An Occupant-Oriented Calculation Method of Building Interior Cooling Load Design

Abstract

Given continued improvement in the thermal performance of building envelopes, interior disturbances caused by occupant behavior now have the greatest impact on building loads and energy consumption. The accurate calculation of interior load during design stage was emphasized in this paper, and a new method was proposed. Indoor occupants were considered as the core of interior disturbances, and the relationship with other interior disturbances was explored. The interior heat release was arbitrarily combined with the representative cooling load to be utilized in building cooling load calculation. Field surveys were conducted in three typical university buildings: an office building, a teaching building, and a library, located in a university in Tianjin, China. The oversized chillers supplying cooling for the buildings resulted from the overestimating of the indoor occupant number and the power density of electric appliances. Through quantitative analysis, it was observed that the maximum representative interior loads were 196.43, 329.94, and 402.58 W/person, respectively, for the case buildings, at least 50% less than the empirical design data. Compared to the measured cooling load during the testing period, the accuracy of the modified cooling load was greater than 90%. This research is intended to serve as a reference for calculating and optimizing the design loads of cooling systems.

Measurement of Cooling Load-Based Occupant Behavior in Under-Actuated Zones: A Time-Variance Approach

“…The research investigated various time intervals ranging from 5 min to 2 h (Wang et al, 2018). There are five distinct time intervals, namely 5, 15, 30 min, and 1 h, each associated with a different cooling load value.…”

“…This signifies that the time interval effectively accounts for a significant portion of the cooling load variance. Generally, a desirable goodness of fit is indicated by an R-squared value of not less than 0.9 (Wang et al, 2018), depicting a strong relationship between the time interval and cooling load data. The proper time interval was selected by comparing the R-squared values obtained from the regression analysis for each of the five time intervals.…”

“…Consequently, devising accurate and efficient HVAC control strategies for under-actuated zones requires a comprehensive understanding of the complex interplay between occupant behavior and environmental dynamics. It is crucial to consider the presence and behaviour of occupants in these zones, as their activities can generate heat and impact the cooling load (Wang et al, 2018).…”

A dual-objective trade-off approach to decide the optimum design parameters for internal cooling load calculation

“…Many existing studies have suggested that the values of design parameters for calculating the cooling load of buildings are different from the actual values at operation stage [11,15,16,17], due to many uncertainties [18], such as meteorological parameters, envelope parameters and occupant-related parameters [19]. In recent years, due to the increasing improvement of building thermal insulation, the influence from outdoor weather parameters has been well controlled [20]. The internal loads, however, continuously increase in modern buildings due to the higher dependence of human activities on electrical equipment [21], and this part is closely linked to room occupancy and occupant behavior [22].…”

A Review on Indoor Environment Quality of Indian School Classrooms

“…The COVID-19 pandemic has created a terrible situation among researchers globally, but it is now time to review the health and wellbeing aspects again in all types of buildings [211][212][213][214]. The density of occupants is much higher in school classrooms than rooms in other types of buildings [215,216]. This makes school classrooms more prone to infections and communicable diseases [217][218][219].…”