortion and negative sequence in the power supply system. In view of the shortcomings of the traditional in-phase power supply system in DC bus voltage stability control, a new in-phase power supply topology based on a back-to-back H-bridge power supply unit is proposed in this study. By establishing the iterative analysis model of the rectifier side double closed-loop control system, the internal correlation mechanism between the DC bus voltage second harmonic fluctuation and the grid side current harmonic is deeply revealed. On this basis, a rectifier-side disturbance compensation control strategy with a second harmonic suppression function is designed. Through real-time detection and compensation of second harmonic components, the active stability control of DC bus voltage is realized. The simulation model of the new cophase power supply system based on the experimental platform shows that the strategy can reduce the ripple coefficient of the DC bus voltage and the total harmonic distortion of the grid side current, which effectively verifies the superiority of the second harmonic suppression strategy in improving the power quality of the cophase power supply system. This work provides a new solution for a high-power quality traction power system.

This paper addresses the critical challenge of optimizing power flow in multi-area power systems while maintaining information privacy and decentralized control. The main objective is to develop a novel decentralized stochastic recursive gradient (DSRG) method for solving the optimal power flow (OPF) problem in a fully decentralized manner. Unlike traditional centralized approaches, which require extensive data sharing and centralized control, the DSRG method ensures that each area within the power system can make independent decisions based on local information while still achieving global optimization. Numerical simulations are conducted using MATLAB (Version 24.1.0.2603908) to evaluate the performance of the DSRG method on a 3-area, 9-bus test system. The results demonstrate that the DSRG method converges significantly faster than other decentralized OPF methods, reducing the overall computation time while maintaining cost efficiency and system stability. These findings highlight the DSRG method’s potential to significantly enhance the efficiency and scalability of decentralized OPF in modern power systems.

In a high-voltage direct current (HVDC) transmission system, commutation failure at the receiving end may lead to transient overvoltage at the sending end converter bus of the weak alterative current (AC) system. Firstly, the principle calculation method of overvoltage generation at the sending end after commutation failure is analyzed. Combined with the output characteristics of the hydroelectric excitation system, a coordinated control strategy for hydroelectric and DC systems is proposed. Since the voltage and current values at the DC outlet of the rectifier side change first after a fault occurs at the receiving end, the relationship equation between DC voltage and AC bus voltage is derived and it is used as an input signal to construct additional excitation control for hydropower stations. The proposed strategy is verified by establishing a simulation hydrogen–wind–solar model bundled via a DC sending system in PSCAD/EMTDC. The simulation results illustrate that the transient overvoltage suppression rates are all more than 35%, and the maximum is 38.53%. The proposed strategy can reduce the overvoltage by 0.126 p.u. compared with the International Council on Large Electric Systems (CIGRE) standard control strategy.

An increasing number of cities are transitioning from fossil fuel-powered buses for public transport to battery electric buses, but there is still much confusion about the economic evaluation of the electrification of buses, especially in terms of the carbon asset value for carbon emissions reduction in this transition. Taking Beijing as the example, this paper studies the economic value of the transition of public buses from fossil fuel-powered buses to battery electric buses from the perspective of carbon asset theory, and mainly focuses the analysis on direct carbon emissions. First, the theory and methodology of carbon asset evaluation are introduced for the transition from fossil fuel-powered buses to battery electric buses. Second, the internal determinants of the carbon assets for the transition from fossil fuel-powered buses to battery electric buses are studied. Third, the distinct impacts of the determinants of the carbon assets of the transition from fossil fuel-powered buses to battery electric buses are analysed. The results indicate that (1) the transition from fossil fuel-powered buses to battery electric buses has a carbon asset value; (2) the carbon asset value of the transition from fossil fuel-powered buses to battery electric buses is determined by the distance-specific CO2 emissions of fossil fuel-powered buses, the carbon price and the annual driving distances of the buses as well as the discounted rate of the carbon assets for buses and the termination time of the fossil fuel-powered or battery electric buses; and (3) the carbon assets contribute to the economic value of the transition from fossil fuel-powered buses to battery electric buses. This paper provides academic support for the economic evaluation of the transition from fossil fuel-powered buses to battery electric buses in a low-carbon society.

Optimal power flow is one of the fundamental optimal operation problems for power systems. With the increasing scale of solar energy integrated into power systems, the uncertainty of solar power brings intractable challenges to the power system operation. The multi-objective optimal power flow (MOOPF) considering the solar energy becomes a hotspot issue. In this study, a MOOPF model considering the uncertainty of solar power is proposed. Both scenarios of overestimation and underestimation of solar power are modeled and penalized in the form of operating cost. In order to solve this multi-objective optimization model effectively, this study proposes a clustering-based multi-objective differential evolution (CMODE) which is based on the main features: (1) extending DE into multi-objective algorithm, (2) introducing the feasible solution priority technique to deal with different constraints, and (3) combining the feasible solution priority technique and the merged hierarchical clustering method to determine the optimal Pareto frontier. The simulation outcomes on two cases based on the IEEE 57-bus system verify the reliability and superiority of CMODE over other peer methods in addressing the MOOPF.