Development of expected performance standards for SolarSatData for BuildingsTM and calculation of resulting energy and C02 emission reductions

制定 SolarSatData for BuildingsTM 的预期绩效标准并计算由此产生的能源和二氧化碳排放量减少量

• 批准号: 452615-2013
• 负责人: OBrien, William
• 金额: $ 1.82万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=541011
• 关键词: Development; expected; performance; standards; SolarSatData

Buildings represent a significant environmental impact - particularly with regards to their substantial energy use. Model predictive control (MPC) is a promising solution to achieving significant savings to these impacts, including reduced secondary energy use, greenhouse gas emissions, and energy infrastructure. MPC uses weather forecasts and building simulation models to optimize future control sequences based on predicted energy performance. However, its success is dependent on high-quality, accurate weather forecasts so that proper on-line control setpoints can be implemented to minimize energy costs while maintaining occupant comfort.

建筑物对环境产生重大影响，特别是在其大量能源使用方面。模型预测控制 (MPC) 是一种很有前途的解决方案，可以显着减少这些影响，包括减少二次能源使用、温室气体排放和能源基础设施。 MPC 使用天气预报和构建仿真模型，根据预测的能源性能来优化未来的控制序列。然而，它的成功取决于高质量、准确的天气预报，以便可以实施适当的在线控制设定点，以最大限度地降低能源成本，同时保持居住者的舒适度。