Vehicle-to-Grid （V2G） technology can provide various supports for the operation of power system, such as peak shaving, frequency regulation and reserve, etc. The realization of V2G can significantly contribute to the secure operation of power systems and facilitate the renewable energy integration. This paper primarily focuses on analyzing control technologies, market mechanisms and infrastructure issues of V2G. First, this paper analyses the architecture and control targets of V2G. Secondly, different control strategies are investigated under the centralized, distributed and hierarchical control frameworks for V2G. Thirdly, we summarize the cost-benefit, business model and market mechanism of V2G with policy recommendations and further discuss the infrastructure needed and communication standard for V2G. Finally, the future directions for V2G research and applications are briefly given.
The development and applications of electric vehicles have become a strategic option in many countries around the world to address the energy crisis and environmental pollution problems. Extensive applications of plug-in electric vehicles could result in some new problems even challenges to the secure and economic operation of a power system concerned. Given this background， the state-of-the-art and future prospect of power batteries are introduced at first， and the aggregated load characteristics of electric vehicles with their spatial and temporal distributions considered are presented in detail. Then， the impacts of plug-in electric vehicles on the power system especially on the distribution system concerned are outlined. The coordinated interactions between electric vehicles and power systems are next addressed， and some charging and discharging control strategies for electric vehicles are outlined for supporting the secure and economic operation of the power system. Finally， the economic profits of the interactions between electric vehicles and power systems are briefly examined from both the perspective s of the owners of electric vehicles and the power system.
With continuous breakthrough in key technologies and increasingly improvement in infrastructures， countries all over the world have been joining battles for the technical and commercial commanding elevation of the electric vehicles industry. In this paper， we firstly concluded current status and prospect of the global electric vehicle market. Then the development courses of electric vehicle industries in the US， the EU， Japan and China were explored from aspects of market situation， technological route and industrial support， and bottlenecks in the progress of electric vehicle industry were further unveiled. Finally， this study introduced the state and future trend of electric vehicle technology development based on an analysis of motor driven technology， electric control system management and Lithium-ion battery technology.
With the rapid growth in the number of electric vehicles （EVs）， the charging and discharging behavior of EVs will bring a greater impact on the distribution network planning. The rational use of EV charging and discharging behavior for the overall planning of distribution network will be the focus of future research. The type， number and charging mode of EV， as well as the national policy will make changes to the impact of EV on distribution network. This paper described the above factors， and then analyzed the impact of EV charging and discharging on distribution network and its rational use. At last this paper proposed some suggestions on the planning of EVs' charging and discharging devices and the distribution network planning adapting to EV access
Electric vehicles （EV） is revolutionary technology with clean energy instead of traditional energy， which attract attention in worldwide. Under the background of the rapid development of electric vehicles （EV）， this paper analyzes consumption behavior and developing route of EV. Firstly， effect of EV connecting into distribution network was analyzed. Secondly， challenges to distribution network planning were presented. Finally， adaptive planning system of distribution network was proposed， which adapted to EV development. This achievement could give a guide to research direction and key point for planning and design of distribution network with large-scale EV load connection.
According to the development of electric vehicles （EVs） and the construction of EVs' charging and discharging devices， this paper analyzed the influence of EV integration on distribution network. From the aspects of the selection of voltage level， the determination of user level， the selection of access point， the configuration of power supply， the selection of electrical equipment， the quality of electric energy and so on， this paper proposed the technical principle of the integration of EVs' charging and discharging devices into power grid. Finally， the typical integration mode of EVs' charging and discharging devices into power grid was presented， which could provide important basis for the guidance of planning and design， the standardization of operation and management and timely， reliable， reasonable and orderly integration of charging and discharging devices.
Appropriate planning of charging facilities is of significant importance for the development of electric vehicles （EVs）. Given this background， a systematical approach for siting and sizing of EV charging facilities based on geographical zonal EV charging demand coefficients is proposed. A charging load prediction model is presented at first， based on the analysis of various charging modes. The demands for different charging facilities are subsequently calculated with the inputs of daily energy charging needs and the maximum plug-in numbers for all types of EVs. Then， the planning region is divided into different geographical zones， and the charging demand coefficient in each zone is determined. These zones with higher charging demand coefficients are selected as the candidates for installing charging facilities， and the demands for the charging facilities in these candidate zones are also determined. Finally， the planning scenario of EV charging facilities in Hangzhou is employed to illustrate the essential features of the developed method.
Electric vehicle （EV） is a significant point for national strategic high point and sustainable development. The industry can be promoted relaying on the construction and development of the charging and swapping service network. As an additional terminal of distribution network， leading to load demand increase， the service network affects but also being limited by the distribution network. The complicated technology and economic dynamic evolution system needs to be studied. In this paper， regarding the typical development stages “demonstration-fast growth-stable development”， charging or swapping load characteristic and analogy， charging or swapping infrastructure deployment， planning incorporating different networks etc. were proposed and discussed. Furthermore， the key technology， problems， and the road map were pointed out.
The ambient temperature has prominent impact on auxiliary power load， battery performance and traffic conditions of electric vehicles （EVs）， thus leading to different charging demands. Quantifying the influence of ambient temperature on charging demands is of great significance to analyze the impacts of EV charging on power grids and plan appropriate charging facilities， etc. A charging load calculation method considering temperature factor is proposed in this paper. The Monte Carlo simulation method is adopted to calculate the total charging load using the data of available range and driving demand of EVs. Taking Guangzhou city as example， simulation results show that EV charging load changes with different ambient temperature， and charging load at a higher or lower temperature day is much higher than at the normal day； charging load of different kinds of EVs are influenced by temperature to different extents and temperature has a more notable influence on electric buses which have a longer daily driving mileage.
Electric vehicle charging load forecasting is the precondition for charging infrastructure construction and charging load coordination control. In this paper， considering the stochastic charging behavior， the parking rules of the different functions areas are analyzed， the spatial distribution of different types of electric vehicles are predicted， and the influential factors are analyzed furthermore. The predicting model is set up as a rusult. The overall daily charging loads at different scenarios are calculated by Monte Carlo simulation. Results have shown that the difference of charging load features for different districts is obvious， and the proportion of using quick charge is higher， the difference of peak and valley is greater. According to the predicted results， not only can we guide charging time and place reasonably， but also provide the basis for charging infrastructure construction.
As the charging of electric vehicles is full of randomness and complexity， the large-scale application of electric vehicles is bound to bring a series of problems to the distribution network， which has become the research hotspot in the domestic and foreign scholars and research institutions. Based on a large number of the measured data on charging load of electric vehicles， choose the charging start time and duration of the charging as two key factors affecting the time distribution of charging load， combined with the analysis of the uncertainty of user charging behavior， build time distribution model of charging load of electric vehicles. According to this， divide the charging load area and the time and space distribution model of electric vehicle charging load was established. Through the example analysis， the impact of charging load of electric vehicle on the voltage drop， power loss and load curve of local distribution network was researched.
Electric vehicles provide a significant opportunity for reducing the consumption of fossil energy and the emission of carbon dioxide. With more and more electric charging facility integrated in the power systems， the impact on the power system distribution network and power quality cannot be ignored now. This paper analyzes the typical mode of charging infrastructure integrating to the distribution network，the prediction of the power demand and power load of the charging infrastructure， and the acceptance ability of power grid. The influence of charge load in different scenarios is analyzed， including residential areas， public parking， exclusive bus stations and exclusive taxi stations， and then the principles of power grid construction planning are proposed， which will provide references to large-scale electric vehicle charging facility integrating to distribution network.
A large number of electric vehicles （EVs） accessing to distribution network， is bound to cause a great influence on distribution network. Based on Monte Carlo simulation method， this paper calculated the charging load. According to the typical structure of actual distribution network in Beijing， this paper firstly analyzed the impact of EV’s orderly charging on power grid under different permeability， and then presented orderly charging method with grid-user side two-way charging as target. The proposed orderly charging method was compared with disorder charging method， whose results showed that the orderly charging could play an important role in load shifting.
Because disorderly charging posed a huge threat to the stability of power grid， the comprehensive control system of charging station was established. For the reason that both the power distribution and the battery characteristic should be considered during charging planning， a control method of power and time allocation （PTAICM） was proposed for charging station， in which the charging control process was converted to short time approximate linear programming problem， through theoretic modeling. The test result proves that it can meet the basic charging requirements of users， as well as minimize the impact on the stability of power grid and battery life.
As the electric vehicle （EV） charging service provider， aggregator is the important coordinator between the grid and EV users. In this paper， a decentralized optimization charging model based on the Lagrangian relaxation method was formulated from the perspective of EV aggregator， which took the maximum charging profit of the aggregator as target with considering constraints: users’ electricity demand， charging time and available capacity of distribution transformers， etc. The implementation mechanism and process of the decentralized optimization charging strategy were also explained. Then， Monte Carlo method was used to simulate the charging situations of EVs， and based on this simulation， the load curve， economic benefits and computational efficiency under uncoordinated charging， centralized optimization charging and decentralized optimization charging modes were compared and analyzed. The results show that the decentralized optimization charging using the Lagrangian relaxation method can get the approximate charging profit as the centralized optimization charging and the decentralized method possesses higher computing efficiency， so it is suitable for actual application.
Electric vehicles （EVs） are very likely to be dispatched by the power grid in the form of aggregation in the future， e.g.， the EVs in a large charging station being regarded and dispatched as one aggregation. After receiving the dispatch order from the power grid， an aggregator of EV aggregation should optimize each EV’s charging power to realize the dispatch order with regard to the aggregation， which is defined as a tracking problem. The tracking problem is a large-scale optimization problem which is hard to solve in a centralized manner. A hierarchical decentralized optimal algorithm was proposed to solve that problem. In the proposed algorithm， the aggregator sent coordination messages to EVs， while each EV solved a local small-scale optimization problem in a distributed manner and returned messages to the aggregator until the iteration process finished. To further enhance the computational efficiency， the sub-problem regarding the aggregator and each EV was deeply studied and its algorithm was improved. The numerical experiment results show that the proposed method has fast calculation speed， and is especially suitable for the large-scale tracking problem inside an EV aggregator.
The charging load of large-scale electric vehicles （EVs） is high， fluctuant and uncertain， which will bring negative effects on power grid， such as increased peak load， voltage fluctuations. To reduce the negative effects caused by EVs， this thesis proposes the coordinated charging strategy for battery in EV charging and switching station. By fitting the relationship between state of charge and equivalent charging time， and that between charging power and equivalent charging time， the charging characteristics of switched battery can be obtained. Based on the charging characteristics， the coordinated charging strategy for battery in EV charging and switching station with dedicated line is established to optimize the charging starting time of each battery. The objective of the proposed strategy is to minimize the sum of squares of the substation， and the number of battery chargers， EVs’ needs for batteries， power limit of EV charging and switching station and substation are all taken into account. The proposed methods of charging load forecasting and coordinated charging strategy are applied to an EV Charging and Switching Station， Shandong.
Nowadays V2G had been employed in large scale as the major way the electric car connect with the grid. However， there had been so many problems that in the V2G mode， such as the huge complex connection calculation models， difficulties in controlling， etc. This should be a huge problem on the way of electric car employed in a bigger scale. Compared with V2G， the mode of B2G could help to solve the questions mentioned above. And in this paper， a novel strategy of electric vehicles in B2G operation mode has been discussed. Taking the real-time operating condition into account， the strategy would provide an optimized solution of regulated power plan for charging stations， which run the economic maximization as the goal. A declaration of regulated power plan would be employed in the strategy mentioned above， which make the vehicles and the grid interact actively. The result of demonstration in some certain charging station in Yinchuan has proved that the strategy is effective and beneficial.
With the shortage of energy supply， it is imperative for electric vehicles to develop rapidly. Large-scale unordered charging of electric vehicles will bring about negative impacts on power grid. Therefore， this paper firstly proposed the operating mode of integrated power station， and constructed the control model of virtual power plant containing electric vehicle integrated station with charging， exchange and storage， and interruptible loads. Secondly， this paper used binary particle swarm optimization algorithm to realize the economic scheduling of virtual power plant， with taking the minimum operation cost as the scheduling target. Finally， the feasibility of the proposed scheduling scheme was verified by simulation example. The results show that under the control of the virtual power plant， the electric vehicle integrated station with charging， exchange and storage and the interruptible loads can cooperate with each other， which will greatly relieve the strain on the peak and make the system more effective.
This paper proposed a charging control strategy for electric vehicles （EVs） based on demand response， in which the threshold of charging price was set according to the real-time price information in order to reduce charging costs. At the same time， this paper studied the power system unit commitment problem containing large-scale EVs. On this basis， the economic scheduling model of EVs was established based on the demand response according to the prediction of the EV users’ behavior characteristics， which took the maximum profit of power grid corporation as the goal and optimized the charging price of EVs to transfer charging load. Simulation result shows that the proposed economic dispatch model can reduce the peak-valley ratio， and significantly reduce the operation cost of the system compared with the disorderly charging scenario， which can realize the economic dispatch of large-scale EVs access to power grid.
A large number of electric vehicles （EVs） getting connected to power grid need feasible control architecture and optimization algorithm. In order to optimize the charging and discharging management of EVs， this paper first introduced the concept of EVs aggregator， and then proposed hierarchical control architecture for EVs. Based on the hierarchical control architecture of EVs， this paper constructed a bi-level optimization control model for EVs to achieve the goal of valley-filling. In order to avoid the difficulties in solving the optimization problem with the increasing of EVs， an improved solution algorithm was proposed， which decomposed the high-dimensional optimization problem into many low-dimensional ones， so has good convergence property and could greatly improve the computational efficiency. Finally， the effectiveness and practicability of the proposed model and improved algorithm were verified through different case scenarios.
According to the problem of system frequency instability caused by large-scale intermittent renewable energy， electrical vehicle （EV） was used as valid demand response （DR） resource to provide ancillary load frequency control （LFC） service for power system. On the basis of the analysis on user’s behavior characteristics in ancillary LFC service impacted by electricity price， a dynamic LFC strategy with using variable participation factor was proposed for EVs， which could effectively evaluate the response ability of EVs in system frequency service under RTP （real-time pricing）. The simulation results show that under RTP， the LFC strategy of EV based on variable participation factor can provide dynamic ancillary frequency modulation service for power system with using the charging and discharging characteristics of EV load， and effectively support the dynamic frequency stability of power system.
EVs can participate into the frequency regulation of grid through vehicle-to-grid （V2G） technique when EVs are in the controllable state. In order to figure out EVs reaction when its receive frequency regulation single and how it influence frequency regulation， the research should be down to figure out the changes of controllable EVs' number. Now there is few research about the changes of controllable EVs' number in a period time when participate into grid frequency regulation. Based on that， a arithmetic which based on Monte Carlo simulation was proposed to figure out the changes of controllable EVs' number. The proposed arithmetic can figure of the changes of EVs' number in 24 time period a day. The proposed arithmetic gives a great help to those who do searching but cannot get the practical data of EVs.
In view of the increased demand of EV batteries as well as the performance requirement of charging device， a multi-functional modular （dis）charging system for EV batteries was proposed. On this basis， the control technology of the module which consisted of a three-phase AC/DC converter and an isolated dual-active-bridge DC/DC converter was studied. A coordinated optimization control was proposed for two-stages converters to improve the energy transfer efficiency and power density of （dis）charging module. Then， a detailed analysis was presented to discuss the condition of eliminating back-flow power of DC/DC converter under double phase-shift control， and the conclusion was verified through the simulation of power battery’s charging and discharging process. Furthermore， a new power feed-forward compensation of charging/discharging motor load was introduced in DC bus voltage control to improve both the dynamic and static performance. Finally， the superiority of the proposed control strategy was verified through the simulation.
To enhance the energy conversion efficiency of energy storage system， a hybrid sinusoidal-pulse current （HSPC） charging strategy based on Li-ion battery was proposed. Firstly， this paper discussed the principle of using wide frequency band current to enhance the energy conversion efficiency of Li-ion battery， based on the AC impedance spectrum characteristics of Li-ion battery. Then， the method that paralleled boost converter and phase shifting technology were applied to generate hybrid sinusoidal-pulse charging current was compared with constant current charging method and pulse current charging method. Finally， the simulation and experimental results show the effectiveness of the proposed method.
Taking the estimate strategy of the SOC （state of charge） in battery management system as research object， this paper used extended Kalman filter algorithm to established the simulation model in Matlab SimuLink/Stateflow， and verified the correctness of the model. The TargetLink automatic code generation tool of the dSPACE company was used to complete the model transformation， in-the-loop simulation and code generation. The generated code was downloaded to the debugging circuit board which used Freescale EVB9S12XEP100 as the CPU. The deviation of test results and theoretical results is in an acceptable range， the size of generated code， the stack usage can satisfy the demands of chip processing capacity and the software can operate stably.
As a regional active power station， electric vehicle intelligent charging-discharging-storage integrated station can provide auxiliary services for the grid by developing reasonable charging/discharging strategy considering the operating status of the grid. Generally， the grid operates in normal， alert， emergency， collapse， or restorative state， and correspondingly the intelligent integrated station may operate in normal， protective， or isolated state. The proposed standard operating procedures can be applied in different operating conditions. By considering the operating states of both the grid and the intelligent integrated station， we can combine the two systems together and make full use of the integrated station. In this way， the integrated station can provide services such as frequency regulation， reactive power compensation， and harmonic suppression for the grid. As a whole， the state assemblage of the integrated station is helpful to improve the power quality of the grid by considering the operation status of the grid.
Implementing coordinated charging management for electric vehicles （EVs） could optimize the load profile， and hence improve the security and economics of the power system concerned. Thus， how to develop a coordinated EV charging strategy and how to evaluate the effect of implementing such a strategy are important issues to be addressed. Given this background， a coordinated EV charging optimization model is firstly proposed with an objective of minimizing the system load variance for a given time period， and a highly efficient commercial solver， named AMPL/CPLEX， is employed to solve the optimization model， and the system load profile is finally attained. Subsequently， methods are developed for evaluating the potential economic benefits of coordinated EV charging management from four aspects， including no extra generation and transmission investment， reduced cost of distribution system capacity reinforcement， reduced cost of energy losses， reduced cost of purchasing ancillary services， with the free charging scenario as the datum. Then a method for comprehensive benefit analysis of coordinated EV charging management is presented. Finally， a 54-bus sample distribution system is employed to demonstrate the proposed method， and it is shown by simulation results that remarkable economic benefits can be achieved by implementing coordinated EV charging management.
The integration of photovoltaic （PV） generation system and electric vehicles （EVs） charging station is able to promote the local consumption of PV power， reduce the impact of charging load on the distribution network and the indirect carbon emission of EVs. A typical operation mode was proposed for a PV charging station of commercial building with considering the consistency of parking demands and charging demands. Taking the environmental， economic benefits and their influences on distribution network into consideration， this paper established a comprehensive evaluation index system for the long-term operation effectiveness of the PV charging station. Besides， a charging strategy was designed based on PV power consumption and service quality according to the daily actual operation scene. Finally， the simulation was carried out based on actual statistical data； the daily running effect and long-term comprehensive effect of PV charging station were analyzed and assessed.
According to the running characteristics of EV charging stations in our country， based on the relevant standards， technical specifications and realistic factors， the assessment index system of running energy efficiency was established for EV charging station from five aspects of power supply reliability， efficiency of charging equipment， power quality， operation conditions and ancillary services ability of grid. Then the running efficiency assessment model of EV charging station was proposed based on AHP-Entropy method. The quantitative indexes and qualitative indexes were normalized respectively； and the AHP-entropy method was used to comprehensively consider the subjective weight and objective weight of index， which could realize the comprehensive assessment of the running energy efficiency of EV charging station. Taking four EV charging stations in Wuhan as examples， the results of the running energy efficiency assessment show that the proposed running energy efficiency assessment model of EV charging station based on AHP-entropy method can provide references for the construction and economic operation of EV charging station.
Electric vehicles operating system is a complex adaptive system， it involves a variety of entities which are difficult to be modeled accurately due to their proactivity and social ability. In this paper， the design， implementation and application of a multi agent system （MAS） （electric vehicle） operating simulation platform was introduced. With this platform， behaviors of the entities such as system operator， vehicle drivers and charging facility operators， involving in EV operating and charging facility planning， were simulated and analyzed. Based on this platform， in which characteristics of passengers traveling， EVs charging and drivers shifting were comprehensively takes into account， a digital example for electric taxis in a city in South China was used to study the charging load characteristics. The simulation result was compared with that of a traditional method and demonstrates the advantages of multi-agent-system method.
