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A Case Study in Reconciling Modeling Projections with Actual Usage

机译:将建模投影与实际用法相协调的案例研究

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A subdivision, built near Sacramento, CA was designed to incorporate advancedresidential energy efficiency strategies as part of Department of Energy’s (DOE) BuildingAmerica (BA) program. Energy efficiency measures included attic radiant barrier, condensingfurnace, high efficiency air conditioning, tankless gas water heater, efficient lighting, and thirdparty building inspections. Detailed DOE-2 building simulation was used to project energyperformance and utility bills. Analyzing one year of billing data obtained from these homes aswell as 100 surrounding reference homes suggest that even when detailed data is known, energysimulation is not effective in characterizing energy by end use. Results show natural gas use onaverage was 36% lower than simulated projections and supports a study done on Californiacompliance software model projections (KEMA et al. 2010). Electrical use patterns on the otherhand varied from model projections inconsistently, due in part to anomalies not accounted for inthe model. Results indicate that household variations in energy usage patterns and appliancepenetration rates have a very strong effect on total energy use. This issue seems especiallypronounced in mild climate regions of the country where miscellaneous plug loads, lighting, andlarge appliances can exceed 80% of the total electric use. Understanding and influencinghomeowner behavioral patterns is important in delivering high performing homes to the market.Additional research into the effectiveness of energy control mechanisms, such as motiondetecting lighting, phantom load controls, home energy displays, and educational programs arerequired in order to incorporate these savings into building simulations.
机译:在加利福尼亚州萨克拉曼多附近建立的一个分区旨在将先进的住宅能源效率策略纳入能源部(DOE)美国建筑(BA)计划的一部分。节能措施包括阁楼辐射屏障,冷凝炉,高效空调,无罐式燃气热水器,高效照明和第三方建筑检查。详细的DOE-2建筑模拟用于预测能源绩效和水电费。对从这些房屋以及100个周围参考房屋获得的一年计费数据进行的分析表明,即使知道了详细数据,能源模拟仍无法有效地表征最终用途的能源。结果表明,平均天然气使用量比模拟预测值低36%,并支持有关Californiacompliance软件模型预测的研究(KEMA等,2010)。另一方面,用电模式与模型预测不一致,部分原因是模型中未考虑异常。结果表明,家庭在能源使用方式和设备普及率方面的差异对总能源使用量有很大的影响。在该国气候温和的地区,这个问题似乎尤为明显,在该地区,各种插头,照明和大型电器的用电量可能超过总用电量的80%。理解和影响房主的行为模式对于将高性能住房推向市场非常重要。还需要对能量控制机制的有效性进行更多研究,例如运动检测照明,幻像负载控制,家庭能量显示和教育计划,以便将这些节省的资金纳入其中建筑模拟。

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