Rusek Robert, Melendez Frigola Joaquim, Colomer Llinas Joan
Institute of Informatics and Applications, University of Girona, Av. LluisSantaló S/N,Bloc P IV, Research group eXiT, 17003 Girona, Spain.
Energy Sustain Soc. 2022;12(1):13. doi: 10.1186/s13705-022-00336-6. Epub 2022 Feb 21.
In recent years, the monitoring of occupant presence patterns has become an imperative for building energy optimization. Very often, there is a significant discrepancy between the building energy performance predicted at the design stage and the actual performance rendered during the building operation. This stems from the difference in user occupancy. In spite of this, user interaction and feedback are rarely taken into account and evidence of the impact of occupant presence patterns on energy consumption is still scarce. Thus, the purpose of this study is to apply crowd-sensing techniques to understand how energy is consumed and how appropriate performance indicators should be defined to provide inputs for building operations regarding more efficient use of resources.
Monitoring strategies were implemented in an office lab with controlled variables to collect quantitative data on occupancy patterns, ambient factors and energy consumption. In addition, crowd-sensing techniques were applied to model user activity in different ambient conditions over time and to contrast their occupancy with energy consumption patterns in combination with new inquiry tools to identify how occupants perceive their comfort level. In addition, a set of energy efficiency indicators was used to compare energy performance over different periods.
It was discovered that there is a strong relation between user occupancy patterns and energy consumption. However, more than 50% of energy was consumed when no user activity was registered. Energy performance indicators revealed that measuring energy efficiency in terms of kWh per surface area encourages a less efficient use of space and, therefore, including a coefficient of person hours is advisable. It was also discovered that users do not fully rely on feedback mechanisms and they prefer to take action to adapt the ambient conditions rather than simply expressing their opinion. Analysis of energy usage during the Covid-19 lock down revealed substantial use of energy contrary to what was expected. This was because home computers were used as terminals only, while the actual tasks were performed on the lab computers, using remote desktop connections, which were turned on 24/7. In addition, energy consumed by each employee at his/her home should be taken into account. Moreover, a set of practical recommendations was formulated.
近年来，监测居住者的存在模式已成为建筑能源优化的当务之急。在很多情况下，设计阶段预测的建筑能源性能与建筑运行期间的实际性能之间存在显著差异。这源于用户占用情况的不同。尽管如此，用户交互和反馈很少被考虑在内，而且居住者存在模式对能源消耗影响的证据仍然很少。因此，本研究的目的是应用群体传感技术来了解能源是如何被消耗的，以及应如何定义合适的性能指标，以便为建筑运营提供关于更有效利用资源的输入信息。
在一个具有可控变量的办公室实验室中实施监测策略，以收集关于占用模式、环境因素和能源消耗的定量数据。此外，应用群体传感技术对不同环境条件下用户随时间的活动进行建模，并将他们的占用情况与能源消耗模式进行对比，同时结合新的询问工具来确定居住者如何感知他们的舒适度。此外，使用一组能源效率指标来比较不同时期的能源性能。
发现用户占用模式与能源消耗之间存在很强的关系。然而，在没有记录到用户活动时，超过50%的能源被消耗。能源性能指标表明，以每表面积千瓦时来衡量能源效率会鼓励对空间的低效利用，因此，纳入人均小时系数是可取的。还发现用户并不完全依赖反馈机制，他们更愿意采取行动来调整环境条件，而不是简单地表达他们的意见。对新冠疫情封锁期间能源使用情况的分析表明，与预期相反，能源消耗仍然很大。这是因为家用电脑仅用作终端，而实际任务是通过远程桌面连接在实验室电脑上执行的，这些电脑全天24小时开机。此外，应考虑每位员工在家中消耗的能源。此外，还制定了一套实用建议。
