I-Corps: Residential Energy Management and Analytics

I-Corps：住宅能源管理和分析

• 批准号: 1848868
• 负责人: Srinivas Shakkottai
• 金额: $ 5万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1848868&HistoricalAwards=false
• 关键词: Corps; Residential; Energy; Management; Analytics

The broader impact/commercial potential of this I-Corps project derives from its promise to positively affect not only consumers, but also enhance efficiencies in the electric energy marketplace as a whole. The basic functionality of matching users to optimal electric plans will result in both higher consumer satisfaction, and result in Retail Electric Providers (REPs) offering more competitive rate packages. Identifying the actual usage profile of appliances over time and providing actionable information to consumers will enable consumers to take informed decisions on appliance purchases, as well as manufacturers to optimize designs with real-world inputs. The platform will enable the solution of system-wide problems faced by utility companies like peak period demand surges to be countered through demand response initiatives such as incentivizing customers to modify their usage patterns to smoothen the load curve. Each function of the proposed system is geared toward addressing a specific source of friction in the electric energy marketplace, and consequently also possesses commercial potential. Thus, the overall economic impact will be on consumers, REPs, utility companies and appliance manufactures, while promoting a greater knowledge and engagement among the electricity consumers.This I-Corps project explores the value of creating a bundled energy management system aimed at residential users. The system uses machine-learning-based analytics of the customer's daily, weekly, monthly, and seasonal energy usage trends to offer potential savings through (1) recommending the best retail energy service provider plan matching the customer's usage patterns, (2) incentivizing customers to enable full integration with smart home devices, including smart thermostats, (3) identifying and predicting the electricity consumption of different appliances and providing actionable information on their optimal usage and maintenance, and (4) services to allow customers to navigate through the process of switching plans. A smartphone app available for the iOS and Android platforms forms the customer interface to the system. The key novelties of this project lie in the development and integration of machine learning tools and behavioral economics ideas into the domain of residential energy management. The project is founded on research into the design, development and validation of such tools in contexts such as predicting residential energy usage over time, disaggregating usage on a per-appliance basis, and experimentation on how best to motivate users to engage in energy usage behavior that induces efficient grid operation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该 I-Corps 项目的更广泛影响/商业潜力源于其承诺不仅对消费者产生积极影响，而且还提高整个电力能源市场的效率。将用户与最佳电力计划相匹配的基本功能将提高消费者满意度，并导致零售电力提供商 (REP) 提供更具竞争力的费率套餐。 随着时间的推移，识别电器的实际使用情况并向消费者提供可操作的信息将使消费者能够就电器购买做出明智的决定，并使制造商能够根据现实世界的输入来优化设计。 该平台将能够解决公用事业公司面临的系统范围的问题，例如通过需求响应举措来应对高峰期需求激增，例如激励客户修改其使用模式以平滑负载曲线。 所提议系统的每个功能都旨在解决电能市场中的特定摩擦源，因此也具有商业潜力。 因此，整体经济影响将针对消费者、REP、公用事业公司和电器制造商，同时促进电力消费者的更多知识和参与。该 I-Corps 项目探讨了创建针对住宅用户的捆绑式能源管理系统的价值。 该系统使用基于机器学习的方式对客户的每日、每周、每月和季节性能源使用趋势进行分析，通过以下方式提供潜在的节省：(1) 推荐符合客户使用模式的最佳零售能源服务提供商计划，(2) 激励客户实现与智能家居设备（包括智能恒温器）的全面集成，(3) 识别和预测不同电器的用电量，并提供有关其最佳使用和维护的可操作信息，以及 (4) 允许客户浏览整个过程的服务切换计划。适用于 iOS 和 Android 平台的智能手机应用程序构成了系统的客户界面。 该项目的主要新颖之处在于机器学习工具和行为经济学思想的开发和集成到住宅能源管理领域。 该项目的基础是对此类工具的设计、开发和验证的研究，例如预测住宅能源使用情况随时间的推移、按每台电器分类使用情况以及如何最好地激励用户参与能源使用行为的实验该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。