Differentially Private Smart Meter Data Markets: An Interdisciplinary Approach

差异化私有智能电表数据市场：跨学科方法

• 批准号: 2113082
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2113082
• 关键词: Differentially; Private; Smart; Meter; Data

Full title: Agent-based simulation approach to the provision of ancillary service by demand response and distributed storage and generation assets in the future low carbon systemThis project aims to investigate one of the most pertinent challenges facing electricity markets today. The push for rapid decarbonisation of the electricity sector is leading to increased amounts of intermittent renewable generation such as wind and solar within the power system increasing system integration costs. The need to ensure the instantaneous matching of supply and demand, as well as system security through reserve margins requires grid system operators to contract ancillary services from market participants. The decreasing costs of Battery Energy Storage (BES), developments in smart metering and Demand Side Management (DSM) provide opportunities for distributed, small-scale generation and storage assets to participate in the ancillary services market. Existing studies have focused on cost-optimal and automated dispatching solutions, using production-cost models which assume market participants typically make rational choices, respond to pricing signals, have perfect foresight, and operate in the absence of market power. Such an approach, however, does not take into account the fact that market participants exhibit heterogeneous behaviour. In particular, distributed DSM and BES assets exhibit diverse attitudes and behavioural intentions that are often ignored or only assessed qualitatively. The project proposes the use of an agent-based approach to account for behavioural difference and to allow for the formulation of appropriate incentive structures and provide insight into what is required to achieve reliable service from distributed assets.By integrating an interdisciplinary framework, the research attempts to capture the effects of different socio-psychological-economic factors that influence agent behaviours in a distributed network with the ultimate aim of translating these findings into practical and actionable policy recommendations.

基于智能体的模拟方法在未来低碳系统中通过需求响应和分布式存储和发电资产提供辅助服务该项目旨在调查当今电力市场面临的最相关的挑战之一。推动电力部门迅速脱碳，导致电力系统内风能和太阳能等间歇性可再生发电的数量增加，增加了系统集成成本。为了确保供需的即时匹配，以及通过备用保证金确保系统安全，电网系统运营商需要从市场参与者那里签订辅助服务合同。电池储能(BES)成本的下降、智能计量和需求侧管理(DSM)的发展为分布式、小规模发电和存储资产参与辅助服务市场提供了机会。现有的研究集中在成本最优和自动化调度解决方案上，使用生产成本模型，该模型假设市场参与者通常做出理性选择，对定价信号做出反应，具有完美的前瞻性，并在缺乏市场力的情况下运营。然而，这种方法没有考虑到市场参与者表现出异质行为的事实。特别是，分散的DSM和BES资产表现出不同的态度和行为意图，这些往往被忽视或只被定性评估。该项目建议使用基于代理的方法来解释行为差异，并允许制定适当的激励结构，并洞察从分布式资产获得可靠服务所需的条件。通过整合跨学科框架，研究试图捕捉影响分布式网络中代理行为的不同社会-心理-经济因素的影响，最终目的是将这些发现转化为实际和可操作的政策建议。

项目成果

Market Value of Differentially-Private Smart Meter Data

• DOI: 10.1109/isgt49243.2021.9372228
• 发表时间: 2021-02
• 期刊: 2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
• 作者: Saurab Chhachhi;F. Teng