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NSF-CSIRO: RAI4IoE: Responsible AI for Enabling the Internet of Energy

NSF-CSIRO: RAI4IoE: Responsible AI for Enabling the Internet of Energy
NSF-CSIRO:RAI4IoE:负责任的人工智能实现能源互联网
批准号:
2302720
负责人:
Ling Liu
金额:
$59.95万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2026-08-31

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中文摘要
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英文摘要
The energy sector is going through substantial changes fueled by two key drivers: building a zero-carbon energy sector and the digital transformation of the energy infrastructure. The advances in AI technology and energy as a service market further fuel the convergence of these two drivers, resulting in the emergence of a new field of research in the energy sector – the Internet of Energy (IoE). With IoE, renewable distributed energy resources (DERs), such as electric cars, storage batteries, wind turbines and photovoltaics, can be connected and integrated for reliable energy distribution by leveraging advanced 5G-6G networks and AI technology. This allows DER owners as prosumers to participate in the energy market and derive economic incentives. DERs are inherently asset-driven and face equitable challenges (i.e., fair, diverse and inclusive). Without equitable access, privileged individuals, groups and organizations can participate and benefit at the cost of disadvantaged groups. The real-time management of DER resources not only brings out the equity problem to the IoE, it also collects highly sensitive location, time, activity dependent data, which requires to be handled responsibly (e.g., privacy, security and safety), for AI-enhanced predictions, for optimization and prioritization services, and for automated management of flexible resources. This US-Australia joint project plans to develop Equitable and Responsible AI framework, techniques and algorithms for the Internet of Energy, coined as RAI4IoE, aiming to elevate "energy poverty" by providing secure, privacy-preserving and equitable access to the networks of DERs for every citizen. The outcome of this research will advance the knowledge of responsible AI as the first principle in developing and deploying the IoE systems and services, in facilitating DER integration, promoting deep engagement with prosumers, aggregators and network operators, and enabling flexibility market of renewable energy supply.To facilitate equitable participation of all DER owners and users in the automated flexibility market, AI enabled IOE should be governed by the responsible AI frameworks and guidelines for distributed monitoring, scheduling, management, and consumption of DERs, while exercising and guaranteeing responsible and equitable AI through ensuring AI fairness and safeguarding AI privacy and AI security in an open and continuously evolving IoE ecosystem. This project will develop responsible AI frameworks, algorithms and compliance evaluation methods for the IoE, aiming to elevate "energy poverty" by providing secure, privacy-preserving and equitable access to the networks of DERs for every citizen. The project will develop innovative solutions along three dimensions. First, it develops an equitable AI framework for ensuring IoE for all, including enabling asset-poor clients to participate in distributed learning of global DER models, and integrating privacy and fairness-aware DER data collection with policy-driven data governance. Second, it develops a suite of responsible AI Algorithms and Models to increase the end-to-end resilience of IoE against disruptive events, including irregular, sparse or corrupted data, biases in data and algorithms, privacy violations, and other fraudulent DER activities. Third, it develops a suite of responsible and equitable AI compliance methods by combining explainable AI with software testing and verification methods. The research findings will lead to new generations of AI-enhanced distributed energy resource management systems. This research will also provide graduate and under-graduate students with diverse backgrounds the unique opportunities to learn responsible AI algorithm development, and the importance of equitable access to DERs from a broad cross-disciplinary perspective.This is a joint project between U.S. and Australian researchers funded by the Collaboration Opportunities in Responsible and Equitable AI under the U.S. NSF and the Australian Commonwealth Scientific and Industrial Research Organization (CSIRO).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.
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EAGER: SaTC-EDU: Privacy Enhancing Techniques and Innovations for AI-Cybersecurity Cross Training
  • 批准号:
    2038029
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2020
  • 负责人:
    Ling Liu
  • 依托单位:
CAREER: Nanoscale Thermal Transport in Hydrogen-Bonded Materials
  • 批准号:
    1946189
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2019
  • 负责人:
    Ling Liu
  • 依托单位:
CAREER: Nanoscale Thermal Transport in Hydrogen-Bonded Materials
  • 批准号:
    1751610
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2018
  • 负责人:
    Ling Liu
  • 依托单位:
TWC: Medium: Privacy Preserving Computation in Big Data Clouds
  • 批准号:
    1564097
  • 项目类别:
    Standard Grant
  • 资助金额:
    $120.0万
  • 财政年份:
    2016
  • 负责人:
    Ling Liu
  • 依托单位:
海外基金