I-Corps: System for Predicting Energy Demands and Energy Usage of Buildings

这个i-Corps团队已经开发了工具来预测城市建筑和整个城市的能源需求。对于包括建筑运营商、公用事业公司、数据中心经理和许多其他用户在内的各种用户来说，能源需求预测的应用具有很高的商业价值，以准备他们的设施和/或利用节能。拟议的技术可以对为建筑环境提供信息、管理控制、设备和能源的行业和政府实体产生重大影响，因为它们可以准确预测其能源需求。高度城市化的地区为这项技术在这一广泛的应用领域产生重大影响提供了一些最大的机会。可以设想新的控制和暖通空调技术，利用预测的能源信息来优化其运行。提出的概念基于现有的天气研究和预报(WRF)中尺度模型，该模型考虑了当地天气的实时时间波动和建筑、社区和城市的特定特征，包括建筑高度、材料、光学特性、暖通空调和能源生成系统，以及居住者的使用。由于一系列可能的情况，包括但不限于电网的安全、基于精确预报的天气和/或需求的大型暖通空调设备的预期准备、更好的生产库存规划，或基于对设施能源活动的更好理解的长期能效规划，可能会显著节省能源。

This I-Corps team has developed tools to forecast energy demands for buildings in cities and for cities as a whole. The application of forecasting energy demands has high commercial value for a range of users including building operators, utility companies, data center managers, and many others to prepare their facilities and/or take advantage of energy savings. The proposed technology can have a large impact on industries and government entities that provide information, management controls, equipment, and energy resources for the built environment by accurate forecasting of their energy demands. Heavily urbanized regions offer some of the greatest opportunities for this technology to have a significant impact across this broad range of applications areas. New control and HVAC technologies may be envisioned that make use of forecasted energy information to optimize their operation.The proposed concept is based on the existing Weather Research and Forecasting (WRF) mesoscale model that considers real time temporal fluctuations of local weather and specific characteristics of buildings, neighborhoods, and cities, including building heights, materials, optical properties,HVAC and energy generation systems used, and usage by occupants. Significant energy savings could be possible due to a range of possible scenarios including but not limited to safety in the grid, anticipated preparation of large HVAC equipment based on refine forecasted weather and/or demand, better planning of production stocks, or long-term energy efficiency planning based on improved understanding of the energy activity of facilities.