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CAREER: Redesign of Ancillary Services via Aggregation and Disaggregation of Information, Flexibility, and Capability

职业：通过信息、灵活性和能力的聚合和分解重新设计辅助服务

基本信息

批准号：
2238414
负责人：
Liang Du
金额：
$ 50.18万
依托单位：
Temple University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2023
资助国家：
美国
起止时间：
2023-03-01 至 2028-02-29
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238414&HistoricalAwards=false
关键词：
CAREER Redesign Ancillary Services via

项目摘要

This NSF CAREER project aims to provide the theoretical foundation of aggregating and disaggregating nodal generation capacity, flexibility, and information, which will allow exploiting the full potential of distributed energy resources and electrified transportation in future decarbonized power grids. The project will transform the conventional energy and ancillary service co-optimization-based power grid operation scheme into a novel capacity-flexibility dispatch and redispatch control framework. This will be achieved by converting existing resource planning problems with system-wide requirements into granular control problems with multi-scale, multi-domain nodal requirements. The intellectual merits of the project include developing nodal demand, capacity, flexibility composite models and computationally efficient aggregation algorithms with guaranteed characteristics under uncertainty. The broader impacts of the project include promoting the integration of research and education for students with diverse backgrounds. Pre-college and undergraduate students, especially from underrepresented groups, will benefit from resulted summer research programs, workshops, capstone projects, and open-access curriculum materials. If successful, this project will also provide power system operators with technology advancements to integrating large-scale renewable energy and enhancing grid resilience.Uncertainties by fast-growing penetration of distributed energy resources, proliferation of electrified transportation, and climate change intertwine and amplify challenges posed on power system reliability. Consequently, widespread and prolonged power outages have been occurring increasingly more frequently and severely in recent years, which illustrates the inadequacy of existing ancillary services provided by reserving unloaded capacity on generation resources. The proposed project will redesign conventional resource planning-based ancillary services into a novel capacity-flexibility dispatch/redispatch control problem through three major technical innovations: (1) Mathematical models and effective aggregation of nodal flexibility provided by both distributed energy resources and electrified transportation through novel cost-aware, multi-period optimization techniques. (2) Computationally effective, granular control policies for the proposed nodal level co-dispatch are established as theoretical co-optimization problems converted through transformations and information aggregation, which will be solved both precisely with guaranteed performance and approximately as a data-driven problem. (3) Aggregating nodal information to determine nodal ancillary service requirements by extended Minkowski sum of polytopes, which will be further integrated into a unified theoretical framework by Difference of Convex programming.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.

该 NSF CAREER 项目旨在提供汇总和分解节点发电能力、灵活性和信息的理论基础，这将允许在未来脱碳电网中充分开发分布式能源和电气化运输的潜力。该项目将把传统的能源与辅助服务协同优化的电网运行方案转变为新型的容量灵活调度和再调度控制框架。这将通过将现有的具有全系统需求的资源规划问题转化为具有多尺度、多域节点需求的细粒度控制问题来实现。该项目的智力优点包括开发节点需求、容量、灵活性复合模型以及在不确定性下保证特性的计算高效的聚合算法。该项目更广泛的影响包括促进具有不同背景的学生的研究和教育的融合。大学预科生和本科生，特别是来自代表性不足群体的学生，将受益于由此产生的夏季研究项目、研讨会、顶点项目和开放获取课程材料。如果成功，该项目还将为电力系统运营商提供技术进步，以整合大规模可再生能源并增强电网弹性。分布式能源快速增长的渗透率、电气化交通的普及和气候变化等不确定性因素交织在一起，加剧了电力系统可靠性面临的挑战。近年来，大面积、长时间停电的情况越来越频繁、严重，这说明现有通过预留发电资源空载容量提供的辅助服务的不足。该项目将通过三大技术创新，将传统的基于资源规划的辅助服务重新设计为一种新型的容量灵活性调度/再调度控制问题：（1）通过新颖的成本感知、多周期优化技术，对分布式能源和电气化交通提供的节点灵活性进行数学模型和有效聚合。（2）所提出的节点级协同调度的计算有效的细粒度控制策略被建立为通过变换和信息聚合转换的理论协同优化问题，该问题将在保证性能的情况下精确解决，并近似作为数据驱动问题来解决。（3）通过扩展多胞体明可夫斯基和来聚合节点信息，以确定节点辅助服务需求，并通过凸差规划进一步整合到统一的理论框架中。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，认为值得支持。