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EAGER: Renewables: Demand response algorithms to improve electric power system stability margins

EAGER: Renewables: Demand response algorithms to improve electric power system stability margins
EAGER:可再生能源:提高电力系统稳定性裕度的需求响应算法
批准号:
1549670
负责人:
Johanna Mathieu
金额:
$27.88万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2018-08-31

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中文摘要
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英文摘要
Power systems with high penetrations of renewables operate with relatively low stability margins. Spatial demand response (DR), i.e., ways of controlling the demand for electricity throughout a geographic area, can be used to improve power system stability margins and may be less expensive and/or less environmentally impactful than alternative approaches to maintain power system stability. Additionally, increasing the potential uses of DR increases its value, making it more attractive for load aggregators and consumers to invest in sensing and communication technologies that enable it, in turn benefiting all DR applications. Results obtained through the the project will inform energy policy, for example, the design of new electricity markets and/or out-of market products to compensate loads for improving power system stability. The work will contribute to the training of one PhD student and the PI will develop a course module for a new graduate course on electricity markets and optimization. Additionally, the methods and results will be communicated to practitioners through "Spatial DR Fact Sheets."The investigators will survey existing stability margin measures and develop a short list of measures that exhibit a good trade-off between accuracy and computational complexity. The researchers will then formulate variants of the spatial DR problem, considering varying levels of realism and complexity. They will develop algorithms to solve variants of the spatial DR problem, focusing on the development of approximations that improve solvability at the expense of solution accuracy, for example, simplified representations of stability margins. Additionally, the research team will analytically and empirically evaluate the developed algorithms to determine expected and worst-case performance (in terms of stability margin improvement). Empirical testing will also allow for quantitatively exploring a variety of topics including: (i) how the parameters of flexible load impact the ability of DR to improve power system stability margins; (ii) how renewables impact stability margins and how spatial DR can be used to mitigate those impacts, enabling higher penetrations of renewables; and (iii) how the value of spatial DR changes as the level of renewable generation increases.
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SCC-IRG Track 1: Reducing Barriers to Residential Energy Security through an Integrated Case-management, Data-driven, Community-based approach
CAREER: Stochastic capacity scheduling and control of distributed energy storage enabling stacked services
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