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，催化的美国荷兰研究合作解决了可再生能源驱动的智能电网。可再生能源包括定期补充的资源，例如阳光，风，雨水，潮汐和地热热。 为了采用创新的方法来管理可再生能源的不确定性，美国首席研究员（PI）和研究生将访问荷兰，与欧洲智能能源研究领导者Delft University of Delft University of Delft Technology一起开始合作。 他们打算共同努力，以改善当前的智能电网技术，以更好地预测面对不确定的发电，就像可再生能源系统中一样。 如果成功，他们的初步结果将有助于改善网格操作员与消费者之间的双向交流。 早期结果和跟进研究可能通过通过建模消费者能源使用的新方法来塑造管理策略，从而产生更大的影响。 成功可能意味着通过采用新的人工智能方法（AI），即，智能控制功率网格。该团队希望确定可再生能源产生的不确定性所带来的挑战，并开始调查在两个优先领域应对这些挑战的智能方法：（a）为了使电力生成和储存量（b）在两种优先级中遇到这些挑战所带来的挑战：a供应和消费者需求。 PI将与经验丰富的AI，Power Systems和技术政策的著名荷兰研究人员团队合作。 他们将从荷兰的中型电压网格中获得实际的操作和能源使用数据，并打算开始开发可扩展的算法，以用于多代理设置中的个体决策。 此外，这次合作将对佐治亚大学的研究和教学引入研究和教学，从而预期更广泛的影响，从而促进了与工业相关性的创新且快速增长的能源领域的美国本科生和研究生。