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A methodology for estimating occupant CO_2 source generation rates from measurements in small commercial buildings

机译：一种根据小型商业建筑中的测量值估算居民CO_2来源产生率的方法

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摘要

It is necessary to know CO_2 source generation rates and system flow parameters, such as supply flow rate and overall room ventilation effectiveness, in order to evaluate cost savings for demand-controlled ventilation applied to commercial buildings. This paper presents a methodology for estimating schedules for generation rates and flow parameters using short-term testing. These parameters are used within a model that predicts return air CO_2 concentrations as part of an overall energy analysis model. As a first step in developing the methodology, two different parameter estimation techniques were evaluated using simulated data. Each method gave models that provide good predictions of return air CO_2 concentrations, but differed in terms of the identified parameters. The preferred parameter estimation method provides estimates of both average hourly source generation rates and day-to-day variations. This technique was applied to three different types of commercial buildings using field monitored data. The sites are small commercial buildings with packaged HVAC equipment and included modular schoolrooms, children's play areas in fast food restaurants and a pharmacy retail store. The impact of the length of model training data period on estimated CO_2 generation rates was investigated. Eight weeks of data is sufficient for training. Expressed in terms of the coefficient of variation, the errors in predicted CO_2 concentrations ranged from 4% to 15% depending on the sites. The predicted frequency of time that CO_2 concentrations were within a given range agreed well with the field measured data.
机译：为了评估应用于商业建筑的需求控制通风的成本节省，有必要知道CO_2源的产生率和系统流量参数，例如供应流量和整体房间通风效率。本文介绍了一种使用短期测试估算发电量和流量参数时间表的方法。这些参数在预测回风CO_2浓度的模型中使用，作为整体能量分析模型的一部分。作为开发该方法的第一步，使用模拟数据评估了两种不同的参数估计技术。每种方法所提供的模型都可以很好地预测回风中的CO_2浓度，但是所识别的参数有所不同。优选的参数估计方法提供对平均每小时源产生率和每日变化的估计。使用现场监测数据将该技术应用于三种不同类型的商业建筑。这些场所是带有包装的HVAC设备的小型商业建筑，包括模块化教室，快餐店中的儿童游乐区以及药房零售店。研究了模型训练数据周期的长度对估计的CO_2产生率的影响。八周的数据足以进行培训。以变​​异系数表示，根据位置的不同，预测的CO_2浓度的误差范围为4％至15％。 CO_2浓度在给定范围内的预计时间频率与现场测得的数据非常吻合。

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