1、 Edna Lorenz is a Senior Associate at Environmental Systems Design, Inc. Mehdi Jalayerian is an Executive Vice President at Environmental Systems Design, Inc. Benchmarking Energy Performance of Tall Buildings Edna Lorenz, PE Mehdi Jalayerian, PE Member ASHRAE Member ASHRAE ABSTRACT Early results fro
2、m Chicagos Energy Benchmarking and Transparency Ordinance indicate that commercial buildings over 250,000 square feet (23,225 square meters) perform statistically better than the average commercial buildings as reported by the Commercial Buildings Energy Consumption Survey (CBECS). The median ENERGY
3、 STAR score of Chicagos large office buildings was 78, which was in-line with the results found in New York City, Philadelphia and Washington DC for similarly sized buildings. These results lead us to hypothesize that taller buildings are better energy performers than low-rise buildings. However, be
4、cause the raw data collected by the City of Chicago in 2014 as part of the first year of compliance was not made publically available, benchmarking data from private Portfolio Manager accounts was collected in order to analyze the relationship between building height and energy consumption. Signific
5、ance testing of benchmarking data revealed a significant relationship between building height and ENERGY STAR score with a measured p-value of less than 0.05. However, analysis of the benchmarking data revealed no linear correlation between building height and ENERGY STAR score or building height an
6、d Source Energy Use Intensity (EUI). The second portion of the paper compares the benchmarking data set against a pool of tall building energy model simulations. The model analysis found a significant negative correlation between Building Height and Source EUI in office buildings located in Illinois
7、. It was also found that there is a significant relationship between Occupancy and building energy performance which leads to the conclusion that other factors not considered as part of this analysis such as operating schedules, equipment efficiency, plug loads, envelope constructions, and building
8、operator proficiency are likely to have a major effect on the energy consumption of operational buildings. Nevertheless, increased building height of an office building can be indicative of higher ENERGY STAR score given that this rating system normalizes for various factors including square footage
9、, occupancy, weather, and equipment usage. INTRODUCTION This paper will explore the relationship between tall office buildings and energy use by examining the analysis released by the City of Chicago following the first year of implementing their Energy Benchmarking and Transparency Ordinance as wel
10、l as energy benchmarking data collected from private ENERGY STAR Portfolio Manager accounts. This data will be compared against modeled tall building energy performance executed using energy model simulation software. The analysis of this information will examine correlations and relationships betwe
11、en building height, size, occupancy, and energy consumption. For the purposes of analysis for this paper, tall buildings are defined as buildings over 10 floors in height, with floor plate areas of at least 25,000 square feet (sf) (2,322.5 square meters (sm). OVERVIEW OF DATA COLLECTED FOR ANALYSIS
12、City of Chicago Energy Benchmarking and Transparency Ordinance The City of Chicago (the City) passed the Energy Benchmarking and Transparency Ordinance in September of 2013. The intent of the ordinance is to encourage energy efficiency in Chicagos building stock by requiring municipal, commercial an
13、d residential properties over 50,000 sf (4,645 sm) to report their energy consumption to the City for public disclosure. The ordinance has a phased compliance timeline: Commercial and municipal buildings over 250,000 sf (23,225 sm) were required to report their energy consumption to the City by June
14、 1st, 2014; commercial and municipal buildings over 50,000 sf and residential buildings over 250,000 sf were required to report by August 1st, 2015; and finally, residential buildings over 50,000 sf were required to report by June 1st, 2015. After their first year of compliance, all buildings must r
15、eport their energy consumption to the City by June 1st on an annual basis. The ordinance also requires that properties have their data verified by a qualified professional, such as a Professional Engineer, every three years, starting their first year of compliance. This requirement helps to ensure t
16、hat the City will receive high quality data for disclosure and analysis (City of Chicago, 2015). As of the writing of this paper, one reporting cycle had been completed, and the City has issued a summary report titled “City of Chicago 2014 Building Energy Benchmarking Report”. The second reporting c
17、ycle for commercial and municipal buildings over 250,000 sf as well as first time reporting cycle for commercial and municipal buildings over 50,000 sf and residential buildings over 250,000 sf is currently ongoing. Data was collected by the City via a custom report generated by ENERGY STAR Portfoli
18、o Manager. ENERGY STAR Portfolio Manager is a free online tool developed by the United States Environmental Protection Agency (EPA) and is the preferred reporting method for cities with energy benchmarking ordinances. The ENERGY STAR Portfolio Manager tool allows users to track and benchmark buildin
19、g energy consumption (EPA, 2015). The tool uses the Commercial Buildings Energy Consumption Survey (CBECS) data base as well as space usage types, occupancy, weather data and other variables to generate 0-100 ENERGY STAR scores for eligible buildings (EPA, 2015). An ENERGY STAR score of 50 indicates
20、 that a building performs in the 50th percentile when compared to similar buildings within the CBECS database. Buildings with an ENERGY STAR score of 75 or higher are eligible to receive recognition by applying for ENERGY STAR certification. The results of the first year of reporting to the City ind
21、icate that commercial and municipal buildings in Chicago over 250,000 sf perform statistically better than the average commercial buildings as reported by the CBECS. Of the 153 large buildings that reported their data to the City in June 2014, only 12 buildings reported an ENERGY STAR score of 50 or
22、 less, and 105 buildings reported a score of 75 or higher. The median ENERGY STAR score of Chicagos large buildings was 78, which was in-line with the results found in New York City, Philadelphia and Washington DC for similarly sized buildings (City of Chicago, 2015). Given the estimated average flo
23、or plate for a commercial office building located in the City of Chicago is 25,000 sf, these results lead us to hypothesize that high-rise buildings that are more than 10 floors in height are more efficient than low-rise buildings less than 10 floors in height. However, the City has chosen not to di
24、sclose a buildings first year compliance data in order to provide buildings with an opportunity to improve their energy consumption prior to public disclosure; therefore, the data analyzed for the “City of Chicago 2014 Building Energy Benchmarking Report” is not publically available for further anal
25、ysis by the private sector. Analyzed Building Energy Benchmarking Data Because the City has chosen not to disclose the first year compliance data, this data is not available for analysis, therefore in order to complete the analysis for this paper energy benchmarking data had to be collected from pri
26、vate ENERGY STAR Portfolio Manager accounts. Data collected included the following: Property Floor Area (sf) District Chilled Water Consumption (kBtu) Year Built ENERGY STAR score City, State Weather Normalized Site Energy Usage Intensity (EUI) Electricity Consumption (kWh) Weather Normalized Source
27、 EUI Natural Gas Consumption(Therms) Primary Property Type EPA Calculated District Steam Consumption (kBtu) Occupancy (Percent of building occupied) Building height is not reported in ENERGY STAR Portfolio manager; therefore height of the building, measured in floors above grade, was obtained from p
28、ublically available sources. In addition to building height, Volume to Surface Area Ratio (V:SA) was included in the analysis to study the impact of envelope loads on building energy performance as building height increases. Benchmarking data was collected for 185 properties located in the state of
29、Illinois from private Portfolio Manager accounts. Of these properties, 166 are classified as Office. The sample sizes of all property types other than Office are not significant relative to the number of Office data points collected and were therefore excluded from further analysis. Energy Model Gen
30、erated Data Energy models were created for a typical office building, in Chicago, Illinois, of increasing height intervals, as measured in number of floors above grade. The models were created in accordance with ASHRAE 90.1-2010 Appendix G. All models were built using rectangular geometry and a squa
31、re 25,000 sf floor plates for the entire height of the building. Besides building height and number of chillers, all input variables, such as lighting power density, occupant density, envelope thermal performance, and equipment efficiency were kept constant between each model. Chillers were modeled
32、as equally sized. Additional chillers were added to the models as cooling load increased with building height square footage so that no chiller was larger than 800 tons (2,800 kW) per the guidance provided by ASHRAE 90.1-2010 Appendix G. The effect of changing atmospheric conditions as building heig
33、ht increases was not modeled due to limitations in the energy modeling software used for this analysis. A total of 13 energy models of buildings ranging in height from 5 to 100 floors were created as a control group for comparison with the collected energy benchmarking data. ANALYSIS OF COLLECTED BE
34、NCHMARKING DATA Comparison of Data Sets City of Chicago, 2013 Data, Office Building Population Over 250,000 sf vs. Illinois, 2014 Data, Office Building Sample, All Sizes The data collected by the City of Chicago in June 2014 represents the entire population of commercial and municipal buildings over
35、 the 250,000 sf within the city limits of Chicago. Therefore, in order to determine if the collected sample of data from Illinois office buildings was a reasonable representation of the information reported to the City, the City of Chicago 2014 Building Energy Benchmarking Report was compared agains
36、t the sample of building data collected for purposes of this study. For both data sets, the office building sub-set was isolated for analysis. Table 1: Comparison of Data Sets City of Chicago, Office Buildings Over 250,000 sf (23,225 sm), 2013 Data vs. Illinois, Office Building Sample, All Sizes, 20
37、14 Data Office Building Population Over 250,000 sf (23,225 sm), Chicago Ordinance, 2013 Data Office Building Sample, All Sizes, Illinois, 2014 Data Number of office buildings: 153 buildings 166 buildings Median ENERGY STAR score: 78 75 Average Square Footage Not reported, greater than 250,000 sf (23
38、,225 sm) Average: 594,853 sf (55,264 sm) Range: 35,000 3.4M sf (3,252 315,870 sm) Height Not reported, approximately 10 stories and higher Average: 21 stories Range: 1 to 83 stories Table 1 compares the basic statistics of each data set. As can be seen, the sample size of the analyzed Illinois data
39、set is within 10% of the number of office buildings reporting to the City in 2014. In addition, the median ENERGY STAR score of the analyzed data set is within 3 points. The “City of Chicago 2014 Building Energy Benchmarking” report did not disclose the average gross floor area or height of reported
40、 office buildings, however based on ordinance compliance requirements for 2014 we know the average gross floor area is likely to be above 250,000 sf and the height to be above the 10 stories, if we assume an average building floor plate size of 25,000 sf. The collected data for the state of Illinois
41、 has an average gross floor area of 594,853 sf (55,264 sm) and average height of 21 stories. In addition to the statistics in Table 1, a single factor ANOVA analysis was completed in order to assess significant differences between the Median Site and Median Source EUI reported by decade of construct
42、ion (Figure 1). The calculated F-critical value was found to be 4.3 and the calculated F-value was found to be 0.06. Because F-critical is greater than F, this indicates that there is no significant difference between the data sets and therefore the data sample collected from private Portfolio Manag
43、er accounts is assumed to be a reasonable representation of the City of Chicago population of office buildings over 250,000 sf. Figure 1 Site and Source Energy Use Intensity of Office Buildings by Decade of Construction Building Height versus ENERGY STAR score and Weather Normalized Source EUI Analy
44、sis Single variable regression analyses comparing ENERGY STAR score and Weather Normalized Source EUI against Building Height, measured in floors, was completed for the collected Illinois benchmarking data. Weather Normalized Source EUI is the measure of energy consumed by the building at the source
45、 of energy generation with the effects of local weather adjusted to match the typical weather for an area or region (EPA, Portfolio Manager, 2014). ENERGY STAR score was also chosen for analysis because the ENERGY STAR score is an industry approved and verified measure of energy performance that nor
46、malizes for operational characteristics of a building, such as floor area, weather, occupancy, number of computers, percent heated and percent cooled. As can be seen in Table 2 and 3, for both cases there is no linear correlation between ENERGY STAR score and Building Height and Source EUI and Build
47、ing Height given the R2 values were found to be much less than 1. The p-value of the dependent variables was also calculated to assess the statistical significance of the relationship between ENERGY STAR score and Building Height and Source EUI and Building Height. The relationship between the indep
48、endent and dependent variable is considered to be significant if the calculated p-value is less than 0.05. As can be seen in Table 2, the calculated p-value for Building Height versus ENERGY STAR score was 0157314471628785050100150200250EUI (kWh/sm)EUI (kBTU/sf)Decade BuiltMedian Source EUI - Illino
49、is SampleMedian Site EUI - Illinois SampleMedian Source EUI - Chicago Ordinance, 2013 Data, Office Buildings over 250,000 sf (23,225 sm)Median Site EUI - Chicago Ordinance, 2013 Data, Office Buildings over 250,000 sf (23,225 sm)found to be 0.019. This result indicates that even though a linear regression model is not an appropriate description of this data, there is a statistically significant relationship between Building Height and ENERGY STAR score. Further review of the regression analysis also revealed that the calculated coefficient (0.279) is po
