Using TensorFlow for Analysis, Learning and Optimization of Net-Zero Homes Energy Data

I-EMS Group Ltd（I-EMS）是一家先进的软件和分析解决方案提供商，用于优化具有多种分布式能源的智能配电网的规划，运营和控制。I-EMS提供能源管理系统（EMS）作为分布式能源市场的连贯解决方案，利用预测，网络分析和能源贸易的尖端技术。EMS是一个自动程序，连接到物理建筑物内的所有传感器，用于监控能源资产及其相应负载的产生和消耗。物联网（IoT）传感器和控制设备阵列生成并可使用大量数据，可用于提高连接系统的效率和能源性能。该合作项目的目标是为I-EMS集团现有的EMS基础设施添加先进的数据分析和大数据组件，这些组件可以快速实施，以提高系统效率并降低I-EMS客户的能源使用量。利用来自净零能源家庭的一年物联网传感器/设备数据，I-EMS集团正在与Nooshin Beheshti教授和Seneca信息技术管理与安全学院合作，设计，开发和测试基于人工智能的算法和数据挖掘方法，并将其实施到新的能源配置优化模块中。

I-EMS Group Ltd (I-EMS) is an advanced software and analytics solution provider for optimal planning, operation and control of smart distribution grids with multiple distributed energy resources. I-EMS provides an energy management system (EMS) as a coherent solution for the distributed energy market, utilizing cutting-edge technologies in forecasting, network analysis, and energy trade. The EMS is an autonomous program connected to all sensors within physical buildings that monitor the generation and consumption of energy assets and their respective loads. An abundance of data are generated and available for use from the array of Internet-of-Things (IoT) sensors and control devices and can be used to improve the efficiency and energy performance of connected systems. The goal of this collaborative project is to add advanced data analytics and big data components to I-EMS Group's existing EMS infrastructure, which can be implemented quickly to improve system efficiency and lower energy usage for I-EMS customers. Utilizing a year of IoT sensor/device data from net-zero energy homes, I-EMS Group is collaborating with Professor Nooshin Beheshti and Seneca's School of Information Technology Administration and Security to design, develop and test AI-based algorithms and data mining methods and implement them into new energy profile optimization modules.