The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a...The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.展开更多
To support power grid operators to detect and evaluate potential power grid congestions due to the electrification of urban private cars,accurate models are needed to determine the charging energy and power demand of ...To support power grid operators to detect and evaluate potential power grid congestions due to the electrification of urban private cars,accurate models are needed to determine the charging energy and power demand of battery electric vehicles(BEVs)with high spatial and temporal resolution.Typically,e-mobility traffic simulations are used for this purpose.In particular,activity-based mobility models are used because they individually model the activity and travel patterns of each person in the considered geographical area.In addition to inaccuracies in determining the spatial distribution of BEV charging demand,one main limitation of the activity-based models proposed in the literature is that they rely on data describing traffic flow in the considered area.However,these data are not available for most places in the world.Therefore,this paper proposes a novel approach to develop an activity-based model that overcomes the spatial limitations and does not require traffic flow data as an input parameter.Instead,a route assignment procedure assigns a destination to each BEV trip based on the evaluation of all possible destinations.The basis of this evaluation is the travel distance and speed between the origin of the trip and the destination,as well as the car-access attractiveness and the availability of parking spots at the destinations.The applicability of this model is demonstrated for the urban area of Berlin,Germany,and its 448 sub-districts.For each district in Berlin,both the required daily BEV charging energy demand and the power demand are determined.In addition,the load shifting potential is investigated for an exemplary district.The results show that peak power demand can be reduced by up to 31.7%in comparison to uncontrolled charging.展开更多
Background:The increasing penetration of a massive number of plug-in electric vehicles(PEVs)and distributed generators(DGs)into current power distribution networks imposes obvious challenges on power distribution netw...Background:The increasing penetration of a massive number of plug-in electric vehicles(PEVs)and distributed generators(DGs)into current power distribution networks imposes obvious challenges on power distribution network operation.Methods:This paper presents an optimal temporal-spatial scheduling strategy of PEV charging demand in the presence of DGs.The solution is designed to ensure the reliable and secure operation of the active power distribution networks,the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand,as the PEVs can be considered as mobile energy storage units.Results:As a result,the charging demands of PEVs are optimally scheduled temporally and spatially,which can improve the DG utilization efficiency as well as reduce the charging cost under real-time pricing(RTP).Conclusions:The proposed scheduling strategy is evaluated through a series of simulations and the numerical results demonstrate the effectiveness and the benefits of the proposed solution.展开更多
预测电动汽车充电需求的动态时空分布对于电网应对大规模电动汽车的接入具有重要意义。已有的研究缺乏能够同时精确描述电动汽车行驶过程中地理位置与荷电状态(state of charge,SOC)变化的数学模型。为了模拟电动汽车交通需求和充电需...预测电动汽车充电需求的动态时空分布对于电网应对大规模电动汽车的接入具有重要意义。已有的研究缺乏能够同时精确描述电动汽车行驶过程中地理位置与荷电状态(state of charge,SOC)变化的数学模型。为了模拟电动汽车交通需求和充电需求的动态时空变化过程,从电网调度的实际需求出发,改进了交通流领域中的微观交通仿真模型,结合Cruise软件计算的不同场景下的电动汽车每公里耗电量,提出了基于Agent-元胞自动机的电动汽车充电需求动态时空分布动态演化模型。最后,以54节点配电系统和25节点交通网络的耦合系统为例,说明所提方法可以预测快充站的电动汽车充电负荷,为电动汽车的充电负荷引导提供重要依据。展开更多
基金supported by National Key Research and Development Program of China–Comprehensive Demonstration Project of Smart Grid Supporting Lowcarbon Winter Olympics(No.2016YFB0900500)
文摘The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.
基金This research was funded by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)-project:“Multi-Domain Modeling and Optimization of Integrated Renewable Energy and Urban Electric Vehicle Systems”[grant number 410830482].
文摘To support power grid operators to detect and evaluate potential power grid congestions due to the electrification of urban private cars,accurate models are needed to determine the charging energy and power demand of battery electric vehicles(BEVs)with high spatial and temporal resolution.Typically,e-mobility traffic simulations are used for this purpose.In particular,activity-based mobility models are used because they individually model the activity and travel patterns of each person in the considered geographical area.In addition to inaccuracies in determining the spatial distribution of BEV charging demand,one main limitation of the activity-based models proposed in the literature is that they rely on data describing traffic flow in the considered area.However,these data are not available for most places in the world.Therefore,this paper proposes a novel approach to develop an activity-based model that overcomes the spatial limitations and does not require traffic flow data as an input parameter.Instead,a route assignment procedure assigns a destination to each BEV trip based on the evaluation of all possible destinations.The basis of this evaluation is the travel distance and speed between the origin of the trip and the destination,as well as the car-access attractiveness and the availability of parking spots at the destinations.The applicability of this model is demonstrated for the urban area of Berlin,Germany,and its 448 sub-districts.For each district in Berlin,both the required daily BEV charging energy demand and the power demand are determined.In addition,the load shifting potential is investigated for an exemplary district.The results show that peak power demand can be reduced by up to 31.7%in comparison to uncontrolled charging.
基金The National Key Research and Development Program of China(Basic Research Class 2017YFB0903000)Basic Theories and Methods of Analysis and Control of the Cyber Physical Systems for Power Grid,and the Natural Science Foundation of Zhejiang Province(LZ15E070001).
文摘Background:The increasing penetration of a massive number of plug-in electric vehicles(PEVs)and distributed generators(DGs)into current power distribution networks imposes obvious challenges on power distribution network operation.Methods:This paper presents an optimal temporal-spatial scheduling strategy of PEV charging demand in the presence of DGs.The solution is designed to ensure the reliable and secure operation of the active power distribution networks,the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand,as the PEVs can be considered as mobile energy storage units.Results:As a result,the charging demands of PEVs are optimally scheduled temporally and spatially,which can improve the DG utilization efficiency as well as reduce the charging cost under real-time pricing(RTP).Conclusions:The proposed scheduling strategy is evaluated through a series of simulations and the numerical results demonstrate the effectiveness and the benefits of the proposed solution.
文摘预测电动汽车充电需求的动态时空分布对于电网应对大规模电动汽车的接入具有重要意义。已有的研究缺乏能够同时精确描述电动汽车行驶过程中地理位置与荷电状态(state of charge,SOC)变化的数学模型。为了模拟电动汽车交通需求和充电需求的动态时空变化过程,从电网调度的实际需求出发,改进了交通流领域中的微观交通仿真模型,结合Cruise软件计算的不同场景下的电动汽车每公里耗电量,提出了基于Agent-元胞自动机的电动汽车充电需求动态时空分布动态演化模型。最后,以54节点配电系统和25节点交通网络的耦合系统为例,说明所提方法可以预测快充站的电动汽车充电负荷,为电动汽车的充电负荷引导提供重要依据。
