Data-driven Methods for Integration of Distributed Energy Resources

数据驱动的分布式能源整合方法

• 批准号: RGPIN-2017-05866
• 负责人: Musilek, Petr
• 金额: $ 2.4万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711841
• 关键词: Data; driven; Methods; Integration; Distributed

The balance between demand and supply is crucial to the safe, reliable and efficient operation of electric power systems. With the advent of distributed energy resources (such as photovoltaic panels and battery storage systems), maintaining this balance becomes more and more challenging. This is caused by the unprecedented complexity of modern power grids, and by the limited control over the energy produced by intermittent energy sources, such as wind and solar. This research program will address these challenges by exploiting energy system data (including data on generation and loads, weather forecasts and energy market conditions) for the design, monitoring and control of electric power grids. This research will leverage and expand the successful results developed during the previous discovery funding cycle, and under related collaborative R&D projects with industry. It will develop new solutions for managing energy in a variety of contexts, from residential buildings, through community energy storage systems, to grids powering extensive urban and rural areas with a high penetration of dispersed generation and renewable energy sources (such as roof-top solar panels or small wind turbines combined with battery energy storage). The use of a data-driven approach is a distinguishing aspect of this proposal. It means that the safe, reliable and efficient operation of modern electric power systems will be driven by local measurements of how the system is behaving now and has behaved in the past. The data-based predictive energy management methods and agent-based balancing protocols will effectively integrate smart grid components with forecasting, analytic and control functions that will also be developed in this research. This will lead to a new type of distributed, reconfigurable systems capable of local optimization while providing global efficiency and reliability through coordination. In practice, this will mean lower power bills for consumers and improved profitability for energy companies. The developed technology will be essential in realizing the expected environmental, reliability and economic benefits of modern electrical grids. This is crucial as the implementation of renewable generation technologies is expected to double by 2020, also doubling the current Canadian investment in renewables of C$10B per year. In addition to ensuring return on this investment, the research outcomes will also bring more direct economic benefits through commercialization, technology transfer and spin-offs. Over the course of five years, this research program will also train a number of highly qualified professionals (HQPs) including up to 4 PhD and 6 MSc graduates and 10 BSc students. They will be equipped with the expertise to design, plan and operate the future smart power systems, and conduct related advanced research in an academic or industry setting.

电力供需平衡是电力系统安全、可靠、高效运行的关键。随着分布式能源（如光伏板和电池存储系统）的出现，维持这种平衡变得越来越具有挑战性。这是由于现代电网前所未有的复杂性，以及对风能和太阳能等间歇性能源产生的能源的有限控制造成的。该研究项目将通过利用能源系统数据（包括发电和负荷数据、天气预报和能源市场状况）来设计、监测和控制电网，从而解决这些挑战。