Charging Facilities Research Articles

Exploring the potential of sharing private charging posts: A data-driven micro-simulation approach

The lack of charging infrastructure has been one of the main barriers to the uptake of electric vehicles (EVs), and sharing private charging facilities could be a promising solution. This paper explored the potential of private home charging post sharing (PHCPS) (specifically, the impact of PHCPS on the usage of EVs and public and private charging posts) in Beijing using a data-driven micro-simulation approach. In the simulation, EV users’ travel and charging behaviors were defined with empirical findings from a trajectory dataset collected from over 76,000 private EVs in January of 2018. We quantified the potential by comparing the results of simulations with and without PHCPS. In the baseline scenario, we found that PHCPS gave rise to 6.32 % increase in the proportion of parking events with accessible charging posts and 33.37 % decrease in the average electricity provided by a public charging post on a working day. The results suggest that PHCPS could provide more charging opportunities for private EV users and decrease private EV users’ dependence on public charging stations, revealing the great potential of promoting PHCPS in the EV charging market.

Research on Price Control Model for PPP Project of New Energy Vehicle Charging Facilities

Research on Price Control Model for PPP Project of New Energy Vehicle Charging Facilities

The role of trust in the implementation and uptake of COVID-19 response measures: a qualitative study of health professionals’ experiences in Tanzania

BackgroundEven though trust is placed at the central point in ensuring proper functioning of the health systems, studies remain scant on how it affects both the implementation and uptake of COVID-19 response measures in low- and middle-income countries such as Tanzania. This study, therefore, explored the role of trust in the implementation and uptake of recommended COVID-19 response measures including vaccines from the perspective of health professionals in Tanzania.MethodsThis cross-sectional qualitative study was implemented in four of Tanzania’s thirty-one regions. Qualitative data was collected through 26 in-depth interviews held with regional and district disease outbreak response teams, district cold chain co-ordinators and health facility in-charges. In addition, five focus group discussions and seven group interviews were conducted with healthcare workers from the lower-level health facilities. Thematic analysis was conducted and applied the trust constructs.ResultsInterpersonal trust and health system trust emerged as two major themes in the study. Interpersonal trust was reported to stem from lack of transparency that instigated fear, worries, and confusion regarding the implementation and uptake of the recommended response measures. The distrust was mainly between health professionals in health facilities and those assigned to isolation centres as well as between patients and community members. On the other hand, the health system trust was shaped by mixed feelings regarding COVID-19 vaccine national decisions, and conflicting messages from national officials, politicians and religious leaders on COVID-19 responses, safety, and effectiveness of the vaccines. Questions surrounding the short duration of clinical trials, indeterminate post-vaccination protection duration, impotence-linked beliefs, freemasonry notion and unclear vaccinated cards information are other reported contributory factors to mistrust in the health system. However, after a comprehensive health education and experience in COVID-19 vaccination administration most professionals affirmed the effectiveness of the vaccines in limiting infections and its severe consequences.ConclusionParticipants indicated limited trust at both interpersonal and health system levels aggravated by lack of transparency, unclear and conflicting messages on COVID-19 infections and response measures. Enforced transparency on pandemics alongside standardised messages from the reliable sources is crucial in enhancing trust in implementation and uptake of the recommended response measures.

Design and optimal energy management of a stand-alone PV/WT/Diesel/battery system with EV charging facility for Thar desert camp: a case study

ABSTRACT Due to different financial restrictions, extending the existing power grid to remote locations like desert camps is not practically possible, forcing the camp owner to utilize expensive and ecologically hazardous diesel generators (DiG). In this regard, renewable sources based hybrid microgrid could be a viable approach toward reliable and sustainable electrification of these desert camps. However, optimum designing and proper energy management of such a system can be a challenging task. In these terms, this study presents a novel model based on the multi-objective PSO (MOPSO) algorithm for optimal design and energy management of a hybrid microgrid employing solar photovoltaic (PV) and wind turbine (WT), battery, and DiG for electrification of Thar desert camp in Jaisalmer, India. To address techno-eco-environmental aspects, objectives such as Dump Energy (DE), Installation and Operation Cost (IOC), and Reduction of Pollutant Emission (RPE) are considered. The optimal configuration of PV, WT, battery, and DiG are determined based on the maximization of RPE and minimization of both DE and IOC. The proposed model is formulated taking into account the seasonal load variation of a typical camp and the stochastic behavior of renewable energy sources. Moreover, electric vehicles (EVs) charging facility for the tourists staying in these camps is also included while modeling the microgrid system. Furthermore, three distinct system configurations are carefully analyzed over a 10-year period based on technical, environmental and economic indicators. The optimum configuration obtained is the hybrid PV/WT/DiG/battery system with 62 kW PV, 76 kW WT, 350 kWh battery and a 117 kW DiG. According to simulation findings, this system has an operational cost of 323.7 × 104 $ and a pollutant emission of 2034.3 tons, which is 33.67% and 63.32% less than that of the DiG-only configuration, respectively. Moreover, as compared to PV/WT/DiG system, PV/WT/DiG/battery system can reduce dump energy by 81.40%, highlighting the necessity of battery for fully utilizing renewable energy. Overall, this analysis suggests that the utilization of renewable energy sources along with the battery is the optimal planning solution for the camp owner to maximize their potential benefits. Moreover, the proposed technique can be effectively used to optimally design hybrid renewable energy system for other remote locations.

Robust Operation Scheme of EV Charging Facility With Uncertain User Behavior

With the widespread of electric vehicles (EV), the necessity of installing EV charging facility has rapidly increased. Since operating EV charging facility are costly and complex, choosing a proper power operation scheme is critical in implementing a cost-effective charging service. Therefore, this paper proposes an efficient power operation scheme for EV charging facility by jointly analyzing not only monetary issues with various power rate policies and battery wear-out costs of the energy storage system (ESS) but also the uncertainty issues caused by EV users' behavior under different charging requirements. By considering the issues, this paper analyzes and formulates the problem with robust optimization techniques. By using the real-world EV operation datasets, the effectiveness of the proposed scheme is analyzed in terms of daily peak power and total cost. In addition, by applying the proposed scheme in an actual power system, it is shown that the proposed scheme is able to reduce the overall cost by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$20.5\%$</tex-math></inline-formula> and reduce peak power by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$17.3\%$</tex-math></inline-formula> compared to other benchmark models.

An evaluation model for smart grids in support of smart cities based on the Hierarchy of Needs Theory

Smart cities depend highly on an intelligent electrical networks to provide a reliable, safe, and clean power supplies. A smart grid achieves such aforementioned power supply by ensuring resilient energy delivery, which presents opportunities to improve the cost-effectiveness of power supply and minimize environmental impacts. A systematic evaluation of the comprehensive benefits brought by smart grid to smart cities can provide necessary theoretical fundamentals for urban planning and construction towards a sustainable energy future. However, most of the present methods of assessing smart cities do not fully take into account the benefits expected from the smart grid. To comprehensively evaluate the development levels of smart cities while revealing the supporting roles of smart grids, this article proposes a model of smart city development needs from the perspective of residents’ needs based on Maslow’s Hierarchy of Needs theory, which serves the primary purpose of building a smart city. By classifying and reintegrating the needs, an evaluation index system of smart grids supporting smart cities was further constructed. A case analysis concluded that smart grids, as an essential foundation and objective requirement for smart cities, are important in promoting scientific urban management, intelligent infrastructure, refined public services, efficient energy utilization, and industrial development and modernization. Further optimization suggestions were given to the city analyzed in the case include strengthening urban management and infrastructure constructions, such as electric vehicle charging facilities and wireless coverage.

Privacy-Preserving Attestation Scheme for Revocable UAV Charging Using Hybrid State Channels

Although widely applied in varied scenarios, unmanned aerial vehicles (UAVs) suffer severe flight time and flight range limitations due to constrained onboard battery capacity, causing frequent battery recharging when performing persistent missions. The wireless power transfer technology is a promising solution for UAV charging by utilizing unmanned ground vehicles (UGVs) equipped with wireless charging facilities, where charging time slots are auctioned and assigned to UAVs. However, UGVs themselves also have limited energy capacity, resulting in the need to revoke a UAV charging transaction after auction to satisfy their own demand if necessary. In addition, as UAVs and UGVs are mutually distrustful, inherent security and privacy concerns must be resolved during the revocation. In this paper, we resort to blockchain technology for secure and efficient revocable charging in vehicle-assisted wireless UAV networks. We present PAS, an efficient privacy-preserving attestation scheme for revocable UAV charging based on hybrid state channels, where UAVs and UGVs perform off-chain operations as blockchain users for privacy and efficiency, while security and fairness are guaranteed by the on-chain mechanism. PAS consists of a multi-party state channel and multiple two-party state channels responsible for charging scheduling and transaction revocation, respectively. PAS ensures fair and private revocation negotiation and compensation in a trust-free manner by developing a set of carefully designed modular protocols. We provide PAS’ constituent primitives in detail, prove its security properties following the universally composable (UC) framework, and present experimental results to demonstrate its feasibility and scalability.

Need of Integrated Regional Planning Approach for the Decentralisation and Optimisation of Renewable Energy Based Electric Vehicle Infrastructure: A Comprehensive Visualisation

The existing research narrates avenues in the regional and thematic area preconditions set via the framework and institutional mechanism towards energy decentralisation (ED). Moreover, with the entrant stakeholders and inclusive energy policy, the researchers find potential in local resources and capacity towards the decarbonisation of the economy. Consequently, governments around the globe emphasise multi-level sectoral economic support packages to buffer the immediate to medium-term gap and subsequently investigate their implementation in infrastructure and technology. The present review attempts to focus on the conditions of energy transformation in enabling a policy and regulatory framework. As such an integrated regional spatial framework focuses to identify support packages across urban and rural planning, transportation, renewable energy, infrastructure, environment and climate change and sustainability. Moreover, the present review revolves its thematic focus around the transport sector to strategize the energy decentralisation of the local potential in the ongoing electric vehicle (EV) transportation. The presented review toils on EV users’ struggle to orient to the need of the hour in the inadequacies of refill/charging infrastructure. Thus, it is imperative to review parameters such as availability and access to charge, depending on the source of energy in the charging infrastructure, facilities and services at the regional level. The presented review investigates under categoric and key search across conceptual regional settlement hierarchy to strategize the development of the Renewable Energy based Electric Vehicle Infrastructure (REEVI) package under system, support and services (SSS). Conclusively, the review study brings out a tentative regional settlement hierarchical integrated methodology for REEVI-SSS in the missing linkages and gaps of spatial planning to ease medium and long trip EV transportation challenges faced at the inter-city–rural, i.e., regional level.

Coordinated Planning of Fixed and Mobile Charging Facilities for Electric Vehicles on Highways

This paper presents a bilevel planning framework to coordinate truck mobile chargers (TMCs) and fixed chargers (FCs) on highways to promote charging flexibility and provide more choices for electric vehicle (EV) users. A collaborative location optimization (CLO) approach is developed at the upper level to optimize the location of charging stations. Furthermore, a collaborative capacity optimization (CCO) approach is formulated at the lower level to optimize the capacity of TMC and FC at candidate stations. In the proposed framework, origin-destination (OD) analysis, Floyd algorithm and Monte Carlo simulation (MCS) are employed to generate the spatial-temporal distribution of charging demand based on historical data. An improved income approach (IIA) is then developed to well capture the heterogeneity of EV users’ charging behavior. The waiting cost of EV users is estimated by their value of time (VOT), which helps them to make a better choice between TMC and FC. To solve the optimal model easily, the big-M method is applied to linearize and convert the nonlinear problem into a mixed-integer linear programming (MILP) model. Meanwhile, the analytical target cascading (ATC) technique is employed to realize the data exchange process between the upper and lower layers. Finally, numerical study demonstrates the effectiveness of the proposed framework and method.

Energy Management and Charging Portfolio Analysis for Future Battery Powered Harbor Vessels

This paper intends to provide key insights to the marine designers and port authorities for adapting battery-operated zero emission electric harbor vessels (ZEE-HVs) and plan the resources for charging infrastructure. The present study is a cumulatively coordinated analysis of various significant aspects concerning the adaptation of ZEE-HVs for short-endurance commercial maritime operations. The sizing of onboard battery energy systems (OBES) is discussed for different short-endurance ZEE-HVs by considering the speed-resistance characteristics of the hull and open-water characteristics of the propeller without limiting their operations for specific load profiles/operating cycles. Charging portfolio selection is critical for a marine vessel as the OBES size is several times higher than a regular electric vehicle's battery. Hence charging portfolio selection criteria are presented to select a suitable battery charging protocol for each ZEE-HV as per the OBES ratings and available idle times on a typical day. Since the port is a commercial spot, uncertainty in resource planning leads to penalties and loss of goodwill. Therefore, Monte Carlo-based iterative analytical method is adopted to forecast the ZEE-HVs' maximum possible charging power demand on a typical day. By the load forecast data, optimal sizing of the load peak shaving battery (LPSB) was performed to limit load fluctuations at the port grid. The synergy of ZEE-HVs with LPSB and bi-directional charge-discharge controller is pivotal for effectively administering the seaport shore charging facility, which is demonstrated for a typical energy management cycle.

A study of the impact of voltage sag on sensitive loads at low-voltage distribution areas

Under the background of the dual carbon goal and the new power system, the power system becomes more complex and diverse, and voltage sag events caused by short-circuit faults, overloads, switching operations, large motor starting, and distributed generation access are more frequent. On the other hand, with the increasing sensitivity of low-voltage distribution network electrical equipment to power quality, especially for precision process control equipment using computers, power electronics, and automation technology, new energy generating units, and electric vehicle charging facilities, voltage sag accidents will cause difficult-to-estimate losses in equipment production and operation, and frequent voltage sag events have become one of the main power quality problems affecting reliable power supply and normal equipment operation. To address this problem, this paper analyzes the impact of voltage sag on low-voltage substation loads from a mechanism perspective, establishes a voltage sag tolerance curve for electronic appliances through experimental research, and simulates and verifies the effectiveness and correctness of the method in this paper using a 3 MW-rated induction generator connected to the distribution network as an example.

Accelerating Two-Phase Multiobjective Evolutionary Algorithm for Electric Location-Routing Problems

Electric location-routing problem is a challenging problem consisting of the optimization of electric vehicle routing and charging facility location, simultaneously. Existing algorithms generally adopt the two-phase search strategy to alternately optimize the routing and the location. However, they are usually criticized for the inefficiency as the problem scale increases. In order to improve the search efficiency in each phase, we propose an accelerating two-phase multiobjective evolutionary algorithm, where the learning method is used to mine the useful information from the historical search process to generate the high-quality routing and location offspring. To be specific, in the routing optimization phase, an interpolation method is developed to extract the frequent visiting orders existing in the historical best solutions. These frequent visiting orders are used to create potential routing offspring that can accelerate the convergence toward the optimal solutions. In the location optimization phase, a surrogate model is used to approximatively represent the relationship from routing to location, which can directly output a promising location scheme for a given routing offspring and thus reduce the optimization time. Experimental results on different scales of test instances demonstrate the competitiveness of the proposed algorithm in comparison with several state of-the-art algorithms, including four widely used heuristic algorithms and two multiobjective evolutionary algorithms.

Provision of adolescent and youth-friendly services in public health facilities in Migori County, Kenya

Background: Global and national guidelines on provision of adolescent and youth-friendly services (AYFS) exist. However, the extent to which these services are provided in developing countries, including Kenya, is unknown. Therefore, this study aimed to assess provision of AYFS in public health facilities in Migori County, Kenya. Methods: A cross-sectional study design was employed. The study setting was public health facilities in Migori County. The county has 275 health facilities, of these 159 are government owned/public health facilities. A multistage sampling of 114 public health facilities was done from which 210 healthcare providers (HCPs) were sampled using simple random sampling. Three facility in-charges were purposively selected to represent each of the county's three Levels of healthcare delivery system. Data was collected using structured questionnaires, key informant interviews guide, and Health facility observation checklists. Results: Majority 153 (74%) practiced nursing and 148 (71%) had worked at their current workstation between 1-5 years. Equitable, accessible, acceptable, appropriate, and effective AYFS are provided in the government owned public health facilities. Conclusion: Inadequate AYFS training of healthcare providers and poor implementation of existing policies including weak engagement of young people in AYFS significantly hinder the effective provision of AYFS in public health facilities.

Joint location optimization of charging stations and segments in the space-time-electricity network: An augmented Lagrangian relaxation and ADMM-based decomposition scheme

Electric vehicles that contribute to better air quality, less noise, and low-carbon emissions are a promising selection for sustainable transportation. However, the development of electric vehicles is impeded by various factors, including driving range anxiety, long recharging period, and insufficient charging facilities. As the charging-while-driving techniques gradually mature, electric vehicles can recharge on charging stations stationarily or charging lanes (segments) dynamically. Additional charging facilities should be constructed to improve the level of charging services. Under a predefined construction budget, the difficulty is how to determine their numbers and distributions. This study jointly locates charging stations and segments by maximizing the accessibility of electric vehicles. In space-time-electricity networks, we formulate a multi-commodity network flow model with location and routing. A decomposition scheme based on augmented Lagrangian relaxation and alternating direction method of multipliers is developed to tackle this problem. The standard and augmented Lagrangian relaxed problems are decomposed into many solvable subproblems. Numerical experiments are conducted in three transportation networks, showing that the proposed method can achieve good integrality gaps.

Long-Distance Electric Truck Traffic: Analysis, Modeling and Designing a Demand-Oriented Charging Network for Germany

The majority of freight in Germany is carried out by trucks, resulting in emitting approximately 9% of Germany’s carbon dioxide equivalent emissions. In particular, long-distance truck journeys contribute significantly to these emissions. This paper aims to explore the conditions and impacts of introducing E-Trucks in Germany by utilizing a microscopic traffic simulation approach. Therefore, five different electrification levels of the long-distance truck traffic are evaluated. The demand-oriented charging network dimensioning aims for a realistic and implementable design and is based on an average charging power of 720 kW. Additionaly, it considers the necessary infrastructure requirements at service and rest areas next to the motorway. The results of this research provide valuable insights in terms of usage, requirements and demand. For an electrification level of 1%, 177 chargers at 173 charging sites must be implemented, while 1296 chargers and 457 charging sites must be built for an electrification level of 20%. The increase in the electrification level leads to more efficient occupancy of the charging facilities; i.e., an increase from 1% to 5% improves the average occupation time ratio per charger by approximately 130%. Of the total energy consumed, 65% is recharged en-route at public chargers. Between Monday and Thursday, each 1% electrification level increase requires 2.68 GW h more energy for the public recharging network.

Retracted: Ecological Landscape Design and Evaluation in Public Charging Facilities for Electric Vehicles.

[This retracts the article DOI: 10.1155/2022/3010851.].

A novel solar photovoltaic powered grid interactive battery charging system for electric vehicle applications

ABSTRACT In this work, a novel Solar Photo Voltaic (SPV) powered grid interactive Electric Vehicle (EV) battery charging system has been proposed and validated. The objective of the proposed system is to provide seamless battery charging facility that includes a high capacity station battery system. The grid interactions like integration of SPV energy, station battery charging and reactive power support are included through the DC link of aShunt Active Power Filter (SAPF). The SAPF maintains unity power factor on the source side grid current. The objectives of the proposed system are ensuring the source side power factor nearly unity with minimal THD of source current, an SPV grid integration system with Maximum Power Point Tracking (MPPT), a comfortable charging point for EVs with a reliable charging station supported by a back up station battery. The novelty of the proposed work is that the common DC bus bar maintains a high DC link voltage when the utility source is available and the SAPF is active. The regulation of the DC link voltage is achieved by a PI controller tuned by the Gravitational Search Algorithm. The proposed system has been validated using simulations in the MATLAB SIMULINK environment as well using an experimental prototype. The proposed GSA controller outperforms in terms of THD (%) of source and load currents are 2.4 and 17.87, respectively.

E-Bike Charging Infrastructure in the Workplace—Should Employers Provide It?

Constructing charging infrastructure for e-bikes at home or in other locations is necessary to enable motor support while riding. This paper focuses on charging facilities at work and study locations. It analyzes the charging frequency preference of 281 e-bike commuters who work or study at RWTH Aachen University, using survey data with 1091 choices for hypothetical free charging, as well as the same conditions for hypothetical paid charging. We use a mixed logit model to estimate the factors influencing the charging frequency, focusing on the commuting distance, an e-bike’s resale value, the age of the owner, student status, and employment group. One charging event per day can be expected for four e-bike commuters when free charging is available. In the case of paid charging, there is one charging event per 12 e-bike users. The magnitude of the reduction caused by a charging fee depends on group membership and, probably, on income. Commuting distance only has a statistically significant influence on the charging frequency when charging is free, raising the question of whether charging at work is necessary to cover trip chains that include stops at work. Owners of more expensive e-bikes charge less often, likely due to higher battery capacities, while the influence of age is inconclusive. However, providing charging infrastructure for employees and guests could be used as a low-cost measure to promote cycling among commuters.

Coordinated planning of charging swapping stations and active distribution network based on EV spatial‐temporal load forecasting

AbstractElectric vehicles (EVs) charging swapping stations (CSSs), as well as multi‐functional integrated charging and swapping facilities (CSFs), have become important to reduce the impact of e‐mobility on the electric power distribution system. This paper presents a coordinated planning optimization strategy for CSSs/CSFs and active distribution networks (AND) that includes distributed generation. The approach is based on the application of a specifically developed spatial‐temporal load forecasting method of both plug‐in EVs (PEVs) and swapping EVs (SEVs). The approach is formulated as a mathematical programming optimization model that provides the location and sizing of new CSSs, the best active distribution network topology, the required distributed generation, and substation capacities. The developed model is solved using CPLEX, and its characteristics and performances are evaluated through a realistic case study.

A novel fast-timing readout chain for LHCb RICH LS3 and prototype beam tests

The prompt Cherenkov radiation and focusing optics of the LHCb RICH detectors allow the prediction of the Cherenkov photon detection time from a given charged particle to within 10ps. Fast-timing information on the detected Cherenkov photons can therefore be used to significantly improve the particle identification (PID) performance and the signal-to-background ratio of the detectors. This concept is a cornerstone for the LHCb RICH detector upgrades and will ultimately allow the system to operate at a luminosity in excess of 1034cm−2s−1 during HL-LHC Run 5. A new electronic readout chain is proposed for the LHC Long Shutdown 3 (LS3, 2026-2028) using the FastRICH, a novel ASIC under development. The specifications for the FastRICH are discussed in the context of the LS3 enhancements and LHCb Upgrade II. The FastRICH will perform multi-channel single-photon discrimination, timestamp photons with 25 ps bin size, integrate closely with the LHCb optical link chipset and apply data-compression techniques. The detector will be capable of timestamping each photon with 150ps resolution dominated by the existing Multianode Photomultiplier Tube (MAPMT) transit-time spread. The new electronic readout chain introduces important timing and detector techniques ahead of the Upgrade II RICH system overhaul and the FastRICH has the flexibility to be coupled to sensors with better time resolution for HL-LHC Run 5. Simulation studies have demonstrated improvements in the hadronic PID performance during Run 4 using the FastRICH coupled to MAPMTs. A first version of the readout chain, based on the FastIC, a predecessor of the FastRICH, and a TDC-in-FPGA, has been studied using Cherenkov photons at the CERN SPS charged particle beam test facility.