Energy Management for a Residential Microgrid Using Wavelet Transform and Fuzzy Control Including a Vehicle-to-Grid System

This paper presents the design and implementation of an energy management system （EMS） with wavelet transform and fuzzy control for a residential micro-grid. The hybrid system in this paper consists of a wind turbine generator, photovoltaic （PV） panels, an electric vehicle （EV）, and a super capacitor （SC）, which is able to connect or disconnect to the main grid. The control strategy is responsible for compensating the difference between the generated power by the wind and solar generators and the demanded power by the loads. Wavelet transform decomposes the power difference into a smoothed component and a fast fluctuated component. The command approach used for fuzzy logic rules considers the state of charging （SOC） of EV, renewable production, and the load demand as parameters. Furthermore, the command rules are developed in order to ensure a reliable grid when taking into account the EV battery protection to decide the output power of the EV. The model of the hybrid system is developed in detail under Matlab/Simulink software environment.

Development of Vehicle-to-Grid Systemto Regulate the System Parameters of Microgrid

This paper proposes a vehicle-to-grid(V2G)system interfaced with a microgrid that is effective at regulating frequency on a microgrid over a 24-h cycle.A microgrid is designed and divided into four components.The first component is a diesel generator,which is used to act as the base power generator.The second component consists of renewable energy(RE)power plants,which include solar photovoltaic(PV)and wind plants.The third component is a V2G system.The last component is the load connected to the microgrid.A microgrid is designed to be of sufficient size to represent a community of one thousand households during the day period of low consumption in the spring or fall seasons.A hundred electric vehicles(EVs)are modeled as base models to realize a 1:10 ratio for cars to households,which indicates a possible scenario in the near future.Detailed analysis of the active power,reactive power,voltage,frequency,and current is carried out.It is established that the proposed design of the V2G andmicrogrid effectivelymaintains systemparameters such as frequency and voltage within permissible limits with an error of less than 1%.Further,transient deviations in these parameters are limited to within 5%.A microgrid with V2G devices regulates the system frequency by mitigating load demand through coordinated control of conventional generation,solar PV plant generation,wind plant generation,power exchange with the microgrid network,and electric vehicles.The proposed microgrid and V2G are efficient for energy management and mitigation of intermittency and variability of RE power with improved performance.Variations in system parameters have been investigated by changing the operating scenario,and it has been determined that the error is limited to less than 5%.The study is effectively realized in the MATLAB/Simulink environment.

Vehicle-to-grid power system services with electric and plug - in vehicles based on flexibility in unidirectional charging

With proper power scheduling and dynamic pricing,a unidirectional charger can provide benefits and regulation services to the electricity grid,at a level approaching that of bidirectional charging.Power scheduling and schedule flexibility of electric and plug-in hybrid vehicles are addressed.The use of electric vehicles(EVs)as flexibility resources and associated unidirectional vehicle-to-grid benefits are investigated.Power can be scheduled with the EV charger in control of charging or via control by a utility or an aggregator.Charging cost functions suitable for charger-and utility-controlled power scheduling are presented.Ancillary service levels possible with unidirectional vehicle-to-grid are quantified using sample charging scenarios from published data.Impacts of various power schedules and vehicle participation as a flexibility resource on electricity locational prices are evaluated.These include benefits to both owners and load-serving entities.Frequency regulation is considered in the context of unidirectional charging.

Momentum Search Algorithm for Analysis of Fuel Cell Vehicle-to-Grid System with Large-scale Buildings

The design and analysis of a fuel cell vehi-cle-to-grid(FCV2G)system with a high voltage conver-sion interface is proposed.The system aims to maximize the utilization of fuel cell vehicles(FCVs)as distributed energy resources,allowing them to actively participate in the energy market.The proposed FCV2G system has FCVs,power electronics interfaces,and the electrical grid.The power electronics interfaces are responsible for con-verting the low-voltage output of the fuel cell stack into high-voltage DC power,and ensuring efficient power transfer between the FCVs and the grid.To optimize the operation of the FCV2G system,the momentum search algorithm(MSA)is employed.By applying MSA,the FCV2G system can achieve optimal power dispatch,con-sidering factors such as energy efficiency,grid stability,and economic feasibility.The proposed method is tested in MATLAB.The best MSA and dynamic load profile solu-tions are run for 24 h and the results show that 100%import of FCVs 51.0%more than 100%electric vehicle.Peak-cutting and vehicle-to-grid service revenue are 30.5%and 95.0%greater,respectively.Low discharge loss,high capacity,and high discharge power are the main advantages of FCVs.The benchmark FCVs ratio of 15%is used for sensitivity analysis.The findings reveal that the overall advantages of FCV2G are improved.Index Terms—Continuous conduction mode,DC-DC converter,discontinuous conduction mode,fuel cell vehi-cle,utility-grids,vehicle-to-grid.

Resilience Enhancement of Urban Energy Systems via Coordinated Vehicle-to-grid Control Strategies

Coordinated vehicle-to-grid(V2G)control strategies can sustain essential loads of an energy system during islanding,thereby increasing resilience.In this context,this paper investigates the resilience enhancement benefits of smart V2G control,the value of electric vehicle(EV)owner cooperation on system resilience,as well as the complementary effects of PV and EV interaction in an urban multi-energy microgrid(MEMG).By using a rolling horizon approach to optimize day-ahead operation of the MEMG and subsequently dispatching EVs,uncertainties in outage start time,EV arrival/departure times,and initial state of charge(SOC)are mitigated.Results show that smart V2G control can provide a substantial essential load curtailment reduction compared to a non-EV scenario,meanwhile,non-coordinated grid-to-vehicle(G2V)operation was shown to slightly burden the system with a slight increase in non-essential load curtailment.Investigations into the influence of EV cooperation on resilience showed that a high percentage of system-prioritized(SP)EVs could help greatly further reduce essential load curtailment compared to individual-prioritized(IP)EVs.Finally,the complementary benefits of smart V2G control and PV were demonstrated,showing a reduction in both PV and essential load curtailments with increasing numbers of EVs.Overall,the application of smart V2G control,especially with cooperation of EV owners,can drive significant resilience enhancement during islanding,while further benefits can be obtained through having a sufficient number of EVs to utilize high PV penetration.

基于区块链的电动汽车去中心化交易研究

随着分布式电源技术和新能源技术快速发展,参与电力交易的电动汽车和新能源发电用户数量不断增多。由于电动汽车和新能源具有随机性和不确定性,现有交易模式无法支撑交易需求。区块链具有去中心化、不可篡改等特点,可以有效解决车网互联系统(vehicle-to-grid,V2G)电力交易遇到的挑战。首先,基于区块链技术,提出基于组合拍卖和滚动撮合交易的交易规则,设计了滚动撮合交易模型。随后,基于组合拍卖和滚动撮合交易机制规则,设计了V2G的电力交易智能合约。最后,为验证所提方案的可行性,将智能合约发布到趣链区块链平台上,进行模拟实验。实验结果表明,本文所提方法能够有效提高交易成功率。

Vehicle-to-grid service development logic and management formulation

Vehicle-to-grid(V2G)is regarded as the effective way to reconcile contradictions between an electric power system and electric vehicles(EVs).A lot of research has been carried out to affect this,often based on different technical and trade model assumptions.The value of theresearch is dependent on how reasonable the assumptions it makes are.This paper presents a framework for analyzing V2G service development from a coevolutionary perspective in which the interactive relation between the diffusion of EVs and the upgrade of the distribution grid system is considered.A V2G service development logic and its management formulation are put forward.First,the motivations and contradictions of developing V2G services are analyzed.Then a development phase division of the V2G services is proposed in view of the coevolution relation between the grid upgrade and the development of the EV.Next,taking into account the characteristics of each phase,the physical trade structures and corresponding management hierarchies,management relations as well as management measures,are proposed.This paper provides a new perspective of V2G service development,answers the core question on how to make the V2G vision come true in synergy with the development of EVs,and gives some advice on future V2G management paradigms.

Short-term interaction between electric vehicles and microgrid in decentralized vehicle-to-grid control methods

In this paper,a particular standard MicroGrid(MG)is accurately simulated in the presence of the Electric Vehicles(EVs)participating in decentralized primary frequency control service.It examines effect of number of the participating EVs on the short-term dynamic behaviour.The simulation results confirm that frequency deviation will not definitely become zero even though an unlimited number of the EVs participate.The output power of each EV is determined according to the frequency deviation.On the other hand,the output power of each EV affects the value of the frequency deviation,especially in small-scale MGs and MGs with predominant inductance behaviour.Eventually,an equilibrium point is reached after a new EV is added that depends on the characteristics of the MG and the functions executed in the MG central controller during such a service.Additionally,effect of Reflex method,an advanced charging technique for EVs,on the frequency deviation is examined.

V2G模式下电动汽车充放电控制策略研究

随着电动汽车的日益增加,大量电动汽车入网将会对电力系统产生深刻影响。对电动汽车的有序充放电策略进行研究可以缓解电动汽车规模化入网造成的负面影响。本文首先对V2G (Vehicle-to-Grid)进行阐述,介绍其概念、工作原理、主要功能及其关键技术。其次通过对电动汽车入网进行无序充电和有序充电的介绍,论述了对V2G模式下电动汽车有序充放电控制策略研究的必要性。然后介绍了电动汽车的充电需求模型、充放电控制策略及其模型求解方法。最后对国内外有关V2G的示范应用进行了介绍,并对V2G技术在国内外的研究现状进行了总结和展望。

考虑插入式电动汽车的电力系统调频控制

插入式电动汽车作为分布式可控负荷接入智能电网并参与电网调频,越来越受到关注。为了实现大规模插入式电动汽车参与电网的调频控制,借助车辆到电网(V2G)技术,实现能量在电动汽车和电网之间的流动。考虑电池的充电/放电特性,构建响应系统频率偏差的插入式电动汽车功率调整模型。在此基础上,进一步提出考虑插入式电动汽车参与调频的电力系统动态模型。最后,SIMULINK仿真结果表明该模型能够很好地响应系统频率偏差,对提高系统频率的稳定性以及实现电网的快速恢复具有重要意义。

A Multi-Objective Coordinated Charging and Discharging Strategy for Electric Vehicles Based on Stackelberg Game

For the negative impact of large-scale electric vehicles (EVs) disorderly charging on the power grid, a multi-objective optimization strategy for coordinated charging and discharging of EVs based on Stackelberg game is proposed. As the leader, the grid company aims to stabilize load fluctuations and formulate a reasonable electricity price strategy to guide EVs to participate in vehicle-to-grid (V2G);As followers, EV users optimize their charging plans based on electricity price information with the objective of reducing costs and obtaining good comfort. This paper uses the MOPSO algorithm to solve the proposed multi-objective Stackelberg problem, and calculates the optimization results under various preferences, which proves the effectiveness of the proposed model and method.

电动汽车V2G关键技术研究综述

V2G(Vehicle-to-grid)技术能够优化能源效率,参与电网调度,促进电网的安全性、稳定性、可靠性和经济性。文章首先阐述了V2G的概念,其次从电动汽车储能应用研究、电动汽车可调度容量研究和电动汽车移动储能对于配网影响及其协同控制研究等三个方面,综述了国内外V2G技术的研究状况。最后介绍了国内外部分有关V2G的示范应用,并对V2G关键技术的国内外研究状况进行了总结。

Power Optimization Strategy Considering Electric Vehicle in Home Energy Management System

With the development of smart grid, residents have the opportunity to schedule their household appliances （HA） for the purpose of reducing electricity expenses and alleviating the pressure of the smart grid. In this paper, we introduce the structure of home energy management system （EMS） and then propose a power optimization strategy based on household load model and electric vehicle （EV） model for home power usage. In this strategy, the electric vehicles are charged when the price is low, and otherwise, are discharged. By adopting this combined system model under the time-of-use electricity price （TOUP）, the proposed scheduling strategy would effectively minimize the electricity cost and reduce the pressure of the smart grid at the same time. Finally, simulation experiments are carried out to show the feasibility of the proposed strategy. The results show that crossover genetic particle swarm optimization algorithm has better convergence properties than traditional particle swarm algorithm and better adaptability than genetic algorithm.

Quantifying Contribution of DER-Integrated EV Parking Lots to Reliability of Power Distribution Systems

In the future smart cities,parking lots(PLs)can accommodate hundreds of electric vehicles(EVs)at the same time.This trend creates an opportunity for PLs to serve as a potential flexibility resource,considering growing penetration of EVs and integration of distributed energy resources DER(such as photovoltaic and energy storages).Given this background,this paper proposes a comprehensive evaluation framework to investigate the potential role of DER-integrated PLs(DPL)with the capability of vehicle-to-grid(V2G)in improving the reliability of the distribution network.For this aim,first,an overview for the distribution system with DPLs is provided.Then,a generic model for the available generation capacity(AGC)of DPLs with consideration of EV scheduling strategy is developed.On the above basis,an iterative-based algorithm leveraging sequential Monte Carlo simulation is presented to quantify the contribution of DPLs to the reliability of the system.In order to verify the effectiveness of the proposed method,a series of numerical studies are carried out.The simulation results show that the integration of DPLs with the V2G capability could help to improve the reliability performance of distribution grid to a great extent and reduce the adverse impact incurred by EV accommodation,if utilized properly.

Vehicle to Grid Decentralized Dispatch Control Using Consensus Algorithm with Constraints

With the transition to electric vehicle technologies, large scale support infrastructure is being deployed. The vehicleto-grid (V2G) concept is an opportunity to take advantage from both infrastructure and electric vehicle drive. However, coordinating large?number of agents in a reasonable speed and lack of homogenous distribution of the service provided by vehicle users to the grid have been left unattended. We apply consensus theory to the V2G concept presenting a decentralized control solution to assure that all vehicles within a region, regardless of their technology, positioning or state of charge, can communicate with their neighbors and agree on how much energy each should individually exchange with the grid. Applying constraints to the system, we considered a 25,000 vehicle fleet connected to a?grid during peak hours. Simulating power changes and vehicles entering and leaving the system, two groups of 5 vehicles were studied: the first group remained in the system during all peak hours, while the second group only an hour. Results showed that the two groups of vehicles despite connecting to the system at different times were able to reach consensus in t = 15 s, and reported a maximum error of ε < 0.01% if left in the system during all peak hours.

Modelling and control of a grid-connected AC microgrid with the integration of an electric vehicle

The purpose of this paper is to propose an efficient model and a robust control that ensures good power quality for the AC microgrid(MG)connected to the utility grid with the integration of an electric vehicle(EV).The MG consists of two renewable energy sources:a photovoltaic system(PVS)and a wind turbine system(WTS)based on a permanent magnet synchronous generator(PMSG),with the integration of an EV.These sources are used to supply active and reactive power to the AC bus and the utility grid.Maximum power point tracking(MPPT)based on the perturb-and-observe(PO)method is used to increase the efficiency of the photovoltaic modules and improve overall performance.The MG system includes a 2-MW WTS,a 100-kW PVS and 12 kW provided by the EV.To validate the performance of the proposed system,a series of simulations were conducted using the MATLAB/Simulink?environment.The results demonstrate that the proposed system ensures high performance in terms of power quality,system stability,power tracking and safe integration of the EV.

Operation-area-constrained Adaptive Primary Frequency Support Strategy for Electric Vehicle Clusters

Due to their fast response and strong short-term power throughput capacity, electric vehicles(EVs) are promising for providing primary frequency support to power grids. However, due to the complicated charging demands of drivers, it is challenging to efficiently utilize the regulation capacity of EV clusters for providing stable primary frequency support to the power grid. Accordingly, this paper proposes an adaptive primary frequency support strategy for EV clusters constrained by the charging-behavior-defined operation area. First, the forced charging boundary of the EV is determined according to the driver's charging behavior, and based on this, the operation area is defined. This ensures full utilization of the available frequency support capacity of the EV. An adaptive primary frequency support strategy of EV clusters is then proposed. The output power of EV is adaptively regulated according to the real-time distance from the EV operating point to the forced charging boundary. With the proposed strategy, when the EV approaches the forced charging boundary, its output power is gradually reduced to zero. Then, the rapid state-of-charge declines of EVs and sudden output power reductions in EV clusters caused by forced charging to meet the driver's charging demands can be effectively avoided. EV clusters can then provide sustainable frequency support to the power grid without violating the driver's charging demands. Simulation results validate the proposed operation-area-constrained adaptive primary frequency support strategy, which outperforms the average strategy in terms of stable output maintenance and the optimal utilization of regulation capacities of EV clusters.

A preventive control strategy for static voltage stability based on an efficient power plant model of electric vehicles

With the increasing integration of wind farms and electric vehicles(EVs)in power systems,voltage stability is becoming more and more serious.Based on vehicle-to-grid(V2G),an efficient power plant model of EVs(E-EPP)was developed to estimate EV charging load with available corresponding response capacity under different charging strategies.A preventive control strategy based on E-EPP was proposed to maintain the static voltage stability margin(VSM)of power system above a predefined security level.Two control modes were used including the disconnection of EV charging load(‘V1G’mode)and the discharge of stored battery energy back to power grid(‘V2G’mode).A modified IEEE 14-bus system with high penetration of wind power and EVs was used to verify the effectiveness of preventive control strategy.Simulation results showed that the proposed strategy can not only improve the static voltage stability of power system with considerable wind generation,but also guarantee the travelling comfort for EV owners.

Constructing a V2G-enabled Regional Energy Internet for Cost-efficient Carbon Trading

The increasing penetration of plug-in electric ve- hicles (PEVs) has highlighted the importance of coordinating ubiquitous distributed energy resources (DERs) via the internet of things (IoT).With the help of vehicle-to-grid (V2G) technology, PEVs can be aggregated to behave as a storage system, yielding both economic and environmental benefits. In this paper, we propose an optimal bidding framework for a V2G-enabled re- gional energy internet (REI) to participate in day-ahead markets considering carbon trading. The REI operator aims to maximize the net profits from day-ahead markets while anticipating real- time adjustments. A detailed battery model is developed to depict the charging and discharging capability of V2G-enabled PEVs. A two-stage stochastic optimization model is formulated to schedule the operation of PEV fleets against various sources of uncertainties, e.g., the arrival and departure time of PEVs, solar power and real-time prices. Case studies undertaken based on realistic datasets demonstrate that the coordination of the V2G- enabled PEVs and other DERs can facilitate the accommodation of renewable energy, thus improving the REI’s revenues in energy and carbon markets.

Complementarity of electric vehicles and pumped-hydro as energy storage in small isolated energy systems:case of La Palma,Canary Islands

Isolated energy systems in archipelagos are characterized for having a great dependence on fossil sources due to isolation and territorial fragmentation.The island of La Palma is situated on the northwest of the Canary Islands,and its electric system is very small.Sustainability policies planned by local authorities are aimed to increase the share of renewable energies and the reduction of fossil energies.However,intermittence and the concentration of unmanageable renewable energies in few locations may hinder the operation of the system.In order to solve these problems,energy storage plays an essential role.The aim of this paper is to analyse the effects of the introduction of two possible alternatives as a way of energy storage:pumped hydro storage and electric vehicles.For this,we use a simulation model adapted to the features of La Palma,considering different scenarios.Results show that,in the most favourable scenario,the installation of an additional 25 MW from renewables(more than double the current power),supported by 20 MW of pumped hydro storage and a fleet of 3361 electric vehicles,would allow the current share of renewables to increase from11%(in 2015)to 49%.Furthermore,this would mean a 26%reduction in CO2 emissions,10%in costs of generated k Wh and 19%in energy dependence.