CSR: Small:Collaborative Research: System Support for Green Homes

鼓励更广泛地采用可再生能源是减少我们对电网依赖的关键。虽然在家中安装太阳能电池板越来越普遍，但管理它们产生的能量的过程既需要手动操作，也需要临时安排。在这项工作中，PI正在建立一个基础设施，用于收集和分析绿色家庭中的能源产生、能源消耗和用户行为的数据;以及一个使用新型的基于减排的评估平台验证的绿色家庭能源管理的综合方法。该项目使用定制的测量基础设施，对各种可再生能源供电的家庭进行了广泛的研究。该研究考察了可再生能源的能源产生以及各种设备消耗能源的方式和原因。结果通知一个整体控制系统的设计，匹配预测的供应与需求的一组分布式设备在家里。此外，该系统正在一些家庭中部署，并使用一个推荐系统进行评估，该推荐系统作为一个移动的应用程序，建议用户何时应该运行设备。该项目支持对鼓励在家庭中采用更环保的做法至关重要的研究，并使在EPSCoR机构任教的PI Banerjee和在本科院校任教的PI Rollins之间的合作成为可能。此外，该项目正在开发一个社区服务一级课程，通过收集和分析能源消费做法的数据，引入计算，提高对绿色能源概念的认识。

Encouraging broader adoption of renewable energy sources is key to minimizing our dependence on the electric grid. Though installation of solar panels at homes is increasingly common, the process of managing the energy they generate is both manual and ad hoc. In this work, the PIs are building an infrastructure for data collection and analysis of energy generation, energy consumption, and user behavior in green homes; and an an integrated approach to green home energy management validated using a novel recommendation-based evaluation platform. Using a custom-built measurement infrastructure, the project conducts a broad study of homes powered by a variety of renewable sources. The study examines both energy generation by renewable sources as well as how and why energy is consumed by a variety of devices. The results inform the design of a holistic control system that matches predicted supply with demand of a distributed set of devices in the home. Moreover, the system is being deployed in a few homes and evaluated using a recommendation system implemented as a mobile application that suggests when users should run devices.This project supports research critical to encouraging adoption of more environmentally responsible practices in the home and enables a collaboration between PI Banerjee, who teaches at an EPSCoR institution, and PI Rollins, who teaches at an undergraduate institution. Further, the project is developing a CS1 course that will increase awareness of green energy concepts by introducing computing through collection and analysis of data on energy consumption practices.