CyberSEES: Type 2: Ocean Wave Energy and the Power Grid: Optimization and Integration

Cyber​​SEES：类型 2：海浪能和电网：优化和集成

• 批准号: 1442858
• 负责人: Shalinee Kishore
• 金额: $ 90万
• 依托单位: Lehigh University
• 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: 2015-01-15 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1442858&HistoricalAwards=false
• 关键词: CyberSEES; Type; Ocean; Wave; Energy

The objective of this project is to develop sensing, prediction, optimization, and control techniques for arrays of ocean wave energy conversion devices, known as wave farms, to make them reliable, efficient, economical, and environmentally benign. The project focuses on operational questions about the cyber-infrastructure required to control and coordinate a wave farm's many autonomous sensing and decision-making functions. Research topics include designing computational tools to assess real-time hydrodynamic interactions of wave energy converters; developing short-term and long-term wave prediction algorithms; using wave condition forecasts to dynamically control arrays of wave energy converters and energy storage systems within wave farms; enabling rapid fault detection tests that use wave sensor data to assess system state; and automating these decision-making processes within a wave farm with a multi-agent control system. The project also assesses and optimizes the sustainability and electricity market potential of wave farms by quantifying the opportunities and gains that wave power producers may avail in the electricity market due to the predictability and consistency of waves, and the effect of optimal wave farm design and control on CO2 emissions. The project includes an educational and workforce development plan to develop and administer an in-ocean course for high school students from the Lehigh Valley, PA at the Bermuda Institute of Ocean Sciences on the topic of wave energy; and to engage in community outreach via educational modules and a unique exhibit on wave energy for patrons of the Da Vinci Science Center in Allentown, PA.If successful, the project will optimize and estimate the extent to which wave energy can provide green, predictable, dispatchable power to the electricity grid. The results will yield models, algorithms, control strategies, and system architectures to improve the output power of wave farms, reduce operating costs, maximize their environmental benefits, and provide guidance for farm operators in pursuing market opportunities. The project will validate the economic and environmental feasibility of wave power and drive forward the significant research and development efforts currently underway to bring the potential of wave energy conversion to grid-scale fruition. Efficient and economic harvesting of the kinetic energy in ocean waves offers an electricity future with a more diverse supply portfolio, reduced greenhouse gas emissions, and higher sustainability impacts. The educational and workforce development components of this project will broaden understanding of the technical and environmental aspects of wave energy among a new generation of engineers and scientists, as well as among the general public.

该项目的目的是为海浪能量转换设备（称为波浪农场）的阵列开发感应，预测，优化和控制技术，以使其可靠，高效，经济和环境良性。 该项目着重于控制和协调Wave Farm的许多自主感应和决策功能所需的网络基础结构的操作问题。 研究主题包括设计计算工具来评估波能转化器的实时流体动力相互作用；开发短期和长期波浪预测算法；使用波浪条件预测，以动态控制波农场内波能转换器和能源存储系统的阵列；实现使用波传感器数据评估系统状态的快速故障检测测试；并在具有多代理控制系统的波浪农场内自动化这些决策过程。 该项目还通过量化波浪生产商可能在电力市场中使用的机会和收益来评估和优化波浪农场的可持续性和电力市场潜力，这是由于波浪的可预测性和一致性，以及最佳波浪农场设计和对CO2排放的最佳影响。 该项目包括一项教育和劳动力发展计划，旨在为来自百慕大海洋科学研究所Lehigh Valley的高中生开发和管理一项有关波动能源主题的高中生；并通过教育模块进行社区外展活动，并为宾夕法尼亚州阿伦敦的达芬奇科学中心的顾客提供独特的展览。结果将产生模型，算法，控制策略和系统体系结构，以提高波浪农场的产出能力，降低运营成本，最大化其环境利益，并为农场运营商寻求市场机会提供指导。该项目将验证波浪能力的经济和环境可行性，并推动目前正在进行的重大研发工作，以将波能量转化的潜力带入网格尺度的成果。 海浪中动力学的高效和经济收获提供了电力的未来，供应组合更多样化，温室气体排放减少以及更高的可持续性影响。 该项目的教育和劳动力发展组成部分将扩大对新一代工程师和科学家以及公众之间波动能源技术和环境方面的了解。