The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Yonghua Song - One of the best experts on this subject based on the ideXlab platform.

  • pev Fast Charging Station siting and sizing on coupled transportation and power networks
    IEEE Transactions on Smart Grid, 2018
    Co-Authors: Hongcai Zhang, Zechun Hu, Scott J Moura, Yonghua Song
    Abstract:

    Plug-in electric vehicle (PEV) Charging Stations couple future transportation systems and power systems. That is, PEV driving and Charging behavior will influence the two networks simultaneously. This paper studies optimal planning of PEV Fast-Charging Stations considering the interactions between the transportation and electrical networks. The geographical targeted planning area is a highway transportation network powered by a high voltage distribution network. First, we propose the capacitated-flow refueling location model (CFRLM) to explicitly capture PEV Charging demands on the transportation network under driving range constraints. Then, a mixed-integer linear programming model is formulated for PEV Fast-Charging Station planning considering both transportation and electrical constraints based on CFRLM, which can be solved by deterministic branch-and-bound methods. Numerical experiments are conducted to illustrate the proposed planning method. The influences of PEV population, power system security operation constraints, and PEV range are analyzed.

  • a second order cone programming model for planning pev Fast Charging Stations
    IEEE Transactions on Power Systems, 2018
    Co-Authors: Hongcai Zhang, Scott J Moura, Yonghua Song
    Abstract:

    This paper studies siting and sizing of plug-in electric vehicle (PEV) Fast-Charging Stations on coupled transportation and power networks. We develop a closed-form model for PEV Fast-Charging Stations’ service abilities, which considers heterogeneous PEV driving ranges and Charging demands. We utilize a modified capacitated flow refueling location model based on subpaths (CFRLM_SP) to explicitly capture time-varying PEV Charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM_SP to enhance model accuracy and computational efficiency. We then propose a stochastic mixed-integer second-order cone programming model for PEV Fast-Charging Station planning. The model considers the transportation network constraints of CFRLM_SP and the power network constraints with ac power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.

  • a second order cone programming model for pev Fast Charging Station planning
    arXiv: Optimization and Control, 2017
    Co-Authors: Hongcai Zhang, Scott J Moura, Yonghua Song
    Abstract:

    This paper studies siting and sizing of plug-in electric vehicle (PEV) Fast-Charging Stations on coupled transportation and power networks. We develop a closed-form service rate model of highway PEV Charging Stations' service abilities, which considers heterogeneous PEV driving ranges and Charging demands.We utilize a modified capacitated flow refueling location model (CFRLM) to explicitly capture time-varying PEV Charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM to enhance model accuracy and computational efficiency.We then propose a stochastic mixed-integer second order cone programming (SOCP) model for PEV Fast-Charging Station planning. The model considers the transportation network constraints of CFRLM and the power network constraints with AC power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.

  • Value of the energy storage system in an electric bus Fast Charging Station
    Applied Energy, 2015
    Co-Authors: Huajie Ding, Zechun Hu, Yonghua Song
    Abstract:

    Electric buses (EBs) are undergoing rapid development because of their environmental friendliness. Different from private electric vehicles, EBs are scheduled by a public transport company and required to be charged as soon as possible during operation hours. Consequently, the implementation of Fast Charging Stations (FCSs) is essential to support the operation of EBs. Usually, the size of an FCS is constrained by the residual capacity of the connected distribution network and the investment budget. An energy storage system (ESS) is considered as a potential supplement not only to reduce the network integration cost for FCSs but also to reduce the Charging cost of EBs through electricity price arbitrage. To quantify the value of ESS in an electric bus FCS, a mixed integer nonlinear programming (MINLP) formulation for optimal sizing and control of FCS and ESS is built. A simplification method is proposed to convert the MINLP problem to a linear one without any loss in optimality, which accelerates the solving process. Simulations are performed based on historical data of a practical FCS. Numerical results indicate that ESS can significantly help reduce the overall investment and Charging cost of the FCS. Meanwhile, the parameters of investment cost, lifespan and time-of-use electricity price have significant influences on the overall value of ESS for an FCS.

Subhashish Bhattacharya - One of the best experts on this subject based on the ideXlab platform.

  • an approach towards extreme Fast Charging Station power delivery for electric vehicles with partial power processing
    IEEE Transactions on Industrial Electronics, 2020
    Co-Authors: Vishnu Mahadeva Iyer, Srinivas Gulur, Ghanshyamsinh Gohil, Subhashish Bhattacharya
    Abstract:

    This article proposes an approach for realizing the power delivery scheme for an extreme Fast Charging (XFC) Station that is meant to simultaneously charge multiple electric vehicles (EVs). A cascaded H-bridge converter is utilized to directly interface with the medium voltage grid while dual-active-bridge based soft-switched solid-state transformers are used to achieve galvanic isolation. The proposed approach eliminates redundant power conversion by making use of partial power rated dc–dc converters to charge the individual EVs. Partial power processing enables independent Charging control over each EV, while processing only a fraction of the total battery Charging power. Practical implementation schemes for the partial power charger unit are analyzed. A phase-shifted full-bridge converter-based charger is proposed. Design and control considerations for enabling multiple Charging points are elucidated. Experimental results from a down-scaled laboratory test-bed are provided to validate the control aspects, functionality, and effectiveness of the proposed XFC Station power delivery scheme. With a down-scaled partial power converter that is rated to handle only 27% of the battery power, an efficiency improvement of 0.6% at full-load and 1.6% at 50% load is demonstrated.

  • Extreme Fast Charging Station architecture for electric vehicles with partial power processing
    2018 IEEE Applied Power Electronics Conference and Exposition (APEC), 2018
    Co-Authors: Vishnu Mahadeva Iyer, Srinivas Gulur, Ghanshyamsinh Gohil, Subhashish Bhattacharya
    Abstract:

    This paper introduces a power delivery architecture for an Extreme Fast Charging (XFC) Station that is meant to simultaneously charge multiple electric vehicles (EVs) with a 300-mile range battery pack in about 15 minutes. The proposed approach can considerably improve overall system efficiency as it eliminates redundant power conversion by making use of partial power rated dc-dc converters to charge the individual EVs as opposed to a traditional Fast Charging Station structure based on full rated dedicated Charging converters. Partial power processing enables independent Charging control over each EV, while processing only a fraction of the total battery Charging power. Energy storage (ES) and renewable energy systems such as photovoltaic (PV) arrays can be easily incorporated in the versatile XFC Station architecture to minimize the grid impacts due to multi-mega watt Charging. A control strategy is discussed for the proposed XFC Station. Experimental results from a scaled down laboratory prototype are provided to validate the functionality, feasibility and cost-effectiveness of the proposed XFC Station power architecture.

Mei Huang - One of the best experts on this subject based on the ideXlab platform.

  • research on configuration methods of battery energy storage system for pure electric bus Fast Charging Station
    Energies, 2019
    Co-Authors: Yian Yan, Huang Wang, Jiuchun Jiang, Weige Zhang, Yan Bao, Mei Huang
    Abstract:

    With the pervasiveness of electric vehicles and an increased demand for Fast Charging, Stationary high-power Fast-Charging is becoming more widespread, especially for the purpose of serving pure electric buses (PEBs) with large-capacity onboard batteries. This has resulted in a huge distribution capacity demand. However, the distribution capacity is limited, and in some urban areas the cost of expanding the electric network capacity is very high. In this paper, three battery energy storage system (BESS) integration methods—the AC bus, each Charging pile, or DC bus—are considered for the suppression of the distribution capacity demand according to the proposed Charging topologies of a PEB Fast-Charging Station. On the basis of linear programming theory, an evaluation model was established that consider the influencing factors of the configuration: basic electricity fee, electricity cost, cost of the energy storage system, costs of transformer and converter equipment, and electric energy loss. Then, a case simulation is presented using realistic operation data, and an economic comparison of the three configurations is provided. An analysis of the impacts of each influence factor in the case study is discussed to verify the case results. The numerical results indicate that the appropriate BESS configuration can significantly reduce the distribution demand and Stationary cost synchronously.

  • hierarchical energy storage configuration method for pure electric vehicle Fast Charging Station
    IEEE Transportation Electrification Conference and Expo Asia-Pacific, 2017
    Co-Authors: Huang Wang, Jiuchun Jiang, Mei Huang, Weige Zhang, Yan Bao
    Abstract:

    Aiming at short-term high Charging power, low load rate and other problems in the Fast Charging Station for pure electric city buses, two kinds of energy storage (ES) configuration are considered. One is to configure distributed energy storage system (ESS) for each Charging pile. Second is to configure centralized ESS for the entire Charging Station. The optimal configuration strategy of hierarchical ESS is studied based on some influencing factors such as basic capacity cost, electricity charge, cost of ESS, costs of the transformer and converter and energy loss costs caused by efficiency factors. Combining with the different characteristics of Charging load timing of multiple Charging piles, the economic comparison of the ES configuration schemes are carried out and the effects of the components in the total cost are analyzed based on the topology of the Charging system in the Station. With the measured data of a Fast Charging Station for electric city buses in Beijing, a multi-level linear programming optimization method is adopted. With the target of the lowest comprehensive cost of the Charging Station, it is concluded that it is more economical to configure centralized ESS at the DC bus.

  • economic study on bus Fast Charging Station with battery energy storage system
    IEEE Transportation Electrification Conference and Expo Asia-Pacific, 2017
    Co-Authors: Mei Huang, Weige Zhang, Yan Bao
    Abstract:

    Bus Fast Charging Station (FCS) Charging power is large, the load short-term peak power and Charging costs is large. Configuring the battery energy storage system (BESS) in the FCS can reduce the load peak and the distribution capacity, and can also use the Time-of-Use (TOU) electricity prices to reduce the Charging costs. But the storage capacity demand is too large if configure the BESS directly, economy is not ideal. In fact, the plug-in electric bus driving behavior is regular, it can improve the load characteristics by adjusting the bus's Charging strategy, and then consider the configuration of BESS. In this paper, first, the load model of the bus FCS was established. Taking a plug-in electric bus Station in Beijing as an example, the Charging load of the Station was simulated and analyzed using two Charging strategies. Then, take maximize the net income of the bus FCS system as the objective, the economic model of the FCS with the BESS is established. The economy of the bus FCS system was simulated and analyzed without and with the BESS under two Charging strategies. Finally, the results demonstrate that configure BESS in the bus FCS can improve the Station system economy.

Hongcai Zhang - One of the best experts on this subject based on the ideXlab platform.

  • pev Fast Charging Station siting and sizing on coupled transportation and power networks
    IEEE Transactions on Smart Grid, 2018
    Co-Authors: Hongcai Zhang, Zechun Hu, Scott J Moura, Yonghua Song
    Abstract:

    Plug-in electric vehicle (PEV) Charging Stations couple future transportation systems and power systems. That is, PEV driving and Charging behavior will influence the two networks simultaneously. This paper studies optimal planning of PEV Fast-Charging Stations considering the interactions between the transportation and electrical networks. The geographical targeted planning area is a highway transportation network powered by a high voltage distribution network. First, we propose the capacitated-flow refueling location model (CFRLM) to explicitly capture PEV Charging demands on the transportation network under driving range constraints. Then, a mixed-integer linear programming model is formulated for PEV Fast-Charging Station planning considering both transportation and electrical constraints based on CFRLM, which can be solved by deterministic branch-and-bound methods. Numerical experiments are conducted to illustrate the proposed planning method. The influences of PEV population, power system security operation constraints, and PEV range are analyzed.

  • a second order cone programming model for planning pev Fast Charging Stations
    IEEE Transactions on Power Systems, 2018
    Co-Authors: Hongcai Zhang, Scott J Moura, Yonghua Song
    Abstract:

    This paper studies siting and sizing of plug-in electric vehicle (PEV) Fast-Charging Stations on coupled transportation and power networks. We develop a closed-form model for PEV Fast-Charging Stations’ service abilities, which considers heterogeneous PEV driving ranges and Charging demands. We utilize a modified capacitated flow refueling location model based on subpaths (CFRLM_SP) to explicitly capture time-varying PEV Charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM_SP to enhance model accuracy and computational efficiency. We then propose a stochastic mixed-integer second-order cone programming model for PEV Fast-Charging Station planning. The model considers the transportation network constraints of CFRLM_SP and the power network constraints with ac power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.

  • coordinated Charging and disCharging strategies for plug in electric bus Fast Charging Station with energy storage system
    Iet Generation Transmission & Distribution, 2018
    Co-Authors: Huimiao Chen, Hongcai Zhang, Haocheng Luo
    Abstract:

    Plug-in electric bus (PEB) is an environmentally friendly mode of public transportation and PEB Fast Charging Stations (PEBFCSs) play an essential role in the operation of PEBs. Under effective control, deploying an energy storage system (ESS) within a PEBFCS can reduce the peak Charging loads and the electricity purchase costs. To deal with the (integrated) scheduling problem of (PEBs Charging and) ESS Charging and disCharging, in this study, the authors propose an optimal real-time coordinated Charging and disCharging strategy for a PEBFCS with ESS to achieve maximum economic benefits. According to whether the PEB Charging loads are controllable, the corresponding mathematical models are, respectively, established under two scenarios, i.e. coordinated PEB Charging scenario and uncoordinated PEB Charging scenario. The price and lifespan of ESS, the capacity charge of PEBFCS and the electricity price arbitrage are considered in the models. Further, under the coordinated PEB Charging scenario, a heuristics-based method is developed to get the approximately optimal strategy with computation efficiency dramatically enhanced. Finally, the authors validate the effectiveness of the proposed strategies, interpret the effect of ESS prices on the usage of ESS and provide the sensitivity analysis of ESS capacity through the case studies.

  • coordinated Charging and disCharging strategies for plug in electric bus Fast Charging Station with energy storage system
    arXiv: Systems and Control, 2017
    Co-Authors: Huimiao Chen, Hongcai Zhang, Haocheng Luo
    Abstract:

    Plug-in electric bus (PEB) is an environmentally friendly mode of public transportation and plug-in electric bus Fast Charging Stations (PEBFCSs) play an essential role in the operation of PEBs. Under effective control, deploying an energy storage system (ESS) within a PEBFCS can reduce the peak Charging loads and the electricity purchase costs. To deal with the (integrated) scheduling problem of (PEBs Charging and) ESS Charging and disCharging, in this study, we propose an optimal real-time coordinated Charging and disCharging strategy for a PEBFCS with ESS to achieve maximum economic benefits. According to whether the PEB Charging loads are controllable, the corresponding mathematical models are respectively established under two scenarios, i.e., coordinated PEB Charging scenario and uncoordinated PEB Charging scenario. The price and lifespan of ESS, the capacity charge of PEBFCS and the electricity price arbitrage are considered in the models. Further, under the coordinated PEB Charging scenario, a heuristics-based method is developed to get the approximately optimal strategy with computation efficiency dramatically enhanced. Finally, we validate the effectiveness of the proposed strategies, interpret the effect of ESS prices on the usage of ESS, and provide the sensitivity analysis of ESS capacity through the case studies.

  • a second order cone programming model for pev Fast Charging Station planning
    arXiv: Optimization and Control, 2017
    Co-Authors: Hongcai Zhang, Scott J Moura, Yonghua Song
    Abstract:

    This paper studies siting and sizing of plug-in electric vehicle (PEV) Fast-Charging Stations on coupled transportation and power networks. We develop a closed-form service rate model of highway PEV Charging Stations' service abilities, which considers heterogeneous PEV driving ranges and Charging demands.We utilize a modified capacitated flow refueling location model (CFRLM) to explicitly capture time-varying PEV Charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM to enhance model accuracy and computational efficiency.We then propose a stochastic mixed-integer second order cone programming (SOCP) model for PEV Fast-Charging Station planning. The model considers the transportation network constraints of CFRLM and the power network constraints with AC power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.

Kevin Tomsovic - One of the best experts on this subject based on the ideXlab platform.

  • optimal sizing of pv and energy storage in an electric vehicle extreme Fast Charging Station
    IEEE PES Innovative Smart Grid Technologies Conference, 2020
    Co-Authors: Guodong Liu, Yaosuo Xue, Madhu Chinthavali, Kevin Tomsovic
    Abstract:

    This paper proposes an optimization model for the optimal sizing of photovoltaic (PV) and energy storage in an electric vehicle extreme Fast Charging Station considering the coordinated Charging strategy of the electric vehicles. The proposed model minimizes the annualized cost of the extreme Fast Charging Station, including investment and maintenance cost of PV and energy storage, cost of purchasing energy from utility and demand charge. The decision variables are capacity of invested PV and the power and energy ratings of invested energy storage. To further reduce the annualized cost of the extreme Fast Charging Station, the Charging strategy of electric vehicles are integrated into the optimization model and coordinated with the power output of PV and Charging/disCharging of energy storage. Results of numerical simulations indicate that investment of PV and energy storage could help reduce the annualized cost of the extreme Fast Charging Station significantly. Meanwhile, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.