Assessing the potential of ecobee smart thermostats to save energy through load shifting

评估 Ecobee 智能恒温器通过负载转移节省能源的潜力

• 批准号: 517474-2017
• 负责人: Touchie, Marianne
• 金额: $ 1.82万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639826
• 关键词: Assessing; potential; ecobee; smart; thermostats

In 2014, buildings accounted for approximately 12% of Canadas greenhouse gas (GHG) emissions. Over 12% of households arecondominiums, which is projected to rise as high as 53% within the next 20 years. HVAC energy use represents more than half ofenergy consumption in these buildings, so reducing GHG emissions in this area can significantly affect building sector emissions.In Ontario, operational costs and GHG emissions associated with incremental electricity consumption during on-peak hours aremuch higher those associated with consumption during off-peak hours. As a result, shifting electrical load in multi-unit residentialbuildings (MURBs) to off-peak hours has the potential to reduce costs and GHG emissions. Additionally, studies have shown thatcentral heating plants often operate at lower efficiencies for low loading periods so flattening the boiler load profile can potentiallyimprove system efficiency and will reduce excessive cycling. Smart thermostats employing load shifting strategies can be used tooptimize space conditioning profiles to reduce costs and emissions. In order to determine the impact of load shifting andoccupancy-based control mechanisms in MURBs, 80 ecobee3 smart thermostats and energy monitoring equipment will beinstalled in two condominium buildings. This project will assess the how the smart thermostat's load shifting algorithm can reduceGHG emissions in MURBs and develop a model to estimate this impact in other buildings. The study can be used to developfuture evidence-based energy conservation and demand response programs for MURBs and will be used to adapt ecobee`stechnologies for use in the growing MURB sector.

2014年，建筑物约占加拿大温室气体（GHG）排放量的12%。超过12%的家庭是公寓，预计在未来20年内将上升至53%。暖通空调的能耗占这些建筑能耗的一半以上，因此减少这一领域的温室气体排放可以显著影响建筑行业的排放。在安大略，与高峰时段增量电力消耗相关的运营成本和温室气体排放远远高于与非高峰时段消耗相关的成本和排放。因此，将多单元住宅建筑（MURB）中的电力负荷转移到非高峰时段具有降低成本和温室气体排放的潜力。此外，研究表明，集中供热厂通常在低负荷期间以较低的效率运行，因此使锅炉负荷曲线平坦化可以潜在地提高系统效率，并减少过度循环。采用负载转移策略的智能恒温器可用于优化空间空调配置文件，以降低成本和排放。为了确定负荷转移和基于电容的控制机制在MURB中的影响，将在两栋公寓楼中安装80个ecobee 3智能恒温器和能源监测设备。该项目将评估智能恒温器的负载转移算法如何减少MURB中的温室气体排放，并开发一个模型来估计其他建筑物的这种影响。该研究可用于开发未来基于证据的MURB节能和需求响应计划，并将用于调整生态蜂技术，以用于不断增长的MURB部门。