A data analytics system for adaptive demand response in smart grids

智能电网中自适应需求响应的数据分析系统

• 批准号: 543866-2019
• 负责人: Yassine, Abdulsalam
• 金额: $ 2.19万
• 依托单位: Lakehead University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683330
• 关键词: data; analytics; system; adaptive; demand

The load demand of the residential sector in Canada constitutes a third of the country's electricity consumption according to Natural Resources Canada. With thousands of houses being built every year, the growing demand has heightened the burden on electric grids. To address this concern, utility companies strive to find ways to engage consumers in demand response (DR) programs to reduce load demand. However, DR programs face multiple research challenges in the residential sector. First, existing DR programs do not explore the issue of reducing peak load while taking into account the consumer energy consumption behavior. Second, DR schemes require accurate prediction of energy spikes at the electric feeder level (e.g., neighborhood) to be effective. Third, targeting individual appliance/device at residential homes requires a prioritization and interruption cost mechanisms to ensure proper and fair monetary compensation for consumers. To address the above challenges, in this research project we propose to work with Synergy North, Thunder Bay, Canada, to study, design, and develop an intelligent adaptive data-driven DR system. Synergy North is the power distribution company responsible for delivering electricity to 56,000 homes and businesses in the cities of Thunder Bay and Kenora in Northwestern Ontario. The outcome of this research project can lead to breakthroughs in the design and development of next-generation energy DR for the residential sector. The project benefits Canada's economy and the environment in different aspects. Canadian residential consumers adopting the proposed DR solution will be able to save in their electricity bill by engaging in energy curtailment schemes and receive compensation. Canadian utilities will be able to reduce the cost of energy during peak hours and minimize their dependency on standby generators or fossil fuel plants; thus, helping Canada's environment by decreasing greenhouse gas emissions.

根据加拿大自然资源部的数据，加拿大住宅部门的负荷需求占该国电力消耗的三分之一。随着每年成千上万的房屋建成，不断增长的需求增加了电网的负担。为了解决这一问题，公用事业公司努力寻找让消费者参与需求响应（DR）计划的方法，以减少负荷需求。然而，DR项目在住宅领域面临着多重研究挑战。首先，现有的DR方案没有在考虑消费者能源消耗行为的同时探讨降低峰值负荷的问题。其次，DR方案需要准确预测电力馈线水平（例如，社区）的能量峰值才能有效。第三，针对居民家庭的个人电器/设备需要优先排序和中断成本机制，以确保消费者获得适当和公平的货币补偿。为了应对上述挑战，在本研究项目中，我们建议与加拿大桑德贝的Synergy North合作，研究、设计和开发一个智能自适应数据驱动的DR系统。Synergy North是一家配电公司，负责为安大略省西北部桑德贝市和基诺拉市的56,000户家庭和企业提供电力。该研究项目的成果可以为住宅领域的下一代能源DR的设计和开发带来突破。该项目在不同方面有利于加拿大的经济和环境。采用拟议DR解决方案的加拿大住宅消费者将能够通过参与能源削减计划并获得补偿来节省电费。加拿大公用事业公司将能够在高峰时段降低能源成本，并最大限度地减少对备用发电机或化石燃料发电厂的依赖；因此，通过减少温室气体排放来帮助加拿大的环境。