Electric Charging Stations Research Articles

SmartCoin: A novel incentive mechanism for vehicles in intelligent transportation system based on consortium blockchain

An intelligent transportation system (ITS) improves traffic safety and efficiency by enabling vehicles to generate and broadcast messages. However, it is not easy to trust the received message's credibility in an untrusted environment or untrusted network. Additionally, there is no reward mechanism for the honest message generator. Hence, to improve safety and network efficiency and encourage more vehicles to participate in network improvisation, we proposed a novel incentive mechanism for vehicles called SmartCoin based on a consortium blockchain. The proposed scheme aims to achieve social welfare, improved transportation, less traffic congestion, reduced road accidents, and a transportation network free from fraud messages. In the proposed scheme, vehicles give the rating to the message source vehicle based on the validity of the message. Some SmartCoins are credited into the vehicle's account at the blockchain according to the rating of the message. The SmartCoins could be redeemed either at the fuel station, electric charge station for electric vehicles and vehicle service station. Blockchain technology provides decentralization, immutability, transparency to the ITS. The secure storage for the SmartCoin, traffic messages and user information is achieved using blockchain. The secure hash algorithm (SHA256) and elliptic curve digital signature algorithm (ECDSA-192 bit) are used to provide secure communication, message integrity and authentication for vehicles and information. The result analysis reveals that the proposed scheme is effective, comprehensive, and feasible in collecting and storing trust values in the ITS network. The performance evaluation showed enhancement in performance as 90% less consensus delay and 70-80% less storage and communication cost compared to state-of-the-art schemes.

Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids

Studies on forecasting and optimal exploitation of renewable resources (especially within microgrids) were already introduced in the past. However, in several research papers, the constraints regarding integration within real applications were relaxed, i.e., this kind of research provides impractical solutions, although they are very complex. In this paper, the computational components (such as photovoltaic and load forecasting, and resource scheduling and optimization) are brought together into a practical implementation, introducing an automated system through a chain of independent services aiming to allow forecasting, optimization, and control. Encountered challenges may provide a valuable indication to make ground with this design, especially in cases for which the trade-off between sophistication and available resources should be rather considered. The research work was conducted to identify the requirements for controlling a set of flexibility assets—namely, electrochemical battery storage system and electric car charging station—for a semicommercial use-case by minimizing the operational energy costs for the microgrid considering static and dynamic parameters of the assets.

Optimizing electric bus charging infrastructure considering power matching and seasonality

• Electric bus charging infrastructure and vehicle flow are jointly optimized. • Power matching and seasonality effects on bus battery are considered. • A surrogate-based optimization approach is proposed to solve the model. • An empirical study with bus operational data in Beijing is analyzed. In this research, a novel optimization model for electric bus charging station location, charger configuration, charging time and vehicle flow is developed considering power matching and seasonality. The seasonality highlights the effect of air temperature on the battery performances of electric buses. Power matching between batteries and chargers jointly determines the maximum battery acceptance rates of electric buses, and this consideration results in nonlinear constraints. A surrogate-based optimization approach is proposed to solve the mixed integer nonlinear program efficiently. The optimization model is demonstrated on a sub-transit network including 17 bus lines in Beijing. The results reveal significant performance differences regarding vehicle scheduling and charging among different bus fleets in the BEB-based transit system. The interesting findings on the distribution of vehicle flows for charging provide strong evidence to consider powering match in the bus charging infrastructure layout.

Effects of Demand Fluctuation and Mitigation Strategy in Low Voltage EV Charging Station by Battery Energy Storage System

In this paper, the effects of fluctuating demand on a low voltage electric utility system equipped with electric vehicular charging station have been studied and mitigation strategy has been proposed. By applying Battery Energy Storage System (BESS) and demand management (DMM), the stored electric energy during an off-peak period is controlled to supply the spiky demand during the EV charging period. Employing different approaches of discharging control, the BESS can response and shape the peaky demand into the smoothed one with an elevated load factor. Therefore, the result is that energy cost of EV charging has been reduced by cutting the demand charge during the on-peak period and the power quality of the system has also been improved. These findings are confirmed and illustrated by simulation results.

Shunt capacitor allocation by considering electric vehicle charging stations and distributed generators based on optimization algorithm

The two-stage optimization bear smell search algorithm (BSSA) based on fuzzy theory is proposed for determining the optimal location and size of dispersed generation sources, shunt capacitors, and electrical charging stations in distribution systems. In BSSA, in the first stage, the fuzzy method is used for measuring optimal Distributed Generations (DGs) and Shunt Capacitors (SCs) to improve the power factor, re-generation, power losses, and voltage specifications of the distribution system. In the second stage, the distribution system is considered as integrated with DGs and SCs, and the fuzzy BSSA is used to identify the optimal locations for the Electric Vehicle (EV) charging stations and number of vehicles in these stations. Moreover, in the proposed model, a lithium-ion EV battery is used for charging and the characteristic curves are used for analyzing the generated load current. The bear smell search algorithm, which is inspired by bears’ hunting in nature, is a novel meta-heuristic algorithm for solving optimization problems. If the complexity of optimization problems increases, this algorithm suffers from low convergence speed, which increases computation time. To resolve this problem, we propose a new development for this algorithm. Moreover, we examine the effects of EV load increase and uncertainty in DGs and the load distribution system on the performance of the distribution system. The simulation results show that the advantages of BSSA are more than those of the other optimization methods. The simulation results in a 51-bus distribution network indicate that the proposed method has better performance based on numerical analyses.

Output-Input Hybrid Passive Filter Design for Electric Vehicle Charging Station

The impact of electric car charging stations on power grid harmonics is growing as their existence continues to expand and creates harmonic distortion in the power system. At the same time, the quality of charging current and voltage through the process of charge becomes inferior. Therefore, reduction of output ripple factor (RF) and mitigation of input current harmonics is vital in this situation. This paper presents the design of the output filter and three kinds of shunt passive input filters to decrease the present harmonics generated in the industrial power scheme by the charging stations. The simulation software MATLAB/Simulink was used. Results were acquired before and after installation of filters and after installation of filters, it was found thatthe percentage RF of output current, voltage, and the percentage THD of the input current is reduced to match the set standards.

Emissions life cycle assessment of charging infrastructures for electric buses

This paper evaluates and calculates the magnitude of greenhouse gases produced from the implementation of electric bus charging stations into existing bus depots concurrent with the transitioning of the commuter bus fleets into electrified powertrains. To achieve this, a comprehensive and in-depth emissions life cycle assessment is conducted and utilises the Australian based fleets as a case study, focusing particularly on Sydney city and Inner West regions. To define the scope and system boundary for this type of study, the authors have chosen bus routes that take into account city, suburban, and highway driving. The study conducts a life cycle assessment of electric bus charging stations that incorporates the greenhouse gas emissions produced from the production, transportation, installation, operations, and decommissioning phases. Additionally, three alternate scenarios are explored: time variance, high shares of renewables, and net-zero emissions by 2050. Results show that contributions from infrastructure development and the transition to electrified buses are substantially outweighed by operation emissions. The operations phase is heavily dependent on the electricity grid-mixes carbon intensity and contributes the most greenhouse gas emissions (98.8%), followed by production (0.69%), recycling and disposal (0.48%), installation (0.01%), and transportation (0.01%). The current Australian electricity grid-mix produces approximately 1.2 ∼ 1.4 times more greenhouse emissions than when combusting diesel fuel. Thus, net-zero emissions will not be achieved without substantial grid-mix decarbonisation. This study also finds that regional-specific parameters heavily influences the final life cycle emissions calculations. For the case-specific scenario, it is found that transitioning the existing transport bus fleet into electric powertrains has the potential to significantly reduce the impact on climate change compared to diesel buses. However, it can only be made possible if the electricity used to charge the electric buses is generated from low carbon-intensive sources, such as renewable energy.

Location and Expansion of Electric Bus Charging Stations Based on Gridded Affinity Propagation Clustering and a Sequential Expansion Rule

With the escalating contradiction between the growing demand for electric buses and limited supporting resources of cities to deploy electric charging infrastructure, it is a great challenge for decision-makers to synthetically plan the location and decide on the expansion sequence of electric charging stations. In light of the location decisions of electric charging stations having long-term impacts on the deployment of electric buses and the layout of city traffic networks, a comprehensive framework for planning the locations and deciding on the expansion of electric bus charging stations should be developed simultaneously. In practice, construction or renovation of a new charging station is limited by various factors, such as land resources, capital investment, and power grid load. Thus, it is necessary to develop an evaluation structure that combines these factors to provide integrated decision support for the location of bus charging stations. Under this background, this paper develops a gridded affinity propagation (AP) clustering algorithm that combines the superiorities of the AP clustering algorithm and the map gridding rule to find the optimal candidate locations for electric bus charging stations by considering multiple impacting factors such as land cost, traffic conditions, and so on. Based on the location results of the candidate stations, the expansion sequence of these candidate stations is proposed. In particular, a sequential expansion rule for planning the charging stations is proposed that considers the development trends of the charging demand. To verify the performance of the gridded AP clustering and the effectiveness of the proposed sequential expansion rule, an empirical investigation of Guiyang City, the capital of Guizhou province in China, is conducted. The results of the empirical investigation demonstrate that the proposed framework that helps find optimal locations for electric bus charging stations and the expansion sequence of these locations are decided with less capital investment pressure. This research shows that the combination of gridded AP clustering and the proposed sequential expansion rule can systematically solve the problem of finding the optimal locations and deciding on the best expansion sequence for electric bus charging stations, which denotes that the proposed structure is pretty pragmatic and would benefit the government for long-term investment in electric bus station deployment.

Solar Charging Station for Electric Vehicles

This paper describes design of solar powered charging station for charging of electric vehicle that solves the key downside of fuel and pollution. While EV charging has traditionally been grid-based, use of solar powered chargers has emerged as an interesting opportunity. As worlds resources are diminishing, government agencies and non-government organization are pushing greener solution through the use of renewable energy sources. In order to reduce the pollution through the motor vehicles, there is a large scope of increase in electric vehicles all over the world. To run the electric vehicle the fuel required is the electricity which can be storable through the use of solar energy. Electric vehicles that run on the Electric vehicle smart charging station which is the promising alternative and environmentally sustainable solution to meet up the energy crisis. This paper investigates the possibility of charging the battery of electric vehicles at a various working place like offices, colleges, hospitals, universities etc in India using solar energy. In this paper, the charging station successfully developed as desired features for electric vehicle from renewable energy resources with solar panel, solar charge controller, batteries storage and DC-DC converter. A laboratory-scale experimental prototype was also developed, and the performance of the proposed charging station was investigated.

Multiport Converter based EV Charging Station with PV and Battery

: As a ecofriendly electrical vehicle, is vehicles that are used electric motor or traction motor. Are receiving widespread attention around the world due to their improved performance and zero carbon emission . The electric vehicle depend on photovoltaic and battery energy storage system . Electric vehicles include not limited road and railways. It consist of many electric appliances for use in domestic and industrial purposes that is electric car ,electric bike ,electric truck ,electric trolley bus , electric air craft ,electric space craft.The main Moto of this paper is a modelling of proposed system smart charging for electrical vehicle insuring minimum stress on power grid . The large scale development of electrical vehicle we need electric charging station for example fast charging station and super-fast charging station . During a peak demand load , large load on charging station due to the voltage sag , line fault and stress on power grid . At this all problem avoid by multiport converter based EV charging station with PV and BES by using analysis of MATLAB simulation. Result and conclusion of this paper to reduce losses improving efficiency of solar energy , no pollution (reduce) fast charging as possible as without any disturbance.

Investigation of Grid-connected PV System with Electrical Appliances, Electric Vehicles

Electric vehicles (EVs) making a significant contribution to the reduction of fossil fuel consumption and CO2 emissions are expected to thrive in Vietnam in the upcoming years/in the near future. However, such vehicles’ energy demand could become a burden on the transmission networks, causing overloads to the electric grid of the nation. Hence, to solve this problem, a solar PV system can be utilized to fulfill the electricity needs in an EV charging station. This article presents the design, simulation and economic analysis of a grid-connected solar power system for an electric charging station at Thu Dau Mot University (TDMU). The photovoltaic (PV) power system is designed to supply energy to the charging station and office building. The study estimates the generated electricity, the efficiency of the PV power system and the ability to reduce CO2 emissions. This paper can be a recommended input for stakeholders to consider using this energy source for charging vehicles.

Monitoring of Electric Buses Within an Urban Smart City Environment

A practical experience on monitoring the data generated by electric buses is presented, focusing on energy consumption, charge and state of the batteries. The work is carried out in the framework of a global smart city strategy developed by the H2020 Smart City Lighthouse STARDUST project. The crucial role of the data collection and transmission from electric buses has become evident in this work, so the adopted solutions are covered in detail. A practical electric bus charging station configuration is considered, operating within the city of Pamplona, Spain, with an urban route setting in which electric charging is performed. Various key factors for the practical implementation of the necessary communication infrastructure, including wireless Low Power Wide Area connectivity challenges within the urban scenario settings, based in LoRa/LoRaWAN communication system nodes. The monitoring system architecture is also presented, in which specific machine learning modules in order to collect patterns and visualization of data to enhance planning, operation and maintenance procedures.

Review of Renewable Energy-Based Charging Infrastructure for Electric Vehicles

With the rise in the demand for electric vehicles, the need for a reliable charging infrastructure increases to accommodate the rapid public adoption of this type of transportation. Simultaneously, local electricity grids are being under pressure and require support from naturally abundant and inexpensive alternative energy sources such as wind and solar. This is why the world has recently witnessed the emergence of renewable energy-based charging stations that have received great acclaim. In this paper, we review studies related to this type of alternative energy charging infrastructure. We provide comprehensive research covering essential aspects in this field, including resources, potentiality, planning, control, and pricing. The study also includes studying and clarifying challenges facing this type of electric charging station and proposing suitable solutions for those challenges. The paper aims to provide the reader with an overview of charging electric vehicles through renewable energy and establishing the ground for further research in this vital field.

Two-stage fuzzy-logic-based for optimal energy management strategy for SOFC/PV/TEG hybrid polygeneration system with electric charging and hydrogen fueling stations

Integration between supplies for stationary power and vehicles is potentially useful for increasing the efficiency and the reliability of energy generation systems. Solid oxide fuel cell is one matured technology, which is suitable for a polygeneration system and provides an integration of supply for stationary power and vehicles. However, a combination of solid oxide fuel cell with photovoltaic thermal and thermoelectric generation increases the complexity of a polygeneration system. The system needs a management strategy for dispatching the energies produced. Therefore, in this work, a fuzzy energy management strategy was applied for this polygeneration system by considering two different configurations: an off-grid system with electric vehicle supply and an on-grid system with hydrogen vehicle supply. A two-stage fuzzy energy management strategy considering optimization and management of multi-parameters of the polygeneration components was considered. The evaluation of the optimum fuzzy was analyzed based on energy, economic, and environmental criteria. From the results obtained, the optimal strategy increased the reliability, energy, and system cost savings by 22.05%, 22.4%, and 32.58%, respectively. Moreover, the optimum management reduced the power loss of the polygeneration system by about 48.82%, which was achieved by the configuration with electric vehicles supply and off-grid connection.

Cascaded Interleaved DC–DC Converter Designed for Grid-to-Vehicle and Vehicle-to-Grid Technologies

This paper presents a study of a cascaded bidirectional interleaved DC–DC converter applied to an electric charging station, which uses grid-to-vehicle (G2V) and vehicle-to-grid (V2G) technologies. In this context, the interleaved technique is used to reduce the current ripple through the battery of the electric vehicle (EV), which can also absorb or deliver power to the microgrid. Additionally, the small-signal technique is also employed to calculate the gains of the PI controllers for charging and discharging the EV battery. Finally, this paper presents a set of simulations using the software PSIM® and experimental results using a low-cost hardware-in-the-loop (HIL) to support the theoretical study and to demonstrate the effectiveness of the proposed approach.

Solar based wireless on road charging station for electric vehicles

Electric vehicle (EV) emerging as an upcoming technology in both the sector of transportation and power. There are more benefits in terms of economic and environmental conditions. The most important factor in Electric Vehicle is charging station, which reduces a green gas effect and environment pollution. This electric charging station is also known as Electric Vehicle Supply Equipment (EVSE). It consists of both the high power and low power. The high power is terminated at a fraction of second charging that can be implement in the Electric vehicle rather than the low power so, if we construct an on-road charging with the help of solar panel it will be very useful to charge at any point of time and with the help of connected batteries we can drive in off road. Remote force move technique is fused in moving the sunlight-based force from the Photo Voltaic (PV) cell to the battery utilized in the electric vehicle. Sun oriented boards are considered to assemble an independent force station, along these lines limiting its reliance on ordinary energy assets. The sun-oriented boards create electrical energy by the utilization of the light energy produced by the sun. The energy acquired from the board is taken care of to a battery, through a sunlight-based charge regulator which augments the force yield from the PV cell. The communicating coil with the receiving coil are connected wirelessly and thus the DC current is injected to the battery. Once the battery is full it automatically turned off from solar power. Thus, it results in sustainable transportation and use of Electric batteries. The charging stations are outlined and the impact of electric vehicle are also discussed.

Location planning of electric taxi charging station based on driving trajectory

With the vigorous development of energy technology, the promotion and use of electric vehicles has brought new vitality to the development of ecological environment. According to the big data of taxi travel trajectory, we can get the idle rule of taxi operation time. Taking the idle time and location of taxi as the demand hot spot, taking the location points along the road network of the research area as the candidate points, this paper uses ArcGIS to do the location planning of charging station, so that the charging station can reduce the charging anxiety of taxi drivers, meet the charging demand to the maximum extent, and get the the minimum number of stations, and the quantity and distribution are taken as the site selection scheme..

Electric and plug-in hybrid vehicles and their infrastructure in a particular European region

As vehicles powered by conventional combustion engines must be refueled with fossil fuels, so electric vehicles need to supply their own source of energy needed to power them. In case of electric vehicles, electric energy is the main commodity, which is stored in batteries. Electric energy for electric vehicle (or some kinds of hybrid vehicles) is most often supplied by home electric charging station or public charging station. If we want to discuss advantages of operation of electric vehicles, we have to analyze the way of production of electric energy. If the vast majority of electricity produced in less ecological ways, which burden and pollute the environment, electric vehicles cannot be claimed as an environmentally friendly alternative and a substitute for internal combustion vehicles. There are also issues with charging options, building infrastructure, recycling used batteries and many others factors effecting future modes of transport. The article analyses the current overview of possibilities of charging electric or plug-in hybrid vehicles, current infrastructure aimed mainly on region of Central and Eastern.

Location and capacity decisions for electric bus charging stations considering waiting times

This research proposes a mixed integer-linear mathematical model for location and capacity decisions of electric bus charging stations in order to ensure the connectivity of the road network throughout a certain region. The routes followed by electric buses in a country, demand in each route and driving ranges of electric buses are considered so as to determine the locations and capacities of charging stations under limited waiting time constraints. We implement the model on a case study for intercity bus networks in Turkey and use the actual data of coach companies. The results provide optimal locations and capacities of charging stations with minimum cost. Moreover, sensitivity analysis is performed to analyze the effects of different parameters on the results. It is observed that driving ranges have the highest importance in the efficient use of electric buses, and charging durations, number of trips and service rates significantly affect capacities of stations.

Stochastic Energy Management of Electric Bus Charging Stations With Renewable Energy Integration and B2G Capabilities

In this paper, the stochastic energy management of electric bus charging stations (EBCSs) is investigated, where the photovoltaic (PV) with integrated battery energy storage systems (BESS) and bus-to-grid (B2G) capabilities of electric buses (EBs) are included for cost-effective charging of EBs. Also, the day-ahead dynamic prices are derived to mitigate charging impacts on power distribution systems. This problem is formulated as a distributionally robust Markov decision process (DRMDP) with uncertain transition probabilities and costs to address the impacts of random bus loads with inaccurate probability density function estimation. An event-based ambiguity set with combined statistical distance and moment information is developed to achieve minimax-regret criteria for less-conservative and robust solutions. To facilitate practical applications with reduced computational complexity, a heuristic regret function is proposed, based on which the dynamic prices are derived. Case studies based on EB data from St. Albert Transit and IEEE test feeders indicate that the proposed method can minimize EB charging cost with mitigated impacts on power distribution systems.