UNS: Energy Sustainability of Green Commercial Buildings: An Empirical Assessment

1509077 Qiu，Yueming商业建筑占美国电力消耗的36%。工程，组织和行为因素和激励措施之间的相互作用决定了建筑物的能源使用和相关的环境可持续性，并可能导致真正的能源性能和理论上可能的性能之间的分歧。对节能商业建筑设计和技术的投资不断增加。在进行统计使用后评估（POE）的研究中，关于“绿色”商业建筑（即LEED建筑）是否实际上节省能源一直存在争议，这使人们对它们的能源可持续性产生了怀疑。评价绿色商业建筑的真实能耗性能需要对长期数据历史和较大样本量进行实证分析。为了全面了解能源可持续性，必须研究组织管理和居住者行为等社会因素，以及能源使用的环境和经济影响。此外，评估这些因素对建筑物能源使用时间（即高峰时段与非高峰时段）的影响对于了解电力消耗的环境（即碳）成本至关重要。该项目将在一个城市（凤凰城）使用综合建筑能源数据集进行这种全面的能源可持续性分析，该城市是世界上许多迅速发展的炎热和干燥城市地区的典型能源使用模式。具体而言，该项目将：1）基于大型数据集提供绿色商业建筑真实能源性能的可靠统计证据; 2）量化绿色商业建筑对电网负荷分布和发电燃料组合的影响; 3）应用调查来量化决定观察到的建筑能源性能的工程、组织和行为因素; 4）评估凤凰城大都市区绿色商业建筑的系统环境和经济影响。该项目将通过一种新的“大数据”实证方法，推进绿色商业建筑能源可持续性的工程研究。首先，该项目将分析比以前研究的商业建筑更大和更可靠的数据集，包括历史用电量和其他关键的建筑水平属性。该数据集包含700多个能源之星星星和LEED商业建筑，以及超过17，000个商业电力客户。其次，与现有的POE研究相比，本项目采用了更严格和先进的统计分析，包括匹配，面板回归和非参数建模。重要的是，这个项目使用了更可信的控制组。第三，该项目将提供第一个可靠的经验证据，说明绿色建筑技术如何按时间和季节影响环境足迹，这对于确定与电力消耗相关的环境成本至关重要。最后，本项目将实证性地探索人-环境耦合系统中的相关因素，包括工程（如技术可靠性和兼容性）、组织（如委托-代理问题）和行为（如有限理性）因素，这些因素会影响商业建筑的可观察能源性能和对环境可持续性的影响。所产生的见解可以由包括国家能源政策制定者、城市环境规划者、能源服务公司、建筑工程师、建筑业主和公用事业公司在内的从业者直接实施。

1509077Qiu, YuemingCommercial buildings are responsible for 36% of electricity consumption in the United States. Interactions among engineering, organizational, and behavioral factors and incentives determine building energy use and related environmental sustainability, and potentially cause divergence between true energy performance and theoretically possible performance. There has been increasing investment in energy efficient commercial building designs and technologies. Among the studies that conduct statistical post-occupancy evaluations (POE), there has been debate about whether "green" commercial buildings (i.e. LEED buildings) actually save energy or not, and this casts doubt on their energy sustainability. Evaluating the true energy performance of green commercial buildings requires empirical analysis of long data histories and larger sample sizes. To understand a complete picture of energy sustainability, social factors such as organizational management and occupant behaviors, as well as environmental and economic impacts of energy use, must be studied. Additionally, evaluating the effects of these factors on the timing of building energy use (i.e. peak hours versus non-peak hours) is essential to understand environmental (i.e. carbon) costs of electricity consumption. This project will conduct such holistic energy sustainability analysis using a comprehensive building energy dataset in a city (Phoenix) that is typical of energy use patterns in many of the world's rapidly growing hot and dry urban areas. Specifically, the project will: 1) provide reliable statistical evidence of the true energy performance of green commercial buildings based on large datasets; 2) quantify the impact of green commercial buildings on power grid load profiles and electricity generation fuel mix; 3) apply surveys to quantify engineering, organizational, and behavioral factors that determine observed building energy performance; and 4) evaluate the systemic environmental and economic impacts of green commercial buildings in the Phoenix metropolitan area. The project will advance engineering research into energy sustainability of green commercial buildings through a novel "big data" empirical approach. First, this project will analyze much larger and reliable datasets of commercial buildings than previously studied, including historical electricity consumption and other key building level attributes. The dataset contains more than 700 Energy Star and LEED commercial buildings, and more than 17,000 total commercial electric customers. Second, compared to existing POE studies, this project adopts more rigorous and advanced statistical analysis including matching, panel regression, and nonparametric modelling. Importantly, this project uses much more credible control groups. Third, this project will provide the first empirically reliable evidence of how green building technologies impact environmental footprints by time of day and season, which are critical for determining environmental costs associated with electricity consumption. Finally, this project will empirically explore the interrelated factors in the coupled human-environmental systems including engineering (e.g. technical reliability and compatibility), organizational (e.g. principal-agent problem), and behavioral (e.g. bounded rationality) factors that influence the observed energy performance of commercial buildings and the impact on environmental sustainability. The insights produced may be directly implemented by practitioners including state energy policy makers, city environment planners, energy service companies, building engineers, building owners, and utility companies.