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Abstract
Large-scale development of plug-in hybrid electric vehicles (PHEVs) will have direct impacts on the distribution grid. PHEV charging impacts on the distribution grid are analyzed through a residential 10 kV feeder in a city from aspects such as impacts on load profile, power loss and voltage quality. Several scenarios of different penetration levels are discussed. The results indicate that under high penetration scenario, uncontrolled charging will pose great pressure on the grid and reasonable PHEV penetration may be helpful to the grid's economic operation. Smart charging method is explored which can optimize the chargeable power in each period according to the short-term load trend, in order to meet the charging requirements, achieve smoother load profile, less power loss and better voltage quality.
... The increase in number of EVs, while solving some challenges, pose a whole new set of problems especially as it concerns the electric power grid. An increase in EV charging station loads will lead to rise in peak demand, power loss, voltage instability, transformer life reduction and power quality problems (due to harmonics, voltage sag and unbalance) [32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50]. ...
... Shahnia et al. [43] showed that EVs have little impact at the beginning of a low voltage feeder, but have a major impact at the end of the feeder. Li et al. [44] also showed that with more than 50% EV penetration voltage starts to reduce at the end of the feeder. They also suggested a smart charging plan to mitigate the effect of voltage unbalance [44]. ...
... Li et al. [44] also showed that with more than 50% EV penetration voltage starts to reduce at the end of the feeder. They also suggested a smart charging plan to mitigate the effect of voltage unbalance [44]. ...
Concerns about the need for clean energy and the need to reduce green-house gases have led researchers and engineers to explore adoption of electric vehicle technology. Electric vehicles hold a promising future due to their efficiency, low maintenance cost and zero carbon emission. Unfortunately, due to metric range drawbacks associated with electric vehicles, large scale adoption of electric vehicles still remains relatively low. To solve this issue of range anxiety, optimal placement and sizing methods of electric vehicle infrastructure is essential. This paper presents a review of optimal siting of electric vehicle charging infrastructure. It discusses impacts of electric vehicle charging loads on the distribution network and how large scale electric vehicle penetration would affect the grid. Further, the benefits of electric vehicles on the distribution network as well as the integration of renewable energy resources are presented.
... In terms of the impact on the power grid, research [11] studies the impact of EV from the aspects of load, power grid loss and voltage, indicating that disordered charging will cause serious impact, while intelligent charging is conducive to economic operation. Research [12] proposed a probabilistic charging power model and simulated IEEE-33-node distribution network, indicating that large-scale EV would bring serious challenges to the power grid. In research [13], an EV charging load model was built to study the impact of EV random charging on distribution network, preparing for the study of orderly regulation and management of EV charging. ...
... Â maxðjP A:t À P av:t jÞ; maxðjP B:t À P av:t jÞ; maxðjP C:t À P av:t jÞ (12) where P A.t , P B.t and P C.t are the charging power of phase A, B, and C, respectively, and P av.t is their average value. ...
The impact of large-scale electric vehicle (EV) charging load on grids has become a hot issue all over the world, which is a strong random process with a variety of factors intertwined, and raises a major problem in research. Therefore, the article presents a decoupling analysis method which studies charging load and normal load independently and then carries out an integrated analysis with the power grid. Firstly, we calculate the average, maximum, minimum, fluctuating power of charging load and their parameters by Monte Carlo method, and get the function laws of vehicle scale and charging power on them. After that, in a scene of large penetration rate, it analyzes the influence of EV on the grid at all levels, and determines the possibility of main problems. By using this method, some conclusions are obtained. The method and the basic laws gained in this paper are universal, and can provide support for the future research of EV’s charging load.
... Furthermore, when the power line loading is low, reasonable access of EV charging load will improve the efficiency and economic operation of the line. But when the penetration rate of EV is high, the additional power demand will result in a heavy burden on transformers and lines, together with the increased power loss, which moves the state of line from the economic operating area to a high-cost operating area [77]. High-penetration of EV in the power grid may also cause serious voltage sag at line terminals, which affects the users' power quality at receiving end. ...
... By shifting partial peak load to a low point, 5% to 35% of the extra network investment would be saved. Hence, a smart charging method was proposed in [77] to minimize the sum of total loss and voltage excursion in the multi-period of the power grid. The method includes the constraints of loading rate, load demand and basic power flow equations. ...
Electric vehicles (EVs) have been rapidly developed during the last few years due to the
low-carbon industry and smart grid initiatives. Meanwhile, the impact of
large-scale EVs' integration on the reliability and safety of power grids is
becoming increasingly prominent. To address and solve these problems, challenges
on EV charging control have been presented. Besides, the EV charging load
modelling with improved accuracy and rationality is required. To investigate the
influencing factors of EV charging load, this survey summarises the existing EV
charging load modelling methods. In addition, a new research framework for a
scale EV evolution model of charging load is proposed, with an emphasis on
reducing the deficiencies of the existing research in dealing with the EV scale
development. Moreover, the future research prospect of EV charging load
modelling on power system planning, operation, and market design has also been
discussed.
... When massive EV charging loads are integrated into grid randomly, uncertain and bidirectional power will inevitably influence the distribution network, resulting in negative impacts on energy loss, characteristic of load profiles and node voltage [8]- [10]. Therefore, it is of great significance to optimize the planning schemes of EV charging facilities. ...
... Operation cost of charging facilities is closely bound up with the charging power of electric vehicles, and has little to do with regions. After calculating the charging power of each candidate site, the overall operation cost is shown in equation (8). ...
... Impacts of EV charging on distribution network load was analyzed in [5], without considering differences of charging power and duration demand of EVs. [6] and [7] presented intelligent charging, however, [6] ignored the owner's response degree to the intelligent charging, and charging power control of each EV in [7] was not easy to achieve. Acceptance ability of EV of IEEE-34 nodes distribution network was analyzed in [8], but it did not consider the TOU power price and smart charging. ...
... Impacts of EV charging on distribution network load was analyzed in [5], without considering differences of charging power and duration demand of EVs. [6] and [7] presented intelligent charging, however, [6] ignored the owner's response degree to the intelligent charging, and charging power control of each EV in [7] was not easy to achieve. Acceptance ability of EV of IEEE-34 nodes distribution network was analyzed in [8], but it did not consider the TOU power price and smart charging. ...
... The planning and construction of charging infrastructure is directly related to the promotion effect and scale of electric vehicles. The charging behavior of electric vehicles has great uncertainty and randomness in time and space [2] . When large-scale electric vehicles are connected to the power grid in disorder, their charging and discharging behavior will affect many aspects of the power grid, such as power system scheduling, distribution network peak and valley difference, power quality, etc. ...
... (4) In order to make the charge peak-to-valley difference as small as possible, the minimum power charging is used at the peak, and the maximum power charging is used in the low valley. Let F1, F2 and F3 respectively be the number of AC level 1, AC level 2 and DC charging devices accessed at peak charging load, and G1, G2 and G3 are the number of AC level 1, AC level 2 and DC charging devices accessed at low charging load, then the peak-valley difference function 2 f can be expressed as follows: ...
... According to the processing results in [31], the return time ( i.e. the initial time when the user accesses the charging station for charging,) satisfies the normal distribution, and its probability density function is (1) ...
... And, the electricity price distribution of each charging period is shown in Table I. The permeability of EV is the ratio of EV charging load to the maximum load of the line [31]. In order to better reflect the degree of user response, this paper uses the permeability setting method for reference and manually sets the responsiveness η to be equal to 0, 30%, 60% and 100% respectively for simulation. ...
... However, as the market penetration increases, uncoordinated charging of EVs will bring a variety of undesirable consequences to the power grid, charging facilities, and end users. For the power grid, such consequences include an "extra peak" of load on the grid, reduced voltage at some nodes in the grid, and increased network loss of the grid [5][6][7]. For charging facilities, such impacts are manifested in the reduced utilization and increased operating costs [8]. ...
This paper was intended to explore the mutual influences between electric vehicle (EV) charging and charging facility planning, to establish a two-stage model for optimizing the EVs’ charging and charging piles’ selection. In the first stage, the distribution pattern of the demands for EV charging, and various EVs were effectively grouped, in order to reduce the amount of computation for solving the second stage model. The goal of the second stage was to minimize the annual investment and electricity purchasing costs on the charging piles, and the coordinated optimization was carried out for EV charging and charging pile selection. The CPLEX and IP_SOLVE packages were used in MATLAB (R2014a/64 bits) to solve the established optimization model. The simulation results showed that, compared with the scheme for selecting the charging pile under the typical charging pattern (TCP), the total cost of the charging pile could be reduced by 6.32% with a scheme under the optimized charging pattern (OCP), thereby promoting the coordinated development of both the EVs and charging facilities.
... Compared to conventional cars, electric vehicles have incomparable advantages in promoting energy conservation and emission reduction, reducing operating costs and generalizing new energy utilization [1]. With EV abundantly available, it will have influence on the security and stability of power gird, and also bring hardship to the repair and maintenance of EV chargers [2][3][4]. Monitoring and evaluating the operating state of EV chargers timely and accurately, can help deal with the fault and optimize the maintenance strategy of EV chargers. ...
... It would not need to transform 10 kV distribution grids under the AC slow charging mode for vast majority of communities and commercial office buildings, only if EVs are accounting for over 20% of total automobiles. Moreover, a larger number of EVs, a higher charging rate and more random charging behaviors will intensify the reform of the distribution grids under the DC fast charging mode [64]. ...
China had set an ambitious development target of electric vehicles (EVs) to mitigate the environmental pollution. However, the actual situation of EVs far lagged behind the goals. This paper analyzes the elements impeding EVs' development, which are identified into four contributors, including deficient EV subsidy policies, embarrassed EV market, local protectionism, and unmatched charging infrastructure. Based on the actual situation of China, this paper discusses corresponding policy suggestions and explores the alternative roadmap of EVs. In the initial development stage of EVs, it is important to select the appropriate charging mode for EVs according to different characteristics across users. Moreover, the development of hybrid electric vehicle (HEV) may open the EV market faster than battery electric vehicle (BEV). In addition, the low-speed EVs may be a good choice for the rural market and should be well developed. With the promotion of EVs, China central and local governments should make rational policies to promote EVs' development, which is the crucial force to drive the uptake of EVs.
... Electric vehicles (EVs) can help to reduce carbon emission, however, it will also cause serious effects on power quality, reliability and node voltages [1][2][3][4][5][6]. Transfer capacities of distribution networks can be increased, as well as reliability and integrated capacities of distributed generations (DGs), because EVs can be used not only as loads, but also as distributed stored energy [7]. ...
... The EV penetration rate is the ratio of the EV charging load to the maximum load. Under different penetration rates, the influence of random charging of EVs on the distribution network is studied in [23]. In order to have a better reflection of the users' response, we made reference to the penetration rate-setting method and carried out simulations with the responsiveness η being 0, 30%, 60% and 100%, respectively. ...
... As a prominent representative of renewable energy development, electric vehicles have replaced traditional fuel vehicles and became an important trend leading the development of the automotive industry. In the future, the mass access of electric vehicles will have a great impact on the stable operation of the power system [1][2][3][4][5], there are mainly voltage, grid loss and harmonic research at the level of system distribution network at present. Wang Hui uses Monte Carlo algorithm to simulate the charging and discharging power curve of electric vehicles by analyzing the influence of load, voltage and network loss in the system according to different electric vehicle penetration rates [6]. ...
... Several charging strategies have been proposed to reduce the impacts of PHEV charging load on power system networks. In [14], [16], [20] smart charging based on minimization power losses is discussed. This technique is focused to reduce power loss in the network. ...
Uncontrolled PHEVs charging will cause severe impacts on a power system network, especially on the distribution system; i.e. feeders, cables and transformers overload hence shortened its life. In this paper, PHEV charging strategy namely SOC-based charging has been proposed. This charging strategy focused on user needs, i.e. full charged the battery within plugged-in time frame considering maximum charging rate from the standard outlet. Moreover, it will reduce the peak loads as well as improving the load factor on a power system network. Real vehicle travel data from National Household Travel Survey (NHTS) is used to represent PHEV types, miles driven and its final arriving times. This proposed technique also comprehensively used to present the impact of charging PHEV on power system networks considering PHEV battery sizes and maximum charging levels. Vehicles Charging Load Profile (VCLP) is developed and implemented in IEEE 30-bus test system that represents a portion of American Electric Power System (Midwestern US). Normalization technique is used to represent real time loads of IEEE 30-bus test system. Comparative study has been performed with respect to uncontrolled charging technique. Results indicated that the proposed charging strategy not only achieved the required battery capacity but also has improved peak load and load factor thus reduces impacts on power system networks.
... In the discorded charging cases, it will enlarge the load difference between peak and valley, which will need extra power to meet charging load requirements [18][19]. Secondly, terrible charging load may increase the voltage deviation [20][21][22][23] to cause the asymmetry of three-phrase voltage [24,25] and incremental losses of distribution network [26,27]. Thus, economic loss could be made. ...
Large scale access of electric vehicles will bring huge challenges to the safe operation of the power grid, and it's important to control the charging and discharging of the electric vehicle. First of all, from the electric quality and network loss, this paper points out the influence on the grid caused by electric vehicle charging behaviour. Besides, control strategy of electric vehicle charging and discharging has carried on the induction and the summary from the direct and indirect control. Direct control strategy means control the electric charging behaviour by controlling its electric vehicle charging and discharging power while the indirect control strategy by means of controlling the price of charging and discharging. Finally, for the convenience of the reader, this paper also proposed a complete idea of the research methods about how to study the control strategy, taking the adaptability and possibility of failure of electric vehicle control strategy into consideration. Finally, suggestions on the key areas for future research are put up.
The reserved battery number and the charging duration are main factors to affect the energy supply capacity of electric bus battery swapping station. Based on the analysis of vehicle flow, two formulas are presented to describe required battery amount and charged battery amount respectively. Moreover, with analyzing the relation between the two formulas, a charging control method for the peak period is provided. According to the field test data and statistical results of the electric bus swapping station for 2008 Beijing Olympic Games, the procedures of optimal strategy for economic operation have been given. Then a computer simulation program is prepared to verify the strategy. Simulation results show that the proposed strategy can reduce power consumption of peak periods and electricity costs markedly while it meets the condition at swapping demand. In addition, the algorithm and boundary conditions are very clear, and it is easy to be embedded into a charging management system to implement economic optimization for bus battery swapping stations.
Based on power supply modes for three typical residential communities, firstly the power quality indices and the K coefficients of transformers at the points of common coupling (PCC) and low-voltage buses of community power supply systems are calculated; then the impact of wide-range integration of charging station with residential communities on power quality and the existing residential community power equipments' ability of accommodating EV as well as the renovation of residential community power supply system are analyzed in depth; finally, the power supply mode for residential community suitable for wide-range connection of EV charging load and the characteristic condition of EV's on-board charger, which is permitted to be connected to the community power supply system, are put forward. Through this research it is found that power supply system for villa community can bear EV charging load and daily household load simultaneously; the power supply system for multi-storey residential community and that for high-rise residential community cannot bear the direct connection of EV's on board chargers, so it is necessary to configure independent power supply device for them. Using above-mentioned reasonable power supply modes both power quality indices for household consumption in different residential communities and the power quality index at the PCC can meet the demand on power quality even though the medium-sized on board changers are connected with the power supply system.
With the great development of distributed generator (DG) and electric vehicle (EV), it is of great significance to carry out collaborative research of DG and EV accessed to distribution network. Based on the coordination of benefits between distribution companies, DG investors and social communities, this paper comprehensively takes into consideration the operating cost of distribution companies, investment cost of DG investors, and environmental benefit of DG and grid investment saved by vehicle to grid (V2G). A mathematical model for DG optimal planning in distribution network involving EV is developed based on chance constrained programming, with a hybrid coding based improved adaptive genetic algorithm to solve the model. In the calculation process, uncertainties of load forecast, output power of DG and charge or discharge power of EV are fully considered. And the mathematical model of EV influence on the grid maximum power is proposed. The constraints in the model are checked by probabilistic power flow based on semi-invariant and Gram-Charlier expansion theory. Finally, DG planning under different confidence level constraints is respectively computed within an actual distribution network to verify the effectiveness of the mathematical model and corresponding algorithm proposed. It can be concluded from the simulation results that with the reduction of confidence level in the mathematical model, the DG planning capacity in the system has significantly increased, so that the system loss is reduced and environmental benefit is increased. However, the risk of node voltage and branch power constraint violation has also increased, which leads to making higher requirements on real-time control research on the distribution network in the future.
The construction and operation of electric vehicle (EV) charging station is the basic project in the EV industry development. This paper presents a dynamic optimizing method to improve the load characteristics of the distribution system based on the particle swarm optimization (PSO) algorithm. The optimizing strategy is operated by minimizing the load variance for a period as objective function, and the scale of charging station and the demands of customers as constraints. The customers' travel performance is simulated by the stochastic method of probability distribution. And load characteristics of coordinated and uncoordinated charging are compared in different permeability. The conclusion shows that the dynamic optimizing strategy takes effect in mitigating load variance, optimizing distribution system characteristics and shifting peak load.
An online monitoring, analysis and evaluation system for EV (Electric Vehicle) charging station is designed and developed, which adopts the PCI-bus-based multi-DSP structure and consists of multi-DSP acquisition terminal, vehicular terminal, industrial PC and interfacing circuits. The voltages and currents of PCC (Point of Common Coupling) and chargers are collected in real time, based on which, different power quality indices are calculated. All monitoring data are gathered via PCI bus, based on which, the operational characteristics of transformers and chargers are analyzed. The operating and charging information of EV is received via GPRS and the radar map method is applied to comprehensively evaluate the conditions of EV. The probability distributions of EVs' start charging time, initial state of charge and daily mileage are statistically analyzed. The results of practical operation show that, the system is stable and reliable, providing huge practical and reliable data of operation and evaluation for the operation and planning of EV charging station. ©, 2014, Electric Power Automation Equipment Press. All right reserved.
With the gradual increase of distributed generation (DG) and electric vehicle (EVs) integrated in the distribution network, traditional models for reconfiguration canhardly reflect the randomness and volatility. For this reason, a probabilistic scenario model of reconfiguration considering wind power and electric vehicle is developed first. Then, the probabilistic load flow of each scenario is calculated respectively. The model is simplified on the precondition of ensured accuracyto avoid combinatorial explosion, embodying the adaptability of the ever-increasing DGs and EVs. Finally, distribution network reconfiguration using the improved biogeography-based optimization algorithm is proposed, the improved codification strategy, the cosine migration model and the mutation operation are introduced to improve the search efficiency and bypass local optima. The proposed algorithm has shown advantages over other traditional artificial intelligence algorithms in 20 times of simulation of the IEEE 69-bus case.
The influencing factor set of new-type town distribution system is put forward and the interactions among them are analyzed to form the reachability matrix, according to which, its ISM (Interpretative Structural Model) is constructed. In order to directly reflect the impact of each factor on the new-type town distribution system, an extended AHP (Analytic Hierarchy Process) is proposed to calculate the weight of each influencing factor in the model. The main factors influencing its development and construction are analyzed, which provides the reference for the development and construction of China's new-type town distribution system. Two analysis cases verify the practicability and adaptability of the proposed model. © 2015, Electric Power Automation Equipment Press. All right reserved.
Three-phase unbalance may occur in distribution networks with large-scale charging loads of electric vehicles (EVs) plugged in, which significantly threatens the operation of power networks. Most coordinated EVs charging strategies are based on the assumption of single-phase power networks to the neglect of three-phase unbalance problems. A coordinated charging strategy for EVs considering three-phase load balance is proposed. In the outer layer of the proposed strategy, the three-phase backward/forward sweep load flow algorithm is used to iteratively update the node voltages. In the inner layer of the proposed strategy, a three-phase coordinated EV charging optimal model is created and solved based on the updated node voltages. By optimizing the charging power and charging periods of EVs, the objectives of the optimal model, power loss reduction and the three-phase load balance, are achieved. Simulation results show that the proposed strategy can eliminate the three-phase unbalance problems, reduce power losses and flatten the load curve, guaranteeing the economics and security of operation of the power network.
With the reasonable control strategy and enough capacity, the integrated EV (Electric Vehicle) station of intelligent charging, discharging and storage can be used to locally compensate the reactive power. By a control algorithm based on the operating characteristics of its equivalent voltage source, the integrated EV station operates in the equivalent generator mode or SVG (Static Var Generator) capacitive mode. The reactive power and voltage regulating characteristics of its inverter are studied and the value-added strategy and emergency control strategy are proposed. Analysis of an actual example proves that the integrated EV station has a better performance in the reactive power and voltage control. ©, 2014, Electric Power Automation Equipment Press. All right reserved.
It is a serious problem that how to distribute large-scale electric vehicles coordinated charging load with the consideration of every single electric vehicle's charging demands and user intention. Firstly, a coordinated charging strategy for electric vehicles is proposed. Secondly, based on meeting the intention of every electric vehicle user, aiming at minimizing charging times of electric vehicles, charging arrangements for electric vehicles are decomposed to every electric vehicle with the historical driving distances and battery real-time states made as the weighted coefficient. Finally, practical data are applied to the simulation. The results show that with the consideration of application characteristic, charging state and charging times of every electric vehicle, the charging strategy of every electric vehicle is arranged based on the satisfaction of the charging load required. At the same time, the charging times are reduced. The distribution principle proposed is reasonable. ©, 2015, Power System Protection and Control Press. All right reserved.
The detailed parameters of the integrated EV(Electric Vehicle ) station and terminal can be acquired by the monitoring and control system according to the information flow distribution of integrated EV station. IOT(Internet Of Things) and GPS(Global Positioning System) technologies are applied to monitor the operating state handle the fault of the internal and external batteries of integrated EV station. The energy level information of integrated EV station and the information of power exchange between it and power grid are analyzed and fused. A strategy of grid-connection control is proposed based on the fused information, together with their operating information. A calculative example shows that the proposed control strategy based on the information fusion technology has positive effect on the operation of integrated EV station and power grid. ©, 2015, Electric Power Automation Equipment Press. All right reserved.
Large scale of electric vehicles (EVs) integration will have a significant impact on the operation and planning of distribution network, this paper presents an assessment methods of distribution network's ability of admitting EVs. Based on scenarios of different types EVs integration, which are simulated by Monte Carlo stochastic methods, this paper describes a mathematical model of EVs load prediction. According to the distribution network topology and the mode of power supply, power supply region is divided. Considering the spatial and temporal characteristics of EV charging load and the power supply region, loads are distributed in a hierarchy pattern. Calculating network's total load and judging whether the total load is overload. The probabilistic model based on the results of three-phase flow assesses the operation situation of distribution network from voltage excursions and network power loss. The IEEE 123 node radial distribution feeders is taken as an example for flexibility evaluation. This method is a powerful tool for distribution network operation and planning. ©, 2015, Power System Protection and Control Press. All right reserved.
With large-scale electric vehicles (EVs) integrated into the power system, how to optimize EV charging power in real time to avoid incremental peak load and achieve valley-filling will be important. The regular real-time charging optimization as well as the vehicle charging prediction method is reviewed at first. Since vehicle charging (especially vehicle fleet charging) is predictable, a new real-time charging optimization model is proposed on the basis of the regular method with the consideration of the prediction model of incoming EVs. The new model is solved with receding horizon optimization, obtaining the current optimized charging power of plugged EVs. Through case study with various prediction accuracies, it can be seen that the proposed method always approaches the optimal solution to valley-filling. Moreover, compared with regular method, the proposed method would make a greater improvement of optimization result in the case of more diverse EV plug-in time.
With rising oil prices, green appeal, and development of electric vehicle technology, the size of the electric car industry is gradually expanding. However, the rapid development of electric vehicles, the battery-powered electric vehicles, electric energy needs regular supplement. The electric power requirement has brought tremendous pressure to the electricity market which is crisis under the current situation. However, the battery of the electric vehicles and other electric power source, such as solar power stored in battery, can also be used to meet the shortage of grid. Electric vehicles can get supply from other vehicle's battery or solar power stored in battery. The electric vehicle charging outside the grid market, vehicle-to-x electricity trading market, will be formed in the near future. This paper analyzes the vehicle-to-x electricity trading mode among users. The trading parameters and transaction flow are discussed in this paper, and the trading rules are given.
An EVs(Electric Vehicles) charging optimization model based on the safe operation of distribution network is proposed, which takes the EVs in a distribution transformer district as a small "assembly", the minimum power loss as its objective and the node voltage, line power flow, distribution transformer capacity, charging power increase and charging energy balance as its constraints to optimize the charging power of the "assembly" in the slow charging mode. The district service provider is responsible for the supervision of EV charging behaviour. The primal-dual interior point method is adopted to solve the model. The calculative results of IEEE 33-bus system, PG&E 69 system and an actual 119-bus system show the excellent convergency and optimization effect of the algorithm. The dynamically balanced charging power effectively reduces the network loss, smoothes the load fluctuation, improves the terminal voltage level, avoids the short- term voltage quality decline, feeder heavy load and distribution transformer overload, and improves the economy and security of distribution network operation. ©, 2015, Electric Power Automation Equipment Press. All right reserved.
Nowadays, several countries have adopted an energy transition policy to achieve carbon targets and decarbonize transport while improving their electricity mixes. Electric vehicles are ubiquitous, considering its role in the energy transition as a promising technology for large-scale storage of intermittent power generated from renewable energy sources. However, the widespread adoption and commercialization of EV remain linked to policy measures and government incentives. Here in this work, we review the current bottlenecks and key barriers for large-scale development of electric vehicles. First, the impact of massive integration of electric vehicles is analysed, and the energy management tools of electric energy storage in EVs are provided. Then, the variety of services that EVs may provide is investigated. We also, highlight how the optimal placement and sizing of EV charging infrastructure can plays a crucial role in electric vehicle development. The different methods for Li-ion battery states estimation and cells characterization are outlined. Furthermore, we present the different incentives to accelerate EVs adoption. And finally, we provide insightful suggestions and policy recommendations for future studies. The work presented in this paper will be very beneficial for policymakers seeking to promote electric mobility, and advance sustainable EV technologies.
The characteristic of the electric vehicle (EV) power is summarized. The Monte Carlo method is used to simulate the charging and discharging behaviors of EVs, and the load characteristic curves of plug-in EVs of different scales are obtained. The demand characteristic of uncoordinated charging EVs and the capacity curve of controlled charging and discharging EVs in the vehicle-to-grid (V2G) mode are analyzed. Then the multi-objective economical dispatch model for microgrid considering plug-in EVs is developed. Take the one-day economical dispatch of a certain area, which shows the optimal dispatch results of different strategies and different objective functions are obtained with the priority list based on the software package of Visual C++. Finally, the availability and feasibility of the model is verified through a comparative analysis.
Nowadays, energy problem has become increasingly prominent. How to systematically coordinate the relationship between various energy sources and to use energy efficiently are important issues for scholars in various countries. There is no doubt that Energy Internet is development trend of current grid. Also it is an important part of future power grid. The development of Energy Internet is summarized and the concept of Urban Energy Internet is proposed. This paper points out that Urban Energy Internet is the basic unit of national ubiquitous smart grid. A set of influence factors of Urban Energy Internet is put forward. An analysis model of the influence factors of Urban Energy Internet is constructed based on the Interpretative Structural Model and the Analytic Hierarchy Process method. The influence factors of Urban Energy Internet in an urban area are analyzed to provide a reference for the optimal allocation, the construction planning and operation control mode of Urban Energy Internet.
Electric Vehicles (EVs) portray the important role in reduction of greenhouse gases and fuel utilization. The spike in number of EVs put large burden of power on grid system. This enormous power demand causes serious issues on the performance of power system and can leads to power failure. Optimal management strategies are required to alleviate such issues and to maintain the continuous supply of power. Due to integration of EVs various issues related to grid system are reviewed briefly in this paper. This paper reviews different management strategies to minimize the impacts of integration of EVs into grid system. Decentralized coordination helps to reduce load variability and stability issue of grid due to EVs but it needs accurate forecast of EVs travelling pattern. Central coordination reduces load variance, voltage variations, power losses, computational complexity and helps in determining the EVs charging location but it has less customer stratification. Integration of renewables reduces the burden on local grid, optimizes the production cost and enhances the charging capacity but it has intermittent power supply. EVs charging functioning reduce the power losses and waiting time but require huge investments. Public policies maximize the overall profit but it requires proper load managements. Among these methods it is found that centralized coordination can be more effective in solving EVs integration issues. The optimal power, energy capacity and location of EVs in centralized coordination can accurately found by optimizing the objective functions. Centralized coordination becomes more effective to resolve the EVs issues when addition of smooth power from renewables is included in the system.
The energy utilization optimization strategies in a smart house without and with vehicle to home (V2H) and/or home distributed photovoltaic (HDPV) in Shanghai are investigated in detail for the efficient household energy utilization and the reduction of net electricity expenditure. Such influences as EV travel distances, weather conditions and different PV subsidies are also taken into account. The results show that transferring valley electricity and PV by V2H can not only improve the utilization rate of valley electricity and PV, but also obtain considerable economic benefits. Transferring PV by V2H can get more revenues than transferring valley electricity by V2H. The energy arbitrage of V2H decreases with the increase of the EV travel distance. The HDPV-V2H mode in the case studied can completely cover the electricity demand of the household load in sunny and cloudy days without additional grid electricity while the combination of PV with transferred valley electricity by V2H is enough to support the household load demand in rainy days. The positive return of HDPV still can’t do without the support from government’s subsidy in Shanghai in the coming time. However, the HDPV-V2H mode can improve the benefit of HDPV. Meanwhile, there are a lot of EVs in Shanghai, charging with green power in priority. The HDPV-V2H mode can promote the synergetic development of HDPV and EVs in Shanghai.
In order to adapt to the access of high penetration and large-scale distributed generators (DGs), the active distribution network (ADN) has become the research trend of current and future smart grids. The influences of DG access, demand-side management and topology changes on the voltage distribution and voltage stability of distribution network in the AND background are reviewed. The reactive power and voltage control method of ADN are summarized from the perspective of centralized and decentralized control. According to an analysis of the current research status, some of the problems and shortcomings of research on reactive power and voltage control method of AND influenced by various factors are briefly treated. Some problems in research on the AND reactive power and voltage control method are pointed out.
As the electric vehicle(EV)charging is playing an important role in distribution network, it has attracted more and more attention. In order to clarify the relationship between the operation mode of EVs, peak charging load and peak power load of grid, this paper defines two key parameters: coincidence factor and mutual coincidence factor. The variation tendencies of these two parameters under different EVs scale and charging rate are also analyzed. Based on the characteristics of EV charging load and the power load of distribution network in residential area, an evaluation method for distribution network supportability is proposed. Finally effectiveness of the evaluation method are verified by distribution network in residential area. The results show that by choosing the capacity of transformer properly, the ability of the distribution network for the integration of EV can be greatly improved.
With large integration of plug-in hybrid electric vehicle (PHEV) and distributed generation (DG), a good regulation ability of the power grid is required for PHEVs random charging and DG's intermittency. Considering safe and economic operation of the power grid and charging cost of PHEV owners, vehicle-to-grid (V2G) is a multi-objective and multi-constrained optimization problem by nature. A multi-objective optimization coordination model is proposed for PHEV and DG integration. Objectives of this model are maximum synthetic load ratio, minimum node voltage deviation and power loss ratio, lowest V2G service cost of the grid and charging cost of PHEV owners. By dynamic regulating PHEV charging and discharging power, power fluctuation between load and DG can be matched well and the impact of DG intermittency on the power grid will be de creased. A real 10kV feeder is simulated.
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