CNIC: U.S.-Netherlands Planning Visit for Cooperative Research on Intelligent Methods Under Uncertainty for Renewable Energy Driven Smart Grids

CNIC：美国-荷兰计划访问可再生能源驱动智能电网不确定性下的智能方法合作研究

• 批准号: 1444182
• 负责人: Prashant Doshi
• 金额: $ 3.36万
• 依托单位: University of Georgia Research Foundation Inc
• 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
• 起止时间: 2015-05-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1444182&HistoricalAwards=false
• 关键词: CNIC; U.S.; Netherlands; Planning; Visit

This new, catalytic U.S.-Netherlands research collaboration addresses renewable energy-driven smart grids. Renewable energy sources include resources that are regularly replenished, such as sunlight, wind, rain, tidal waves, and geothermal heat. To pursue innovative approaches for managing the uncertainty of renewable energy sources, the U.S. principal investigator (PI) and a graduate student will visit the Netherlands to begin a collaboration with counterparts at the Delft University of Technology, a leader in European smart energy research. There they intend to work together to improve current smart grid technology for better prediction of consumer demand in the face of uncertain power generation, as is often the case in renewable energy systems. If successful, their preliminary results should contribute to improving bidirectional communication between grid operators and consumers. Early results and follow-on research may have broader impact by shaping management strategies through new approaches to modeling consumer energy usage. Success could mean better long-term prediction by employing new artificial intelligence approaches (AI), i.e., smart controls for power grids.The team expects to identify the challenges posed by the uncertainty of renewable energy generation and begin investigating intelligent methods for meeting these challenges in two priority areas: (a) planning for decentralized power generation and storage, and (b) managing congestion in grids due to asynchrony between renewable energy supply and consumer demand. The PI will work with an experienced team of eminent Dutch researchers in AI, power systems, and technology policy. They will have real operating and energy-use data from a medium voltage grid in Netherlands and intend to start developing scalable algorithms for individual decision making in multi-agent settings. Further, broader impacts are anticipated from this collaboration with an introduction of smart energy systems into research and teaching at the University of Georgia, thereby contributing to training U.S. undergraduate and graduate students in an innovative and rapidly growing energy sector with industrial relevance.

这项新的、具有催化作用的美国-荷兰研究合作致力于解决可再生能源驱动的智能电网问题。可再生能源包括定期补充的资源，例如阳光、风、雨、潮汐和地热。 为了寻求管理可再生能源不确定性的创新方法，美国首席研究员 (PI) 和一名研究生将访问荷兰，开始与欧洲智能能源研究领先者代尔夫特理工大学的同行合作。 他们打算共同努力改进当前的智能电网技术，以便在发电不确定的情况下更好地预测消费者需求，这在可再生能源系统中是常见的情况。 如果成功，他们的初步结果将有助于改善电网运营商和消费者之间的双向通信。 通过对消费者能源使用进行建模的新方法来制定管理策略，早期结果和后续研究可能会产生更广泛的影响。 成功可能意味着通过采用新的人工智能方法（AI）（即电网智能控制）进行更好的长期预测。该团队希望识别可再生能源发电的不确定性带来的挑战，并开始研究应对这些挑战的智能方法两个优先领域：(a) 规划分散式发电和存储；(b) 管理由于可再生能源供应和消费者需求之间的不同步而导致的电网拥堵。 该 PI 将与一支由荷兰人工智能、电力系统和技术政策领域的杰出研究人员组成的经验丰富的团队合作。 他们将获得来自荷兰中压电网的真实运行和能源使用数据，并打算开始开发可扩展的算法，用于多代理环境中的个人决策。 此外，预计此次合作将产生更广泛的影响，将智能能源系统引入佐治亚大学的研究和教学，从而有助于在具有工业相关性的创新和快速增长的能源领域培训美国本科生和研究生。