SCC: Empowering Smart and Connecticut Communities through Programmable Community Microgrids

SCC：通过可编程社区微电网增强智能和康涅狄格社区的能力

• 批准号: 2018492
• 负责人: Peng Zhang
• 金额: $ 74.37万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018492&HistoricalAwards=false
• 关键词: SCC; Empowering; Smart; Connecticut; Communities

The keystone of smart & connected communities (S&CCs) is a resilient electric network which supports critical infrastructures and other functions vital for citizens. Existing electric networks, however, can hardly sustain the ever-increasing demand of growing communities. According to the Department of Energy, in 2015, U.S. customers experienced an average of 198 minutes of power outage, indicating an unsatisfied electricity resilience. Furthermore, distributed energy resources (DERs), such as photovoltaics (PVs) increasingly installed in U.S. communities, fail to improve electricity resilience, because they cannot ride through sustained grid contingencies. Adding to these challenges, extreme weather events and cyber-attacks can potentially lead to catastrophic blackouts. Microgrids have proved to be a promising paradigm for electricity resiliency. Unfortunately, transforming community power infrastructures to truly smart microgrids remains prohibitively difficult due to dependence on hardware; limited, unscalable analytics; and broader digital surfaces vulnerable to cyber-attacks. The main objective of this project is to create smart programmable microgrids (SPMs). Our key innovation is to virtualize microgrid functions, making them software-defined and hardware-independent, so that converting DERs to community microgrids becomes affordable, autonomic, and secure. To achieve our main objective, our team will: 1) Architect a programmable microgrid platform for virtualizing traditionally hardware-dependent microgrid functions as flexible software services, fully resolving hardware dependence issues and enabling unprecedentedly low costs; 2) Pioneer a concept of software-defined operation optimization for microgrids, where operation objectives, grid connection, and DER participations will be defined by software and plug-and-play, and can be quickly reconfigured, based on the development of modularized and tightened models and a novel asynchronous price-based decomposition-and-coordination method; 3) Devise a software-defined distributed formal analysis for online stability assessment under heterogeneous uncertainties and plug-and-play of microgrid components or microgrids; 4) Develop a real-time-learning-based cybersecurity function to protect SPMs against power bot attacks; and 5) Enable anaerobic-biomass-digesters (ADs) as environmentally friendly and dispatchable DERs by virtualizing the dispatch and control of ADs in SPM. The proposed SPM will be demonstrated on a CT community microgrid through a recently built cyber-physical testbed. This project will provide groundbreaking, replicable technologies to modernize cost-effectively America's energy infrastructures in the S&CC and could transform today's community power infrastructures into tomorrow's flexible services towards self-configuration, self-healing, self-optimizing, and self-protection. The proposed technologies are expected to be widely adopted especially by those communities suffering high electricity costs, low energy reliability, and poor resilience performances. This project will leverage resources of Eversource Energy Center (EEC) to organize Annual EEC Workshops which will attract users and participants from key stakeholders including utilities, regulators, state governments, state legislators and towns and cities. This S&CC project will impact a large population of graduate and undergraduate students from multiple disciplines by offering new curriculums and using programmable microgrid as a living laboratory to help students gain hands-on experiences to tackle energy resiliency and security problems. The influence of the project will reach beyond university classrooms through UConn's Power Engineering Graduate Certificate Program. This project aims to involve women, underrepresented minorities and persons with disabilities in the development of this S&CC project through multiple channels.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

智能互联社区（S& cc）的基石是一个有弹性的电力网络，它支持关键的基础设施和其他对市民至关重要的功能。然而，现有的电力网络很难满足不断增长的社区不断增长的需求。根据美国能源部的数据，2015年，美国客户平均经历了198分钟的停电，这表明电力恢复能力不尽如人意。此外，分布式能源（DERs），如越来越多地安装在美国社区的光伏（pv），无法提高电力弹性，因为它们无法承受持续的电网突发事件。除了这些挑战之外，极端天气事件和网络攻击也可能导致灾难性的停电。微电网已被证明是电力弹性的一个有前途的范例。不幸的是，由于对硬件的依赖，将社区电力基础设施转变为真正的智能微电网仍然非常困难；有限的、不可扩展的分析；更广泛的数字表面容易受到网络攻击。该项目的主要目标是创建智能可编程微电网（SPMs）。我们的关键创新是虚拟化微电网功能，使其软件定义和硬件独立，从而将DERs转换为社区微电网变得负担得起、自治和安全。为了实现我们的主要目标，我们的团队将：1)构建一个可编程的微电网平台，将传统的依赖硬件的微电网功能虚拟化为灵活的软件服务，充分解决硬件依赖问题，实现前所未有的低成本；2)为微电网开创软件定义的运行优化概念，其中运行目标、电网连接和DER参与将由软件和即插即用定义，并可以快速重新配置，基于模块化和收紧模型的发展以及一种新的异步基于价格的分解和协调方法；3)针对微电网组件或微电网的异构不确定性和即插即用在线稳定性评估，设计软件定义的分布式形式化分析；4)开发基于实时学习的网络安全功能，保护spm免受power bot攻击；5)通过对沼气池调度和控制的虚拟化，使沼气池成为环境友好、可调度的沼气池。提出的SPM将通过最近建立的网络物理试验台在CT社区微电网上进行演示。该项目将提供突破性的、可复制的技术，以经济有效地现代化美国在S&amp；CC的能源基础设施，并将今天的社区电力基础设施转变为明天的灵活服务，走向自我配置、自我修复、自我优化和自我保护。所提出的技术预计将被广泛采用，特别是在那些电力成本高、能源可靠性低、弹性性能差的社区。该项目将利用Eversource能源中心（EEC）的资源组织年度EEC研讨会，吸引包括公用事业、监管机构、州政府、州立法机构和城镇在内的主要利益相关者的用户和参与者。这个S&amp；CC项目将通过提供新的课程和使用可编程微电网作为生活实验室来帮助学生获得解决能源弹性和安全问题的实践经验，从而影响来自多个学科的大量研究生和本科生。该项目的影响将通过康涅狄格大学的电力工程研究生证书课程超越大学课堂。本项目旨在通过多种渠道让妇女、未被充分代表的少数民族和残疾人参与到该项目的发展中来。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Noisy-Intermediate-Scale Quantum Electromagnetic Transients Program

噪声中尺度量子电磁瞬变计划

• DOI: 10.1109/tpwrs.2022.3172655
• 发表时间: 2022
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Zhou, Yifan;Zhang, Peng;Feng, Fei
• 通讯作者: Feng, Fei

Reachability Analysis of Dual Active Bridge DC-DC Converters

双有源桥 DC-DC 转换器的可达性分析

• DOI: 10.1109/ecce.2019.8913224
• 发表时间: 2019
• 期刊: 2019 IEEE Energy Conversion Congress and Exposition (ECCE
• 作者: Wang, Heqiang;Tang, Zefan;Li, Yan;Zhang, Peng
• 通讯作者: Zhang, Peng

Ensuring Cyberattack-Resilient Load Forecasting with A Robust Statistical Method

• DOI: 10.1109/pesgm40551.2019.8973804
• 发表时间: 2019-08
• 期刊: 2019 IEEE Power & Energy Society General Meeting (PESGM)
• 作者: Jieying Jiao;Zefan Tang;Peng Zhang;M. Yue;Chen Chen-Chen;Jun Yan

Reachable Power Flow

可达潮流

• DOI: 10.1109/tpwrs.2020.2974164
• 发表时间: 2020
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Zhou, Yifan;Zhang, Peng
• 通讯作者: Zhang, Peng

Computationally Distributed and Asynchronous Operational Optimization of Droop-Controlled Networked Microgrids

下垂控制网络微电网的计算分布式异步运行优化

• DOI: 10.1109/oajpe.2022.3188733
• 发表时间: 2022
• 期刊: IEEE Open Access Journal of Power and Energy
• 影响因子: 3.8
• 作者: Nikmehr, Nima;Bragin, Mikhail A.;Zhang, Peng;Luh, Peter B.
• 通讯作者: Luh, Peter B.