Elsevier

Applied Energy

Volume 111, November 2013, Pages 515-528
Applied Energy

On variations of space-heating energy use in office buildings

https://doi.org/10.1016/j.apenergy.2013.05.040Get rights and content

Highlights

  • Space heating is the largest energy end use in the U.S. building sector.

  • A key design and operational parameters have the most influence on space heating.

  • Simulated results were benchmarked against actual results to analyze discrepancies.

  • Yearly weather changes have significant impact on space heating energy use.

  • Findings enable stakeholders to make better decisions on energy efficiency.

Abstract

Space heating is the largest energy end use, consuming more than seven quintillion joules of site energy annually in the U.S. building sector. A few recent studies showed discrepancies in simulated space-heating energy use among different building energy modeling programs, and the simulated results are suspected to be underpredicting reality. While various uncertainties are associated with building simulations, especially when simulations are performed by different modelers using different simulation programs for buildings with different configurations, it is crucial to identify and evaluate key driving factors to space-heating energy use in order to support the design and operation of low-energy buildings. In this study, 10 design and operation parameters for space-heating systems of two prototypical office buildings in each of three U.S. heating climates are identified and evaluated, using building simulations with EnergyPlus, to determine the most influential parameters and their impacts on variations of space-heating energy use. The influence of annual weather change on space-heating energy is also investigated using 30-year actual weather data. The simulated space-heating energy use is further benchmarked against those from similar actual office buildings in two U.S. commercial-building databases to better understand the discrepancies between simulated and actual energy use. In summary, variations of both the simulated and actual space-heating energy use of office buildings in all three heating climates can be very large. However these variations are mostly driven by a few influential parameters related to building design and operation. The findings provide insights for building designers, owners, operators, and energy policy makers to make better decisions on energy-efficiency technologies to reduce space-heating energy use for both new and existing buildings.

Introduction

According to the 2010 United States Department of Energy (USDOE) Building Energy Databook [1], space heating is the largest end use in the U.S. building sector. Space heating consumes about 5.2 and 2.3 quintillion joules of annual site energy for residential and commercial buildings, respectively. The U.S. Energy Information Administration (EIA) 2003 Commercial Buildings Energy Consumption Survey (CBECS) [2] indicates that office buildings are the most common building type, comprising the largest floor area and consuming the most energy in the commercial building sector. In office buildings, space heating consumes about one-third of total site energy, according to the CBECS. It is therefore crucial to study the space-heating energy use of such buildings in order to reduce their energy use and carbon emissions.

The growth in energy use allocated to the commercial buildings sector averaged 2.8% annually from 1950 to 2006 [3]. In the past decade, energy-saving technology improvements in office buildings have received a lot of attention [3], [4], [5], [6], [7], [8], [9]. Andrew and Krogmann [8] investigated issues affecting the adoption of energy-efficient heating technology in U.S. office buildings. The factors he studied included energy price, building location, floor area, rental, building vintage, window area, and office equipment. In his study, the multinomial logistic analysis of these factors employed spreadsheet manipulations and statistical calculations. Liu et al. [9] describe a mathematical modeling framework for energy systems to improve energy efficiency and environmental performance of commercial buildings, with the goal of achieving optimal energy designs. However, a systematic integration approach for truly achieving optimal energy-systems design in commercial buildings is still lacking. Recently, more new building designs aim to green buildings or zero net energy buildings, emphasizing the importance of energy-efficiency technologies and system designs, building operation and maintenance, and occupant behavior. Good operational practice and high building design efficiency could lower the energy use of space heating [10], [11]. Santin [12] looked at the relationship between user behavior and space-heating energy consumption, and concluded that behavior patterns could be used in space-heating energy calculations, and usage profiles with different behaviors could be discerned.

Pan et al. [13] simulated effects of external wall insulation thickness on annual cooling and heating energy uses of an office building in three Chinese climates. It was found that, for heating dominant climate like Beijing, more insulation reduced the combined annual cooling and heating energy uses of perimeter offices facing all four cardinal orientations. More insulation reduces annual energy uses of offices facing North, East, and West, but not necessarily for the south facing office. For cooling dominant climate like Guangzhou more insulation did not reduce annual energy use at all. Yang et al. [14] surveyed envelope designs of existing office buildings in five major Chinese climates, and found the overall thermal transfer value of envelope was much higher than the current local energy code and almost double the ASHRAE Standard 90.1-2001. More insulation of exterior walls and roofs was recommended to reduce heating energy use for buildings in cold climate. Dovjak et al. [15] studied problem of High Heating energy use in Slovenian buildings with exergy and energy analysis. Their energy analyses showed that less thermal insulation contributed the most to the highest heating energy demand especially in colder climate. The results from exergy analysis drew similar conclusions – insulation has much bigger effect than effect of boiler efficiency. However, the most effective solution is to improve building envelope together with boiler efficiency. Yildiz and Gungor [16] presented energy and exergy analyses for the whole process of space heating in buildings in Turkey climates using simplified steady state heating load and energy calculations. Three heating systems, liquid natural gas (LNG) fired conventional boiler, LNG condensing boiler, and air-to-air heat pump, were compared from the power plant through the building envelope using exergy analysis. Eskin and Turkmen [17] studied the interactions between different conditions, control strategies and heating/cooling loads in office buildings in the four major climatic zones in Turkey using building energy simulation. Calibrated energy models were used to examine energy conservation opportunities on annual cooling, heating and total building load at four major cities. The effect of the parameters like the climatic conditions, insulation and thermal mass, aspect ratio, color of external surfaces, shading, window systems including window area and glazing system, ventilation rates and different outdoor air control strategies on annual building energy requirements is examined and the results are presented for each city.

The lack of knowledge about the factors that determine total building energy use is a significant barrier to achieving substantial building energy efficiency. Recently, a few studies [18], [19] using simulations to calculate building performance showed relatively low space-heating energy use compared with rules-of-thumb and large discrepancies in space-heating energy use between different simulation programs, which raised concerns of whether simulation can be used to predict space-heating energy use. While various uncertainties are associated with building simulations, especially when simulations are performed by different modelers using different simulation programs for buildings with different configurations, it is crucial to identify and evaluate key driving factors to space-heating energy use to support the design and operation of low-energy buildings. These key driving factors can be categorized into six groups: climate conditions, building envelope, space-heating systems, building operation and maintenance, occupant behavior, and indoor environmental conditions.

The New Buildings Institute recently published a simulation study on total site energy use in midsize office buildings [20] to look at key driving factors of building energy use. Twenty-eight building characteristics were identified and grouped into design assets, operation practice, and tenant behaviors. Three systems and equipment-operation practices with respect to building energy use were identified by using different performance values for each characteristic parameter. Simulation results showed the key factors that affect total site energy use in midsize office buildings in 16 U.S. climates. Total site energy is a simple sum of electricity use and gas use – one unit of electricity is valued the same as one equal unit of natural gas; no generation or transmission or distribution loss is considered. As the total energy use of a building includes all end uses such as lighting, space heating, space cooling, service water heating, and plug-loads, the key driving factors of a building’s total energy use would be very different from those of a specific end use like space heating. The use of source or primary energy would be a better indicator of building energy performance.

The objective of the current study is to identify, understand, and quantify important building design and operation parameters that can have significant impacts on space-heating energy use in office buildings, with different characteristics located in different heating climates, by computer simulations with EnergyPlus. The impact of weather data on space-heating energy use is also investigated by running simulations with multiple decades of historical weather data. The simulated results are further benchmarked with the space-heating energy use of comparable office buildings selected from the two well-known U.S. commercial building databases to investigate discrepancies between simulated and actual heating energy use.

It is not the intent of this paper, although the analysis and simulation method can apply, to analyze the total energy use of buildings; therefore, this study’s results and findings should not be directly applied to the whole-building energy use, which includes other end uses. The heating systems discussed in this article are stand-alone systems powered by natural-gas hot-water boilers or electric resistance; they are not part of the district heating systems that are popular in Northern Europe countries and Northern China [21].

This study is part of a bigger effort to study key driving factors of energy performance of buildings under the International Energy Agency (IEA) Energy Conservation in Buildings & Community Systems (ECBCS) Annex 53 Total Energy Use in Buildings: Analysis & Evaluation Methods.

The first section of the paper describes analysis methodology, and the second section provides details of the selected building design and operation parameters, together with definitions of simulation runs. The third section presents and discusses the results. The conclusion section summarizes key findings and potential future research.

Section snippets

Analysis methodology

Building simulations and benchmarking with building energy consumption databases are the two methods we used to study the space-heating energy use in office buildings. Two office buildings with different sizes and design configurations – the high-rise large office and the single-story small office – are studied. To look at the influence of climate, three typical climate zones that require significant space heating are studied. Based on design and operation practice, a few key parameters for the

Building design and operation parameters

Based on office-building design and operation practice, 10 parameters with potentially significant impacts on space-heating energy use were selected for the study. The parameters were sorted into two groups – design and operation – as shown in Table 2, based on whether a parameter is mostly determined during building design or operation. The classification for design and operation parameters for space-heating energy use is listed in Table 2. The selected parameters include envelope insulation,

Simulation runs

Table 5 lists the parametric of the simulation runs for the two office buildings. There are 126 EnergyPlus simulation runs in total, including 22 runs for the large office building and 20 runs for the small office building for each of the three cities. These runs include the basecase, the High and Low Internal Loads cases, the High and Low Infiltration Rate cases, the High and Medium Infiltration Schedule cases, the High and Low Minimum VAV Box Damper Position cases for large office only, the

Impact of design and operation parameters

Fig. 2 shows the percentages of change in space-heating EUIs calculated by comparing the space-heating EUI from each parametric run to that of the basecase for the large office building in the three climates. Fig. 3 shows similar data for the small office building. Both figures are sorted by the percent changes for the Chicago climate.

Looking at results in Fig. 2 for the large office building, it can be seen that: (1) based on the relative impact of the building operation, the most influencing

Conclusions

The simulated space-heating energy use of the small- and large-size office buildings across the three heating climates can vary significantly, depending on details of a few key building design and operation parameters. The most influencing parameters are space-heating temperature setpoint and setback strategies, air infiltration, VAV terminal box damper minimum position settings for the large office, window type, WWR, and internal loads. The relative impacts of these parameters vary with

Acknowledgement

This work was supported by the U.S. Department of Energy under the U.S.–China Clean Energy Research Center on Building Energy Efficiency. It was co-sponsored by the Bureau of Energy, Ministry of Economic Affairs, Taiwan, ROC.

Glossary

ASHRAE
American Society of Heating, Refrigeration, and Air-conditioning Engineers
BESTest
Building Energy Simulation Test
BLAST
Building Loads Analysis and System Thermodynamics
CBECS
Commercial Buildings Energy Consumption Survey
CDD
cooling degree day
CRB
commercial reference building
DX
direct expansion
EIA
Energy Information Administration
EPD
equipment power density
EUI
energy use intensity
HDD
heating degree day
HPB
high-performance building
IEA
International Energy Agency
IEAD
insulation entirely above deck
LPD

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