Integration of Distributed Energy Resources into Electricity Systems and Markets

将分布式能源整合到电力系统和市场中

基本信息

  • 批准号:
    RGPIN-2021-04177
  • 负责人:
  • 金额:
    $ 2.04万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2021
  • 资助国家:
    加拿大
  • 起止时间:
    2021-01-01 至 2022-12-31
  • 项目状态:
    已结题

项目摘要

Distributed energy resources (DER), including roof-top solar, small-scale wind turbines, home battery storage, electric vehicles (EV), and demand response, have become increasingly popular and essential components of power distribution systems. However, the growth of DER poses significant challenges to system operation, such as bidirectional power flow, intermittent power generation, and unexpected frequency/voltage fluctuation. DERs will also considerably impact electricity markets. For example, the Federal Energy Regulatory Commission (FERC) Order No. 2222, announced in 2020, requires grid operators in the US to establish DERs as market participants. Therefore, grid operators need to prepare for high-level DER penetration in the electricity system and market. Methods have been developed for DER integration, such as DER modeling, optimal power flow (OPF), and game theory. Among others, the applicant developed demand response, vehicle-to-grid, and battery models. Nonetheless, accurate and unified DER models are needed. Distributed, stochastic, and convexified OPF models should be developed for DER integration. Also, effective dynamic pricing to incentivize DER participants in the electricity market becomes increasingly crucial. The long-term goal of the proposed research program is to safely, reliably, and economically integrate DERs into electricity systems and markets. To reach this goal, the following learning and optimization models will be developed: 1) machine learning for modeling DERs; 2) OPF for economic dispatch, optimal sizing, and optimal placement of DERs; 3) distribution system reconfiguration methods to improve DER integration; 4) DERs management systems; and 5) game and mechanism design methods to promote DERs in markets. The short-term objectives will focus on developing accurate and unified DER, OPF, dynamic pricing, and game models. Novel learning and optimization methods will be developed for efficient and economic DER integration. The deep learning method and unified DER models can help grid operators to visualize DERs and simplify DER integration. The proposed OPF models will be quantitatively evaluated. The most suitable OPF model for high-level DER integration into large-scale power distribution systems will be identified. Grid operators can use this information to select the best model for their specific application. Using the proposed method, DERs can be controlled to increase power system stability, reduce generation cost, delay infrastructure investments, and contribute to Canada's commitment to greenhouse gas emission reduction. The proposed dynamic pricing can promote electricity market competition and increase DER owners' revenue. Also, five highly qualified personnel (HQP) will be trained with relevant knowledge, skills, and abilities, which are in high demand by governments, utilities, power industries, and academia. I will also strive to promote equity, diversity, and inclusion (EDI) in HQP training.
分布式能源(DER),包括屋顶太阳能、小型风力涡轮机、家用电池存储、电动汽车(EV)和需求响应,已经成为配电系统越来越受欢迎的重要组成部分。然而,DER的增长对系统运行提出了重大挑战,例如双向功率流、间歇性发电和意外的频率/电压波动。DER也将对电力市场产生重大影响。例如,2020年公布的联邦能源监管委员会(FERC)第2222号命令要求美国电网运营商作为市场参与者建立DER。因此,电网运营商需要为电力系统和市场中的高水平DER渗透做好准备。 DER集成的方法已经发展,如DER建模,最优潮流(OPF)和博弈论。除其他外,申请人开发了需求响应,车辆到电网和电池模型。然而,需要准确和统一的DER模型。分布式,随机,和convexified OPF模型应开发DER集成。此外,有效的动态定价激励DER参与者在电力市场变得越来越重要。 拟议的研究计划的长期目标是安全,可靠和经济地将DER集成到电力系统和市场中。为了实现这一目标,将开发以下学习和优化模型:1)用于DER建模的机器学习; 2)用于DER的经济调度、最优规模和最优位置的OPF; 3)用于改善DER集成的配电系统重构方法; 4)DER管理系统;以及5)用于在市场上推广DER的博弈和机制设计方法。短期目标将侧重于开发准确和统一的DER、OPF、动态定价和博弈模型。 将开发新的学习和优化方法,以实现高效和经济的DER集成。深度学习方法和统一的DER模型可以帮助电网运营商可视化DER并简化DER集成。将定量评估所提出的OPF模型。最合适的OPF模型的高层次DER集成到大规模配电系统将被确定。电网运营商可以使用这些信息来选择最适合其特定应用的模型。使用所提出的方法,DERs可以控制,以增加电力系统的稳定性,降低发电成本,延迟基础设施投资,并有助于加拿大的温室气体减排的承诺。提出的动态电价可以促进电力市场竞争,增加DER所有者的收益。此外,五名高素质人员(HQP)将接受相关知识,技能和能力的培训,这些知识,技能和能力是政府,公用事业,电力行业和学术界的高需求。我还将努力在HQP培训中促进公平、多样性和包容性(EDI)。

项目成果

期刊论文数量(0)
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会议论文数量(0)
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Wang, Zhanle其他文献

An ensemble method of full wavelet packet transform and neural network for short term electrical load forecasting
  • DOI:
    10.1016/j.epsr.2020.106265
  • 发表时间:
    2020-05-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    El-Hendawi, Mohamed;Wang, Zhanle
  • 通讯作者:
    Wang, Zhanle
Evolution of smart grids towards the Internet of energy: Concept and essential components for deep decarbonisation
  • DOI:
    10.1049/stg2.12095
  • 发表时间:
    2022-11-20
  • 期刊:
  • 影响因子:
    2.3
  • 作者:
    Ghiasi, Mohammad;Wang, Zhanle;Ghadimi, Noradin
  • 通讯作者:
    Ghadimi, Noradin

Wang, Zhanle的其他文献

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{{ truncateString('Wang, Zhanle', 18)}}的其他基金

Integration of Distributed Energy Resources into Electricity Systems and Markets
将分布式能源整合到电力系统和市场中
  • 批准号:
    RGPIN-2021-04177
  • 财政年份:
    2022
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Grants Program - Individual
Integration of Distributed Energy Resources into Electricity Systems and Markets
将分布式能源整合到电力系统和市场中
  • 批准号:
    DGECR-2021-00362
  • 财政年份:
    2021
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Launch Supplement

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用于整合分布式能源的静态功率转换器
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