Using measured equipment load profiles to "right-size" HVAC systems and reduce energy use in laboratory buildings (Pt. 2)
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Using measured equipment load profiles to "right-size" HVAC systems and reduce energy use in laboratory buildings (Pt. 2)

  • Author(s): Mathew, Paul
  • Greenberg, Steve
  • Frenze, David
  • Morehead, Michael
  • Sartor, Dale
  • Starr, William
  • et al.
Abstract

There is a general paucity of measured equipment load data for laboratories and other complex buildings and designers often use estimates based on nameplate rated data or design assumptions from prior projects. Consequently, peak equipment loads are frequently overestimated, and load variation across laboratory spaces within a building is typically underestimated. This results in two design flaws. Firstly, the overestimation of peak equipment loads results in over-sized HVAC systems, increasing initial construction costs as well as energy use due to inefficiencies at low part-load operation. Secondly, HVAC systems that are designed without accurately accounting for equipment load variation across zones can significantly increase simultaneous heating and cooling, particularly for systems that use zone reheat for temperature control. Thus, when designing a laboratory HVAC system, the use of measured equipment load data from a comparable laboratory will support right-sizing HVAC systems and optimizing their configuration to minimize simultaneous heating and cooling, saving initial construction costs as well as life-cycle energy costs.In this paper, we present data from recent studies to support the above thesis. We first present measured equipment load data from two sources: time-series measurements in several laboratory modules in a university research laboratory building; and peak load data for several facilities recorded in a national energy benchmarking database. We then contrast this measured data with estimated values that are typically used for sizing the HVAC systems in these facilities, highlighting the over-sizing problem. Next, we examine the load variation in the time series measurements and analyze the impact of this variation on energy use, via parametric energy simulations. We then briefly discuss HVAC design solutions that minimize simultaneous heating and cooling energy use.

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