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Travel decisions during the COVID-19 pandemic might be substantially influenced by destination-based attributes, in particular, health safety measures at airports. In the current study, we aimed to assess the effects of the perceived importance of safety measures at the Sharm El Sheikh airport on the intention of international passengers to revisit the destination, which might reflect their behavioral control for traveling to other tourism destinations. A total of 954 international travelers were asked to fill out a survey to reveal their travel risk perceptions, the importance of airport safety measures, and their future intentions to revisit the destination, and the data were integrated in an SEM model. The results showed that passengers with low-risk perceptions and highly perceived importance of logistic and sanitization procedures, as well as traveler- and staff-related safety measures, were more likely to exhibit greater intentions to revisit the city and lower intentions to cancel or change future travel plans to other touristic regions. Health safety at airports should be stressed in future strategic plans by governmental authorities and stakeholder activities to mitigate the psychological barriers of tourists.

A higher penetration of EVs may pose several challenges to the power systems, including reliability issues. To analyze the impact of EVs on the reliability of power systems, a detailed EV charging infrastructure is considered in this study. All possible charging locations (home, workplace, public locations, and commercial fast chargers) and different charging levels (level 1, level 2, and DC fast charging) are considered, and seven charging infrastructures are determined first. Then, the reliability impact of each charging infrastructure is determined using the two widely used reliability indices, i.e., the loss of load expectation (LOLE) and the loss of energy expectation (LOEE). The impact of mixed charging infrastructure portfolios is also analyzed by considering two different cases, which included the equal share of all charging infrastructure and charging infrastructure share based on consumer preferences. The performance is analyzed on a well-known reliability test system (Roy Billinton Test System) and different penetration levels of EVs are considered in each case. Test results have shown that fast-charging stations have the worst reliability impact. In addition, it was also observed that mixed charging portfolios have lower reliability impacts despite having a fair share of fast-charging stations.

The unpredictable nature of the loads and non-linearity of the components of microgrid systems make optimal scheduling more complex. In this paper, a deterministic optimal load-scheduling problem is developed for microgrids operating in both islanding and grid-connected mode under different energy scenarios. Various cases are considered in this research, based on the interaction and dynamic behavior of the microgrid, considering electric vehicles (EVs) in the scenario. The aim of this research is to minimize the overall cost of microgrid operations. The concept of dynamic pricing has also been introduced in order to optimize the energy cost for the consumers. For ensuring the stability of the microgrids, a load variance index has been considered, and the fuzzy-based approach has been used for cost and load variance minimization to reduce the operation cost without compromising the stability of the microgrid. The grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations of EVs are integrated into the microgrid, which would help in valley filling and peak shaving of the loads during the off-peak and peak hours, respectively. In order to solve the proposed complex combinatorial optimization problem, elephant herding optimization (EHO) is modified and implemented. The performance of the proposed improved EHO (IEHO) is first tested on the latest CEC test functions. The results obtained by IEHO after 100 different trials are compared with the latest published methods and are found to be better based on the average value and the standard deviation for different CEC test functions. In addition, the simulation results obtained by particle swarm optimization (PSO), EHO, and proposed IEHO on a microgrid test system for different scenarios with all cases reveal that the proposed model with a mix of energy resources in the dynamic load dispatch environment bring the maximum benefits of microgrid systems. Furthermore, the results obtained from the simulation verifies that if free trade of power is allowed between the microgrids and the main grid, the process of power generation can be more economical, and further introduction of dynamic pricing into the scenario proves to be even cheaper. The implementation of the G2V and V2G operations of EVs operations in the proposed scenario not only helped in cost minimization but also helped in stabilizing the grid.

Evaluation of the reliability of the components of electric vehicles (EVs) has been studied by international research centers, industry, and original equipment manufacturers over the last few years. Li-ion batteries are the main sensitive component of an EV’s E-power train. In other words, the Li-ion batteries for electromobility applications are one of the main components of an EV, which should be reliable and safe over the operational lifetime of the EV. Thus, investigating how to assess the reliability of the Li-ion battery has been a highly recommended task in most European projects. Moreover, with the increase in the number of new EVs made by European car companies, there has been a competition for market acquisition by these companies to win over customers and gain more market share. This article presents a comprehensive overview of the evaluation of the reliability of Li-ion batteries from practical and technical perspectives. Moreover, a case study for assessing reliability from practical and technical perspectives has been investigated.

Smart mobility systems offers solutions for traffic congestion, transport management, emergency, and road safety. However, the success of smart mobility lies in the availability of intelligent transportation infrastructure. This paper studied smart mobility systems in three Asia-Pacific countries (South Korea, Singapore, and Japan) to highlight the major strategies leading their successful journey to become smart cities for aspiring countries, such as the Kingdom of Saudi Arabia (KSA), to emulate. A robust framework for evaluating smart mobility systems in the three countries and Saudi Arabia was developed based on the indicators derived from the smart mobility ecosystem and three major types of transport services (private, public, and emergency). Sixty indicators of smart mobility systems were identified through a rigorous search of the literature and other secondary sources. Robots, drones, IoT, 5G, hyperloop tunnels, and self-driving technologies formed part of the indicators in those countries. The study reveals that the three Asia-Pacific countries are moving head-to-head in terms of smart mobility development. Saudi Arabia can join these smarter countries through inclusive development, standardization, and policy-driven strategies with clear commitments to public, private, and research collaborations in the development of its smart mobility ecosystem. Moreover, cybersecurity must be taken seriously because most of the smart mobility systems use wireless and IoT technologies, which may be vulnerable to hacking, and thus impact system safety. In addition, the smart mobility system should include data analytics, machine learning, and artificial intelligence in developing and monitoring the evaluation in terms of user experience and future adaptability.

Due to the recent advancements in the manufacturing process of solar photovoltaics (PVs) and electronic converters, solar PVs has emerged as a viable investment option for energy trading. However, distribution system with large-scale integration of rooftop PVs, would be subjected to voltage upper limit violations, unless properly controlled. Most of the traditional solutions introduced to address this problem do not ensure fairness amongst the on-line energy sources. In addition, other schemes assume the presence of communication linkages between these energy sources. This paper proposes a control scheme to mitigate the over-voltages in the distribution system without any communication between the distributed energy sources. The proposed approach is based on artificial neural networks that can utilize two locally obtainable inputs, namely, the nodal voltage and node voltage sensitivity and control the PV power. The controller is trained using extensive data generated for various loading conditions to include daily load variations. The control scheme was implemented and tested on a 12.47 kV feeder with 85 households connected on the 220 V distribution system. The results demonstrate the fair control of all the rooftop solar PVs mounted on various houses to ensure the system voltage are maintained within the allowed limits as defined by the ANSI C84.1-2016 standard. Furthermore, to verify the robustness of the proposed PV controller, it is tested during cloudy weather condition and the impact of integration of electric vehicles on the proposed controller is also analyzed. The results prove the efficacy of the proposed controller.

Part of the Hang-Tai High-speed Railway (Hangzhou via Shaoxing to Taizhou in Zhejiang Provence) in China passes through the diatomaceous earth area, which is the first time in the history of Chinese high-speed railway construction. This type of soil has significant compressibility, swelling and disintegration. Diatomaceous earth also shows a sharp reduction in strength when exposed to water, which severely impacts the safety of the project. However, no studies have been carried out on the engineering practice of building a high-speed railway in the diatomaceous earth area in China. Moreover, there is limited experience in the construction of ballastless track through the diatomaceous earth area. In order to ensure the stability of the high-speed railway subgrade in diatomaceous earth area, and considering the high level of precipitation in the location of this railway, a kind of waterproof and drainage subgrade (WDS) is proposed to reduce the influence of precipitation on the strength of the diatomaceous earth foundation. The subgrade has a flexible waterproof and drainage layer (WDL) inside, which consists of capillary waterproof and drainage plates and medium-coarse sand. In the present study, field tests including immersion tests and excitation test are carried out on a subgrade test section to verify the subgrade structure. The tests mainly focus on construction technology, waterproof performance and dynamic characteristics. The studies show that the subgrade bed with the WDL can effectively avoid the diatomaceous earth foundation from rainfall interference and maintain the long-term stability of the subgrade. The flexible WDL in WDS has a significant energy dissipation effect in comparison with the traditional subgrade (TS) filler and can play a key role in vibration damping, promoting the attenuation of dynamic response in the downward and cross-sectional directions within the subgrade. The dynamic response of the WDS attenuates along the depth. In comparison with the existing high-speed railway subgrade measured data, its dynamic response attenuation coefficient is within acceptable limits. The laying of the WDL does not change the subgrade dynamic characteristics transfer law. The proposed structure meets the requirements of ballastless track construction for high-speed railways, and the WDL can be used in the design of high-speed railways for enhanced drainage protection in diatomaceous soil areas or other special soil areas.

DC-DC converters play a crucial role in recent and advanced applications, enabling efficient power conversion and management for renewable energy systems, electric vehicles, portable devices, and advanced communication systems. In line with this, the objective of this paper is to introduce a new DC-DC configuration based on the Cuk converter named as Mahafzah converter, which utilizes a coupling capacitor with a lower rated voltage. The paper aims to demonstrate the effectiveness of the proposed converter in terms of improved efficiency, reduced size, and reduced semiconductor device currents compared to the conventional Cuk converter. The proposed configuration comprises the same components as the Cuk converter, but in a different arrangement, without any additional elements. The main advantage of the proposed converter is using a coupling capacitor with a much lower rated voltage than the Cuk converter, resulting in a smaller capacitor size, reduced printed circuit board (PCB) size, and manufacturing cost. Additionally, the proposed converter reduces the currents of the semiconductor devices compared to those in the Cuk converter. To demonstrate its effectiveness, the converter is operated under continuous current mode (CCM) with a constant duty cycle and switching frequency. The study provides an in-depth discussion of the various operating modes by making use of equations relating to currents, voltages, duty cycles, and voltage gains. It also provides detailed illustrations of the limits between CCM and discontinuous current mode (DCM). The effectiveness of the proposed converter is demonstrated through a design example with operating parameters of 1 kW, 200 V/−300 V, and 20 kHz. Additionally, a low voltage–low power prototype (12/−18 V, 3.24 W, 20 kHz) is established to verify the operation of the proposed converter. Simulation and experimental verification of the proposed configuration achieved the desired results to improve efficiency and reduce the rate. The results clearly indicate that the efficiency of the proposed converter surpasses that of the conventional Cuk converter under identical operating conditions, reaching approximately 88% at rated load conditions.