Data and analytics to inform energy retrofit of high performance buildings
Introduction
In 2010, the U.S. accounted for 19% of the global energy consumption – more than any other country except China [1]. The buildings sector is responsible for about 41% of the U.S. primary energy use and 8% of the world’s CO2 emissions [2], [3]. Globally the buildings sector consumes more than one-third of the world’s primary energy. It has been demonstrated that most existing buildings operate with various levels of deficiencies, and the problems of building energy performance are pervasive and well known [4]. Thus it is important to identify and realize energy saving opportunities in the buildings sector to reduce energy use and carbon emissions.
Currently, more and more attention is drawn to high performance buildings (HPBs), aka green, sustainable, and low energy/carbon buildings, discussed in many studies [5], [6], [7]. HPBs are buildings receiving higher rating scores under various building performance rating and labeling systems. Though such buildings are designed to be more energy efficient than other buildings, more efforts and retrofits are needed to maintain their high performance status [8], [9]. Whether there exists any deeper energy savings for HPBs and how to identify such opportunities become an important concern for not only the government, but also the building owners and facility managers.
In February 2011, President Obama announced the Better Buildings Initiative to make commercial and industrial buildings 20% more energy efficient by 2020 and accelerate private sector investment in energy efficiency [10]. In this aspect, California has been a leader since the inception of the Building Energy Efficiency Standards – Title 24 [11] in 1978. California buildings also received higher Energy Star scores compared with the national stock [12]. Further, more energy codes and savings targets were set in subsequent state policies, such as the Energy Action Plan [13], Assembly Bill 32 – Global Warming Solutions Act [14] which sets California’s target of reducing GHG emission to the 1990 level by 2020, and Assembly Bill 758 – Comprehensive Energy Efficiency Program for Existing Buildings [15]. On the other hand, owners and managers of HPBs can also benefit from improving building operation and maintenance, reducing energy cost, extending equipment life span, and improving indoor environmental quality and employee productivity.
However, it is not easy to find out the specific energy savings potential and related retrofit measures for HPBs which already employ energy efficient technologies and design strategies to reduce energy use – no low hanging fruit in this case. Although building simulations can be used to analyze energy performance and estimate savings potential of building technologies [16], [17], [18], [19], [20], [21], creating and calibrating energy models is a time-consuming effort. The other approach is to measure and analyze performance of buildings. Since energy savings may lie in some specific end-uses or equipment, traditional analysis methods, based on the whole building’s total energy use data from monthly utility bills, are far less adequate. Though some new approaches have been studied and implemented in real projects for a long time, such as energy benchmarking, building energy simulation, building energy monitoring, and fault detection and diagnosis, there is a lack of holistic and uniform approach for energy consultants or building managers to follow [22]. Besides, due to the lack of comprehensive and detailed monitored data, the previous studies and projects mainly focus on some aspects of the building energy performance, or portion of the building systems. For example, only energy use patterns or system operating efficiency is analyzed, only lighting system or heating, ventilation and air conditioning (HVAC) system is considered [23], [24].
There are three main reasons to study the retrofit of HPBs: (1) HPBs do not necessarily consume less energy than normal buildings [25], (2) operational changes and maintenance issues can degrade performance of energy systems [26], [27], and (3) building owners or regulations may require further energy savings. In this study, a new holistic approach using measured building performance data and analytics were proposed, for the purpose of identifying energy use patterns, operation deficiencies and then retrofit measures for major energy end-uses in existing HPBs. This study aims to shed some light on energy retrofit of high performance buildings by exploring answers to the following questions:
- (1)
Are there energy savings in retrofitting HPBs?
- (2)
What types of measured building performance data is needed to enable the analyses?
- (3)
What analytics can be used to identify and evaluate energy retrofit measures?
- (4)
What are the main challenges of using data-driven analytics to inform retrofit of HPBs?
The first section of this paper describes three types of measured building performance data which are needed to enable the analytics. An energy data model based on the ISO Standard 12655 “Presentation of real energy use of buildings” [28] is used to represent the energy use in buildings in a three-level hierarchy. Next, analytics were proposed to analyze energy use in buildings and to identify retrofit measures for high performance buildings. Then, as a case study, these analytics were applied to retrofit of a HPB in California. Finally conclusions and discussion of challenges were provided.
Section snippets
Building performance data
As Peter Drucker, a management thinker, said “you can’t manage what you can’t measure.” To fully understand and manage energy use and performance of buildings, good quality measured data from energy monitoring systems, building automation systems, and building energy management and control systems are crucial. Unfortunately for most buildings, only one electric meter and one natural gas meter are usually installed, and only monthly electric and gas use data from utility companies are available.
Building performance analytics
In order to qualify and quantify how the building energy service systems are performing and how the performance can be improved, ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) defined three progressive levels of energy audits: (1) walk-through analysis/preliminary audit; (2) energy survey and analysis; and (3) detailed analysis of capital intensive modifications [29].
To support some of the efforts defined in the ASHRAE three levels of energy audits and go
A case study
To better understand how the analytics can be applied to retrofit of HPBs, the California State Teachers’ Retirement System (CalSTRS) Headquarters building, shown in Fig. 2, is taken as a case study.
Conclusions
A new holistic approach, powered by measured building performance data and analytics, to inform energy retrofit of high performance buildings was presented in this study. The three analytics, energy profiling, benchmarking, and diagnostics, are based on long-term performance data monitored at short time intervals from the energy monitoring system as well as the building automation system usually installed in high performance buildings. The level of effort to conduct the three levels of analysis
Acknowledgement
This work was supported by the United States Department of Energy under the United States – China Clean Energy Research Center for Building Energy Efficiency with Contract No. DE-AC02-05CH11231.
Glossary
- AHU
- air handling unit
- ASHRAE
- American society of heating, refrigeration, and air-conditioning engineers
- BAS
- building automation system
- CalSTRS
- California state teachers’ retirement system
- CBECS
- commercial buildings energy consumption survey
- CEUS
- California end use survey
- CHWP
- chilled water pump
- COP
- coefficient of performance
- CRAC
- computer room air conditioner
- CWP
- condenser water pump
- DHW
- domestic hot water
- DX
- direct expansion
- EIA
- energy information administration
- EMS
- energy management system
- EUI
- energy use intensity
- HPB
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