Intelligent Control and Optimization for PV-Based EV Fast Charging Stations

光伏电动汽车快速充电站的智能控制与优化

• 批准号: 514029-2017
• 负责人: Gaber, Hossam
• 金额: $ 1.82万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640024
• 关键词: Intelligent; Control; Optimization; PV; Based

Canada is moving towards deployment of electric vehicles, which requires large capacity charginginfrastructures. To meet charging capacity and time requirements, fast charging stations are preferred. AlternatePower International (API) is active in developing, integrating, and installing solar / Photovoltaic (PV) systemsin Canada and worldwide. API is seeking advanced PV-based charging stations to support transportationinfrastructures to meet Ontario/Canada requirements of clean energy. This project is aiming at the design,control and optimization of PV-based fast charging stations to support electric vehicles (EVs) using integratedPhotovoltaic (PV) and intelligent control system with hysteresis control strategy and optimization techniques.The proposed design will allow PV systems, provided by Alternate Power International Ltd., to providemaximum power for improved system with high Return-On-Investment (ROI). The proposed fast chargingstations will be implemented in residential and public charging infrastructures.The energy management in the station is performed by an intelligent control algorithm that directs the powerflows among the PV, fast chargers, the energy storage system and the grid connection. There is a clear trade-offbetween the size of the PV system, energy storage system, and the power rating of the grid connection.Different mobility and charging models will be synthesized, analyzed, and optimized to achieve high ROIbased on station design, demands, and operation requirements, as well as weather forecasting. Moreover, withdifferent-range vehicles, this technology can be tuned and optimized to supply all the power required for EVsand the supporting utilities. The proposed system will include PV system, battery, converters / inverters,charger head module, grid interface module, control systems, as well as integrated energy optimization system.Intelligent optimization algorithms will be developed to optimize PV system design and their integration. Foreach part of the system, physical and economical models will be evaluated and optimized. A techno-economicoptimization algorithms will be developed to ensure overall high performance and profits.

加拿大正朝着部署电动汽车的方向发展，这需要大容量的充电基础设施。为了满足充电容量和时间要求，快速充电站是首选。AlternatePower International（API）积极在加拿大和世界各地开发、集成和安装太阳能/光伏（PV）系统。API正在寻求先进的基于光伏的充电站，以支持交通基础设施，以满足安大略/加拿大对清洁能源的要求。该项目旨在设计、控制和优化基于光伏的快速充电站，以支持使用集成光伏（PV）和智能控制系统的电动汽车（EV）。该设计将允许由Alternate Power International Ltd.提供的光伏系统，为改进的系统提供最大的功率，并具有高投资回报率（ROI）。建议的快速充电站将在住宅和公共充电基础设施中实施。站中的能量管理由智能控制算法执行，该算法指导PV，快速充电器，能量存储系统和电网连接之间的功率流。在光伏系统、储能系统和电网连接的额定功率之间有一个明确的权衡。不同的移动性和充电模型将被综合、分析和优化，以实现基于电站设计、需求和运营要求以及天气预报的高ROI。此外，对于不同里程的车辆，该技术可以进行调整和优化，以提供电动汽车和配套设施所需的所有电力。该系统将包括光伏系统、蓄电池、变流器/逆变器、充电头模块、电网接口模块、控制系统以及综合能量优化系统。将开发智能优化算法以优化光伏系统设计及其集成。对系统的每一部分，都进行了物理模型和经济模型的评估和优化。将开发技术经济优化算法，以确保整体高性能和利润。