331 research outputs found

    Methodology for the optimal design of PEV charging systems with multiple chargers and distributed resources

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    Increased penetration of plug-in electric vehicles (PEVs) will necessitate deployment of numerous PEV chargers. Pairing these chargers with renewable distributed generation (DG) and storage can potentially alleviate negative impacts on the distribution grid and help meet renewable portfolio goals. The optimal design of such integrated charging systems depends on many factors, including geographic location and charging profiles. This paper presents an optimization methodology for designing integrated PEV charging systems with multiple chargers and distributed resources. This methodology is used to investigate optimal designs for charging systems at a retail business and on a university campus. When PEV charging can introduce a demand charge, it is shown that the optimal design depends on the time of charging and the level of existing load. When non-negligible distribution system losses exist between charger locations, it is shown that the optimal size and location of DG and storage depends on the charging profile of the different chargers and the distribution efficiency.Siemens Corporatio

    A Practical Approach for Coordination of Plugged- In Electric Vehicles To Improve Performance and Power Quality of Smart Grid

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    This PhD research is undertaken by supplications including 14 peer-reviewed published articles over seven years research at Curtin University. This study focuses on a real-time Plugged-in Electric Vehicle charging coordination with the inclusion of Electric Vehicle battery charger harmonics in Smart Grid and future Microgrids with incorporation of Renewable Energy Resources. This strategy addresses utilities concerns of grid power quality and performance with the application of SSCs dispatching, active power filters or wavelet energy

    A Probabilistic Approach for the Optimal Sizing of Storage Devices to Increase the Penetration of Plug-in Electric Vehicles in Direct Current Networks

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    The growing diffusion of electric vehicles connected to distribution networks for charging purposes is an ongoing problem that utilities must deal with. Direct current networks and storage devices have emerged as a feasible means of satisfying the expected increases in the numbers of vehicles while preserving the effective operation of the network. In this paper, an innovative probabilistic methodology is proposed for the optimal sizing of electrical storage devices with the aim of maximizing the penetration of plug-in electric vehicles while preserving efficient and effective operation of the network. The proposed methodology is based on an analytical solution of the problem concerning the power losses minimization in distribution networks equipped with storage devices. The closed-form expression that was obtained is included in a Monte Carlo simulation procedure aimed at handling the uncertainties in loads and renewable generation units. The results of several numerical applications are reported and discussed to demonstrate the validity of the proposed solution. Also, different penetration levels of generation units were analyzed in order to focus on the importance of renewable generation

    Optimal electric vehicle scheduling : A co-optimized system and customer perspective

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    Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivizing the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions. First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle --Abstract, page iv

    Optimal Management of an Integrated Electric Vehicle Charging Station under Weather Impacts

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    The focus of this Dissertation is on developing an optimal management of what is called the “Integrated Electric Vehicle Charging Station” (IEVCS) comprising the charging stations for the Plug-in Electric Vehicles (PEVs), renewable (solar) power generation resources, and fixed battery energy storage in the buildings. The reliability and availability of the electricity supply caused by severe weather elements are affecting utility customers with such integrated facilities. The proposed management approach allows such a facility to be coordinated to mitigate the potential impact of weather condition on customers electricity supply, and to provide warnings for the customers and utilities to prepare for the potential electricity supply loss. The risk assessment framework can be used to estimate and mitigate such impacts. With proper control of photovoltaic (PV) generation, PEVs with mobile battery storage and fixed energy storage, customers’ electricity demand could be potentially more flexible, since they can choose to charge the vehicles when the grid load demand is light, and stop charging or even supply energy back to the grid or buildings when the grid load demand is high. The PV generation capacity can be used to charge the PEVs, fixed battery energy storage system (BESS) or supply power to the grid. Such increased demand flexibility can enable the demand response providers with more options to respond to electricity price changes. The charging stations integration and interfacing can be optimized to minimize the operational cost or support several utility applications

    Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids

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    Electric Vehicles (EV) usage is increasing over the last few years due to a rise in fossil fuel prices and the rate of increasing carbon dioxide (CO2) emissions. The EV charging stations are powered by the existing utility power grid systems, increasing the stress on the utility grid and the load demand at the distribution side. The DC grid-based EV charging is more efficient than the AC distribution because of its higher reliability, power conversion efficiency, simple interfacing with renewable energy sources (RESs), and integration of energy storage units (ESU). The RES-generated power storage in local ESU is an alternative solution for managing the utility grid demand. In addition, to maintain the EV charging demand at the microgrid levels, energy management and control strategies must carefully power the EV battery charging unit. Also, charging stations require dedicated converter topologies, control strategies and need to follow the levels and standards. Based on the EV, ESU, and RES accessibility, the different types of microgrids architecture and control strategies are used to ensure the optimum operation at the EV charging point. Based on the above said merits, this review paper presents the different RES-connected architecture and control strategies used in EV charging stations. This study highlights the importance of different charging station architectures with the current power converter topologies proposed in the literature. In addition, the comparison of the microgrid-based charging station architecture with its energy management, control strategies, and charging converter controls are also presented. The different levels and types of the charging station used for EV charging, in addition to controls and connectors used in the charging station, are discussed. The experiment-based energy management strategy is developed for controlling the power flow among the available sources and charging terminals for the effective utilization of generated renewable power. The main motive of the EMS and its control is to maximize usage of RES consumption. This review also provides the challenges and opportunities for EV charging, considering selecting charging stations in the conclusion.publishedVersio

    Online Coordinated Charging of Plug-In Electric Vehicles in Smart Grid to Minimize Cost of Generating Energy and Improve Voltage Profile

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    This Ph.D. research highlights the negative impacts of random vehicle charging on power grid and proposes four practical PEV coordinated charging strategies that reduce network and generation costs by integrating renewable energy resources and real-time pricing while considering utility constraints and consumer concerns

    Stochastic planning of electric vehicle charging station integrated with photovoltaic and battery systems

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166260/1/gtd2bf00020.pd
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