Improving Energy Utilization

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Aruna Balakrishnan

Jared CauserJohn Jones

Mary Krause

Laura Thomson

Aaron Wilson

ENGINEERING SCIENCES 96: DESIGN SEMINAR SPRING 2002

IMPROVING ENERGY UTILIZATION:

John An

Andrew CarlsonRohan Gulrajani

Roy Kaiser

Timothy Mariano

A Study of the Maxwell Dworkin Laboratory

Division of Engineering and Applied SciencesHarvard University, Cambridge, Massachusetts


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ACKNOWLEDGEMENT

The ES 96 Class would like to express our gratitude to the many people who so generously assisted

us in our investigation. In particular, we would like to thank:

Prof. Michelle Addington Peter Arvidson Prof. Michael Brandstein Prof. Roger Brockett Susyrati Bunanta Frank DeCosta Jeff Deyette Armond Diaz Scott Gaines Prof. Barbara Grosz Jean Humber Ed Jackson Jonathan Kanda Greg Kousidis Xuan Liang Prof. David Parkes Jay Phillips David Richards Stephen Robichaud Dr. Joy Sircar Joe Ustinowich Prof. Gu-Yeon Wei Prof. Woodward Yang Rich Zitola

and, of course, our dedicated Coaching Staff,

Prof. Frederick H. Abernathy Prof. Al Pandiscio Aaron Dollar

for sharing their knowledge, dedicating their time, and being so patient throughout the semester.


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TABLE OF CONTENTS

Foreward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

1.0 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2.0 Energy & Environmental Indicators . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1 Energy, Economy, and Environment . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1.1 Environmental Issues and Opportunities . . . . . . . . . . . . . . . . . . . . . 7

2.1.2 Indicators of Energy and Environmental Efficiency . . . . . . . . . . . . . . . 8

2.2 Acres of Forest as an Environmental Indicator . . . . . . . . . . . . . . . . . . . . 9

2.2.1 Electricity to Acres of Forest . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2.2 Chilled Water to Acres of Forest . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2.3 Steam to Acres of Forest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

3.0 Environmental Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.1 Environmental Impacts of Maxwell Dworkin . . . . . . . . . . . . . . . . . . . 15

3.2 Energy Use in Maxwell Dworkin and Harvard Buildings . . . . . . . . . . . . . 17

3.3 Energy Consumption in Maxwell Dworkin . . . . . . . . . . . . . . . . . . . . . 18

4.0 Building Energy Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.1 Building Scale Energy Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

5.0 Intelligent Control of Building Systems . . . . . . . . . . . . . . . . . . . . . . 29

5.1 APOGEE: The Intelligent Control System . . . . . . . . . . . . . . . . . . . . . . 31

5.1.1 System Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315.1.2 Method of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

5.1.3 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.1.4 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.2 Air Ventilation and Circulation Systems Controlled by APOGEE . . . . . . . . . . 34

5.2.1 Air Handling Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

5.2.2 Fan Coil Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

6.0 Office Energy Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

6.1 Adaptable Temperature Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

6.1.1 The Status Quo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

6.2 Method of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

6.2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426.2.2 Heat Capacity of a Room . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

6.2.3 Temperature Invariant Heat Sources . . . . . . . . . . . . . . . . . . . . . . 45

6.2.4 Heat Exchanges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

6.2.5 Active Temperature Regulation . . . . . . . . . . . . . . . . . . . . . . . . . 47

6.2.6 Putting it All Together . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

6.2.7 Predicting the Status Quo . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

6.3 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

6.3.1 Application of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50


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6.3.2 Optimizing the Office Controls . . . . . . . . . . . . . . . . . . . . . . . . . 53

6.4 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

7.0 Cooling in Maxwell Dworkin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

7.1.1 Chilled Water System in Maxwell Dworkin . . . . . . . . . . . . . . . . . . . 61

7.2 Method of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 637.3 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

7.3.1 Daily Use of Chilled Water . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

7.3.2 Weekly Use of Chilled Water . . . . . . . . . . . . . . . . . . . . . . . . . . 66

7.3.3 Monthly Use of Chilled Water . . . . . . . . . . . . . . . . . . . . . . . . . . 67

7.3.4 24-Hour Cooling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

7.4 Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

7.4.1 More Efficient Operation of the APOGEE Control System . . . . . . . . . . . . 70

7.4.2 Elimination of Weekend Cooling . . . . . . . . . . . . . . . . . . . . . . . . 71

7.4.3 Summer Night-Time Air Purges . . . . . . . . . . . . . . . . . . . . . . . . . 75

7.4.4 Ethylene Glycol Heat Exchangers . . . . . . . . . . . . . . . . . . . . . . . . 79

7.4.5 Steam to Hot Water Heat Exchanger . . . . . . . . . . . . . . . . . . . . . . 80

7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

8.0 Ventilation and Indoor Air Quality . . . . . . . . . . . . . . . . . . . . . . . . . 83

8.1 Introduction to Indoor Air Quality . . . . . . . . . . . . . . . . . . . . . . . . . 85

8.2 Determining Indoor Air Quality by Carbon Dioxide Levels . . . . . . . . . . . . 86

8.2.1 CO2 in Human Respiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

8.2.2 Building Ventilation Requirements . . . . . . . . . . . . . . . . . . . . . . . 86

8.2.3 Predictive CO2 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

8.2.4 Conclusion and Recommendations . . . . . . . . . . . . . . . . . . . . . . . 90

8.3 Indoor Air Quality via Massachusetts Building Code . . . . . . . . . . . . . . . 90

9.0 Air Handling Units in Maxwell Dworkin . . . . . . . . . . . . . . . . . . . . . 93

9.1 Air Handling Units in Maxwell Dworkin . . . . . . . . . . . . . . . . . . . . . . 959.2 Method of Determining Ventilation Rates . . . . . . . . . . . . . . . . . . . . . 95

9.3 Air Handling Unit 2 Supply and Return Air System . . . . . . . . . . . . . . . 97

9.3.1 Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

9.3.2 Sequence of Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

9.3.3 Operation Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

9.4 Method of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

9.4.1 Determination of Ventilation Rate Requirements . . . . . . . . . . . . . . . . 98

9.4.2 Comparison with the Actual Ventilation Provided . . . . . . . . . . . . . . . . 99

9.4.3 Measurement of CO2 Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

9.5 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

9.6 Exhaust Fans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

9.6.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1009.6.2 Operation of the Exhaust Fan . . . . . . . . . . . . . . . . . . . . . . . . . 101

9.7 Method of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

9.7.1 Exhaust Provided vs. Exhaust Requirements . . . . . . . . . . . . . . . . . 101

9.7.2 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

9.8 Air Handling Units 4 and 5 Supply Air Only Systems . . . . . . . . . . . . . 105

9.8.1 Sequence of Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

9.8.2 Originial Operation Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

9.9 Method of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106


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11.0 Generalization to Other Harvard Buildings . . . . . . . . . . . . . . . . . . . 145

11.1 Applicability to William James Hall and the Science Center . . . . . . . . . . . 147

11.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

11.1.2 Ventilation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148

11.1.3 Lighting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148

11.1.4 Additional Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

11.2 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

12.0 Summary of Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151

12.1 Overall Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153

Appendices

Appendix 1 Temperature Data for Boston, MA

Appendix 2 Energy Balance Calculations for Maxwell Dworkin

Appendix 3 Conversion Calculations from Energy Source to Acres of Forest

Appendix 4 Utility Information for Maxwell Dworkin

Appendix 5 Calculations and Measurements for AHUs 4 and 5

Appendix 6 Calculations and Measurements for AHUs 1 and 3

Appendix 7 Schematic Drawings of the Operation of AHUs 1, 2, 3, 4, & 5Appendix 8 BOCA International Mechanical Code Ventilation Requirements

Appendix 9 Decora Wall Switch Occupancy Sensor

Appendix 10 Lighting Tables from the Illuminating Engineering Society of North America

Appendix 11 Extech Light-Meter Profile

Appendix 12 Lighting Measurements for a South-Facing Office Space on a Sunny Day

Appendix 13 Lighting Measurements and Calculations

Appendix 14 Telaire 7001 Carbon Dioxide and Temperature Monitor


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1.0 INTRODUCTION


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1.0 IntroductionThis spring, the Engineering Sciences 96 design seminar of 11 students was presented with the task of

investigating in detail the mechanical systems of one of Harvards newer buildings. After gaining a

full understanding of the advanced systems involved, we used our research of these systems to offer

recommendation on how they could be more efficiently operated with greater savings to the

university and less impact on the environment.

Efficient use of Harvards buildings is an important concern today and one that will become

increasingly relevant in years to come as Harvards buildings continue to age. The buildings on

campus range anywhere from newly built to more than 250 years old, which means that the

mechanical systems that run them are as diverse as Harvards student body itself. By measuring a

buildings efficiency based on the cost to run the building per sq. foot, we created an efficiency

comparison of several Harvard buildings. Though it may seem counterintuitive, many of Harvards

older buildings may actually be more efficient than those built today. Newer buildings offer many

modern conveniences that the buildings of the past did not and those comforts equal more money.

When undertaking our project, we decided it would be best to focus on one building. After choosing

a building, we could determine if our insights of how to operate that building more energy efficiently

could be generalized to buildings such as the Science Center and William James Hall. We therefore

chose to first study Maxwell Dworkin, as it provided the ideal setting for gathering our initial

research. Maxwell Dworkin is one of Harvards newest buildings, completed in 1999, and a friendly

staff and faculty were willing to assist in our experimentation, and this made it an attractive choice. It

hasa sophisticated and accessible mechanical system that is equipped with several hundred control

points which can be accessed and managed by a central control program. The class then toured the

mechanical rooms of Maxwell Dworkin to get a first-hand look at its mechanical, electrical, and

heating ventilation air-conditioning (HVAC) systems. While touring these systems, we questioned

how FAS buildings are provided with heating and cooling.


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The answer? Buildings are heated via an underground utility tunnel to a steam and electrical

generating plant at Western Avenue and Memorial Drive on the Charles River. The underground

tunnel carries steam under pressure, electrical lines, and communication lines directly to buildings.

Chilled water for cooling, however, is generated in the basement of the Science Center and is

distributed directly to buildings through buried insulated pipes.

The electricity, steam and chilled water then meet the utility room. Steam energy is converted to hot

water and pumped throughout Maxwell Dworkin to provide heating. Steam flow is metered by the

flow rate of the steam condensate which is returned to the power plant. Chilled water is also pumped

throughout the building and then returned to the plant slightly warmer than it arrived at Maxwell

Dworkin. Billing for chilled water is metered by the flow rate of the water times the temperature rise

in the water returned to the plant. Electrical power enters the building through a separate vault and is

there metered for billing purposes.

Armed with this knowledge, we were able to identify three major sources of energy consumption in

Maxwell Dworkinlighting, air handling and fan coil units, and chilled and hot water usage. We then

split into smaller groups that would address each of these areas. Each group looked at energy

consumption records, and performed individual data records such as measuring and recording CO2

levels over time, measuring light levels, and looking at the time history of energy use in rooms and

lecture halls. From that data each group developed mathematical models to predict room conditions

under different operating settings. This information was then used to determine how each of the

systems could more efficiently and environmentally be managed. These insights of how to operate

the building more energy efficiently were used to determine if improvements might be made to the

Science Center and William James Hall, though this is by no means an exhaustive list of the buildings

that could be aided by such improvements.

It is imperative that Harvard do its part in helping the environment. We hope to help people

understand how greenhouse emissions may be decreased for the operation of every Harvard building

while maintaining the building as a pleasant place to teach, go to classes, and do research. This paper

presents our findings for the potential environmental and monetary savings in lighting, air handling

and fan coil units, and chilled water usage along with the background knowledge necessary to

understanding the environmental impact.


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2.0 ENERGY & ENVIRONMENTAL INDICATORS


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2.1 Energy, Economy, and Environment

Measures of economic and environmental efficiency often take the same form: the consumption of

fewer resources to achieve equal provision of products and services makes good business and

ecological sense. This is particularly true with respect to energy saving endeavors: conservation often

pays a commendable double dividend. Unfortunately, where the economic dividend is easily

understood and measured in dollars, the environmental benefits are sometimes harder to calibrate.

This section discusses the motivation behind calculating an environmental dividend and provides

detailed information on the calculations that undergird the environmental indicators of the analysis.

2.1.1 Environmental Issues and Opportunities

The April 2001 edition of the Environmental Building Networks Newsletter stated that commercial

buildings in the United States account for 36% of all energy consumption in the United States an

astronomical 3.6 billion MWh per annum. Of this amount, these buildings which include private

and public offices, as well as retail space account for 62% of all electricity use and 30% of all

greenhouse gas (GHG) emissions. As such, commercial buildings represent a tremendous

opportunity to improve the environmental efficiency of the United States. Concentrated efforts in the

design and retrofit of building with advanced technology are important steps forward in capitalizing

upon this opportunity. Yet in order to move forward, an easily understandable means of comparing

the benefits to costs is necessary.


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2.1.2 Indicators of Energy and Environmental Efficiency

The lack of easily comparable and standardized indicators often renders discussions of environmental

efficiency contentious and frustrating. The scale of the factors involved billions of dollars, 3.6

billion MWhs are often confounding. In order to avoid unnecessary confusion and facilitate

comprehension of the suggestions made in this report, we have decided to use four indicators

throughout this analysis:

Dollars

Operational Cost per Square Foot

Units of Energy or Utility

Acres of US Commercial Forest

The first three indicators, in our estimation, are relatively self-explanatory. For each type of

operation or utility analyzed, estimated savings will be presented in economic terms. For example,

the changes proposed to the lighting scheme have the potential to save $13,000. Moreover, the

decreases to the operational cost per square foot will be presented; using the lighting example,

changing the lighting schema in Maxwell Dworkin could reduce the operating cost per square foot

from $2.73 to $2.54. Furthermore, savings will be presented in terms of the units of the energy or

utility consumed.

Our fourth indicator, in contrast, requires further explanation. Recent concern over global climate

change has prompted heated international discussion over the role of greenhouse gases (GHG), which

change the heat-absorbing properties of our atmosphere. Governments, institutions and companies

are under increasing pressure to calibrate and reduce the amount of carbon dioxide, methane, and

sulfur hexafluoride. One of the recent initiatives in this debate has been to consider forests as carbon

dioxide sinks that sequester GHGs, and thereby compensate for the GHG emitted as a result of use

of fossil fuel energy. As such, we decided to use the reduction in the number of acres of US

commercial forest required to absorb Maxwell-Dworkin's carbon dioxide emissions as our fourth

indicator.


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2.2 Acres of Forest as an Environmental Indicator

Embedded in these discussions, however, are assumptions as to the efficiency of energy production.

The variety of methods used in the production of energy requires that any serious discussion of GHG

reductions measures make these assumptions explicit to avoid unnecessary confusion. In recognition

of this necessity, we analyzed the carbon dioxide production involved in the three major utilities our

study focused on. After identifying Electricity, Chilled Water and Steam as the principal targets

for reduction, data accumulation on the efficiency of energy production from each of these three

utilities was gathered in order to calculate the greenhouse gas emissions. Furthermore, research from

the Naval Research Laboratory1 revealed that 1.19 tons of carbon dioxide are annually absorbed by 1

acre of US Commercial Forest per annum.

2.2.1 Electricity to Acres of ForestElectricity at Harvard is provided by the NSTAR Corporation, Massachusetts largest investor owned

electric and gas utility. Recent corporate documentation demonstrated that the electricity that

Harvard consumes is generated in a variety of different ways (Figure 2.1).

Figure 2.1 Fuel mix of electricity purchased by Harvard University

1 http://itest.slu.edu/articles/90s/hannan.html


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The large proportion of nuclear energy in Harvards energy supply complicates the calibration of

GHG emissions from electricity use, however. As a result, we decided to use the EMISS program

provided by the National Institute of Standards and Technology, which gives the conversion factor to

carbon dioxide by the different region in the United States, taking into account the different fuel mix.

EMISS stated that 234.6 kg of carbon dioxide are emitted per MMBtu of electricity produced. The

calculations in Appendix 3 reveal that this means 1350 kWh of electricity would need to be reduced

in order to reduce the area of forest required to absorb the emissions by 1 acre of US Commercial

Forest.

2.2.2 Chilled Water to Acres of ForestThe chilled water used to cool Harvards building is generated at the Science Center from 5 distinct

chillers of differing capacities. Maxwell Dworkin is billed for its chilled water use in ton-days, a

unit of energy equivalent to what would need to be removed from 1 ton of water at 32 degrees

Fahrenheit to generate 1 ton of ice at the same temperature. In more quantitative terms, a ton-day

represents the same amount of energy that a 12,000 BTU/hr engine would output if it ran for twenty-

four hours. Our research revealed an Energy Efficiency Ratio (EER) of 12 for the plant: that is, it

takes 1000 watts to produce a ton (12,000 BTU) of cooling. As such, our calculations in Appendix 3

reveal that a reduction of 56 ton-days of cooling would reduce the area of forest required to absorb

the GHG emissions by 1 acre of US Commercial forest.

2.2.3 Steam to Acres of ForestFinally, steam at Harvard is co-generated at the Commonwealth Electric Company on Memorial

Drive from a highly viscous fuel known as Bunker Oil. This steam circulates throughout the

campus from September to April, providing the energy required for heating water, which in turn heats

the buildings themselves. Using information from the Department of Energy with respect to the

energy content of Bunker Oil, a standard chemical equation for the combustion of hydrocarbons2,

CxHy + vO 2(O2 + 3.76N2) vCO 2CO2 + vH2OH2O+ vN2N2 (Eq. 2.1)

2 Equation of Combustion from Sonntag et al.,Funadmentals of Thermodynamics, p 524, Wiley:New

York:1998


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and an assumed value of the plants efficiency of 80%3, we concluded that a reduction of 12.5

MMBTU of steam consumption is required to reduce the GHG absorption requirement by 1 acre.

3 Provided by Professor Frederick H. Abernathy, Abbott and James Lawrence Professor of Engineering and

Gordon McKay Professor of Mechanical Engineering, Division of Engineering and Applied Sciences,Harvard

University


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3.0 ENIVRONMENTAL IMPACTS


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3.1 Environmental Impacts of Maxwell Dworkin

Realizing the potential impact of buildings on the environment, our class explored these implications

to Harvard University. On the Cambridge campus alone, Harvard possesses over two hundred

buildings. Additionally, buildings are constantly being renovated and new structures continue to be

built. By understanding the impact on the environment of current buildings, future construction

projects can incorporate this knowledge into their plans.

Specifically, our class chose to examine Maxwell Dworkin. Our choice was not made without

reason; Maxwell Dworkin is one of the most modern building on campus. Its complex operating

systems were designed to be energy efficient. Our hope was that having investigated the opportunity

for energy savings in a modern building on campus, we could generalize our findings to other

buildings. By examining the records of Maxwell Dworkins utility use, we calculated a total utility

budget and its equivalence in acres of U.S. Commercial Forest that would have been required to

absorb the carbon dioxide emissions from typical utility plants generating the utilities. We chose the

utility use for the fiscal year 2001 because it was the most complete data set obtained from Harvard

University Operations Services. A projected budget was computed using the utility costs for the

Fiscal Year 2003 alongside the utility use for the year 2001. These costs include distribution costs for

the specific utility (Table 3.1). Refer to Appendix 4 for detailed data. The calculated budget includes

the following utilities: chilled water, steam, electricity and water. With these four utilities, the

estimated utility cost for Maxwell Dworkin is $305,816.


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TABLE 3.1 Projected Budget of Maxwell Dworkin

Fiscal Year 2001 Utility Usage Cost of Utility in Dollars for

Fiscal Year 2003**

Electrical (kWh) 1153728 x 0.1095 dollars/kWh = 126333.2

Steam (MMBtus) 3753 x 17.97 dollars/MMbtu = 67441.41

Chilled Water (Ton-Days) 12540 x 8.7 dollars/Ton-Day = 109098

Water (Ccf) 290 x 10.15 dollars/Ccf = 2943.5

$ 305816.1 Total Cost

*Utility Usage obtained from Harvard University Operations Services.**Utility Cost for the Fiscal Year 20034

In order to obtain an equivalent measure in acres, the emission rate for each utility was tabulated

separately using the calculated conversions explained above in Section 2.2. See Table 3.2 for

calculations. The total acreage required to compensate for the Maxwell Dworkins utilities for the

fiscal year 2001 is 1379 acres.

TABLE 3.2 Environmental Impact of Maxwell Dworkin

Fiscal Year 2001 Utility Usage* Conversion to acres Acres

Electrical (kWh) 1153728 / 1350 kWh/acres = 854.6

Steam (MMBtus) 3753 / 12.5 MMBtus/acre = 300.2

Chilled Water (Ton-Days) 12540 / 56 Ton-Days/acre = 223.9

1378.7 Total acres

*Utility Usage obtained from Harvard University Operations Services.

To place this number into perspective, our class found it useful to compare this acreage to a more

familiar piece of land, specifically Harvard Yard. The entire area of Harvard Yard enclosed by the

black iron gates, as shown in Image 3.1, equals 22 acres. In comparison to the total acres needed to

compensate for Maxwell Dworkins carbon dioxide emissions, it would require approximately 63Harvard Yards.

These calculations motivated our class to examine more energy efficient ways in which to operate

buildings at Harvard University. If just one building produced this enormous amount of carbon

4 FAS Planning numbers for Fiscal Year 2003. Courtesy of the Office of Physical Resources.


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dioxide emissions, imagining the impact of all Harvard University buildings is astounding. Clearly, it

is imperative for Harvard University to consider its impact on the environment.

IMAGE 3.1 Map of Harvard Yard5

3.2 Energy Use in Maxwell Dworkin and Harvard Buildings

Having decided to focus our study on Maxwell Dworkin, it was important to compare the relative

energy efficiencies of various buildings. By using current utility planning costs for the fiscal year

2003, we compared the utility cost per square foot of various buildings. The utility usage numbers

are from the fiscal year 2001. Keeping in mind that Maxwell Dworkin was built to be energy

efficient, its success is limited (Figure 3.1). See Appendix 4 for detailed utility data.

5 Image obtained from Harvard University Map http://map.harvard.edu/level2/2Yard.shtml


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Maxwell

Dworkin

Pierce Hall William

James

Science

Center

Gordon

McKay

Utility Cost per Square Foot

$2.73$2.39

$5.41

$4.99

$3.74

FIGURE 3.1 Utility cost per square foot of 5 buildings on the Harvard Campus

In comparison to William James Hall, the Science Center and Gordon McKay, Maxwell Dworkin

appears to be more energy efficient. It is important to note that these buildings have different

functionalities. William James Hall, the Science Center and Gordon McKay all possess laboratories

that heighten utility expenses. However, Pierce Hall and Maxwell Dworkin share similar

functionality. Both buildings contain mostly offices and lecture halls. When compared to Pierce

Hall, Maxwell Dworkin is more expensive to run. Pierce Hall is an older, basically un-insulated

building while Maxwell Dworkin is a modern, well-insulated building. This puzzling result forced

our class to further examine the exact sources of energy consumption within Maxwell Dworkin.

3.3 Energy Consumption in Maxwell Dworkin

By examining the monthly trends of utility costs, our class gained an understanding of how the

building consumes energy throughout the year. The three utilities trended were electricity, steam and

chilled water. The data used was from January 2000 to April 2002. See Figures 3.2, 3.3, and 3.46.

6 Utility Usage obtained from Harvard University Operations Services


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Monthly Trends of Electricity

0

20,000

40,000

60,000

80,000

100,000

120,000

January

March M

ay July

Septe

mber

Novemb

er

January

March M

ay July

Septe

mber

Novemb

er

January

March

Years 2000-2002

KWh

FIGURE 3.2 Monthly Trends of Electricity

The electric use throughout the years remains relatively constant, which corresponds to a constant use

of items such as lights, computers, elevators, etc. This result seems reasonable since professors and

graduate students work all year round.

The steam trends also appear logical. During the winter months when the most heating is required,

the most steam is being used. Additionally, as the steam is shut during the summer months, and there

is no steam usage during the appropriate period.


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Monthy Trends of Steam

0

100

200

300

400

500

600

700

800

900

1000

January

March

May Ju

ly

Septe

mber

Novemb

er

January

March

May Ju

ly

Septe

mber

Novemb

er

January

March

Years 2000-2002

MMBTUs

FIGURE 3.3 Monthly Trends of Steam

The third trended utility was chilled water. As expected, chilled water usage peaks in the summer,when most cooling is needed. However, chilled water costs do not vanish during the winter months.

In fact, during the winter months they are nearly one-third as much as during the summer months.

Maxwell Dworkin needs cooling all year round. Furthermore, the building is being simultaneously

heated and cooled during the winter. These unusual patterns of utility usage needed further

investigation.


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Monthy Trend of Chilled Water

0

500

1000

1500

2000

2500

JanuaryM

arch May July

Septe

mber

November

JanuaryM

arch May July

Septe

mber

November

JanuaryM

arch

Years 2000-2002

Ton-Days

TABLE 3.4 Monthly Trend of Chilled Water

We needed to determine the demands of the building that created this pattern of usage. Having

realized the impact of Harvard buildings on the environment, our class had analyzed the sources

behind the impact. However, our investigation had only proved that Maxwell Dworkins building

operations required a greater understanding in order to form a complete picture.


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4.0 BUILDING ENERGY BALANCE


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4.1 Building Scale Energy Balance

Knowing the utility usage for the building, we placed these factors alongside other energy

components to create an energy balance of the entire building. Our class wanted to determine the

forms of energy flowing in and out of the building during various times of the year. We initially

came up with a very basic energy balance for the building. See Figures 4.1a and 4.1b for December

Energy Balance. See Figures 4.2a and 4.2b for July Energy Balance. Please refer to Appendix 2 for

calculations.

During the winter months, we calculated energy coming into the building from three major sources.

The first was sunload through the buildings exterior walls and windows. The electrical load from

such devices as computers, lights and elevators, accounted for thirty-nine percent of the energy load

into the building. The most significant factor bringing heat and energy into the building is steam,

FIGURE 4.1b December Energy Out

Heat

Transfer

through

Envelope

21%

Chilled

Water

32%

Ventilation

47%

FIGURE 4.1a December Energy In

Electrical

39%

Steam

55%

Sunload

6%


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which accounted for fifty-five percent. Energy is carried out of the building by heat transfer through

the exterior building frame, chilled water and ventilation. During the winter months, ventilation

systems of the building are responsible for nearly fifty-percent of the energy exiting the building.

These winter calculations, however, proved to be problematic for the class. There is a nearly twenty-

five percent of energy flowing in unmatched by the energy leaving the building. This discrepancy is

most likely due to unaccounted energy loss due to exterior frame radiation, and inaccurate weather

data.

As for the summer months, the energy coming into the building is from the sunload, the electrical

load, and ventilation. Since the steam transmission into the tunnels is stopped, there are no steam

costs. Chilled water and heat transfer are the means that energy escapes the building. Our July energy

balance came much closer to accounting for energy flow within Maxwell Dworkin. Only ten percent

of energy in was left unmatched by energy leaving the building. Although neither energy balance

was perfected, they were able to point out major areas of energy sources and sinks.

These inadequate balance of energy made it clear to our class that further investigation was required

to understand, on a more fundamental level, the heat exchange and energy flow within the building.

In order to be able to tackle all aspects of the building in depth, our class divided into separate groups.

Each group was given a specific area to research and analyze. In this manner, our class improved

FIGURE 4.2a July Energy In

Electrical53%Sunload

35%

Ventilation

12%

FIGURE 4.2b July Energy Out

ea

Transfer

through

Envelope

1%

Chilled

Water

99%


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upon this energy balance and found other causes for heat loss and gains within the building. After

gaining a perspective of the potential environmental impact of Harvard buildings, our class began

uncovering the basic operating features of Maxwell Dworkin. Armed with puzzling data and

unsolvable problems, we continued our investigation by delving deeper into individual components of

the building, including, an office temperature model, ventilation systems and the lighting scheme.


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5.0 INTELLIGENT CONTROL OF

BUILDING SYSTEMS


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5.1 APOGEE: The Intelligent Control System

5.1.1 System Description

Siemens Business Technologies and APOGEE Protocol Communication have collaborated to develop

the premier integrated building management solution available7

- a control network that digitally

operates the components within its building. Commonly referred to as APOGEE, this unit provides

a modernized Maxwell Dworkin with more control functionality at more control points in a more

sophisticated and unified manner. Technologically, APOGEE runs as follows: data is transmitted

and received over a dedicated set of wires running throughout the building. Each device on this

network is assigned an address and can be accessed by the host automation controller.8

Users can

access any type of information passed over this bus to monitor, schedule, update, review, and easily

operate its building's complex systems.

Ease of data accessibility is one of APOGEEs strongest features. According to Siemens, through

[APOGEEs] powerful, real-time management workstation, information and control is always

accessible to those who need it when and where they need it.9

Users can connect to APOGEE

through a corporate network, through any system panel, and even through a basic modem. Users can

also send system and trend reports to other users on the corporate network by taking advantage of

APOGEEs InfoCenter package. Siemens sums up such broad capabilities in its mantra on APOGEE

access: Sit anywhere, do anything.10

7 Quote taken from HVAC Controls section on Siemens website (www.sbt.siemens.com).8 Quote taken from Reliance Electric Publication D-2976 July 2000 (www.reliance.com).9 Quote taken from HVAC Controls section on Siemens website (www.sbt.siemens.com).10 Ibid.


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IMAGE 5.1 APOGEE Control System

5.1.2 Method of Investigation

For a preliminary understanding of the system, we researched the APOGEE control network online.

To clarify any misunderstandings of the description that we had after our online research and to

experience APOGEE first-hand, we met with Maxwell Dworkins Siemens contact, Scott Gaines.

Scott demonstrated the ease and flexibility of the system and also allowed us to access Maxwell

Dworkins control data through the APOGEE network. Finally, we spoke to the managers of the

building who work with Maxwell Dworkins APOGEE system on a daily basis. Ed Jackson, Greg

Kousidis, and Steve Robichaud all shared with us the details of this intricate relationship between the

particular building and APOGEE.

By the end of our quest to comprehend APOGEE, we felt that we had a solid understanding of the

way in which such a network controls and operates a complex Maxwell Dworkin.


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5.1.3 Findings

The APOGEE System provides scheduling functionalities so that the building components need not

be manually turned on and off, one-by-one. Such functionalities also ensure that these components

need not run excessively.

If the building manager, for instance, is aware that Maxwell Dworkin's G115 lecture hall will not be

used at all on Tuesday morning, he can pre-program the APOGEE System to leave that specific room

in "Unoccupied" mode so that the room's automated components can rest during that vacant period. In

this way, APOGEE - when used efficiently - can be an important energy saving tool.

APOGEE can also be a tool that provides comfort to its occupants, as it monitors comfort levels such

as temperature. Operating Maxwell Dworkin's heating, cooling, ventilating, and recirculating devices,

APOGEE keeps the building's temperature with the pre-set temperature range.

5.1.4 Recommendations

Through researching APOGEE, it is apparent that this control network has the potential to optimize

Maxwell Dworkins energy efficiency, quality of control, and information management. It is now

necessary to reexamine the APOGEE control commands and parameters that are currently operating

Maxwell Dworkin in order to ensure efficient use of the buildings Heating, Ventilation & Air-

Conditioning (HVAC) system.

It is therefore important to consider APOGEE in every aspect of this projects goals. Maxwell

Dworkins energy problem is discussed in many arenas throughout this paper, from an adaptable

temperature model to lighting efficiencies. Though not necessarily mentioned directly, any

recommended change to Maxwell Dworkins digital control system translates to a change to the

APOGEE network. In this way, APOGEEs accessibility, flexibility and information management all

play significant roles in the realization of this projects numerous findings and recommendations.


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5.2 Air Ventilation and Circulation Systems Controlled by APOGEE

5.2.1 Air Handling Units

At the heart of the buildings HVAC operations is the air-handling unit (more commonly referred to

as the AHU). The fundamental role of an AHU is to take in air from outside and condition it through

heating or cooling until the inside air achieves a desired range. Despite this apparently simplistic

fundamental role, AHUs can vary in many levels of complexity.

Diagram 5.1 displays a basic AHU that simply takes in outside air and passes it along the air duct

through a filter, into the supply fun, and then eventually to the appropriate destination space.

DIAGRAM 5.1 Basic Air Handling Unit

Diagram 5.2 is a more complex AHU design that conditions air brought in with heating or cooling

until the air has achieved the temperature specified by APOGEE control. Once the air reaches the

supply air duct, it will pass through either an activated heating or cooling device within the system. If

the airs temperature is above the set-point temperature for the area, an APOGEE command activates

the cooling coil to cool the air. Conversely, if the airs temperature is below the set-point

temperature, an APOGEE command activates the heating coil to heat the air. The newly conditioned

air is then sent to its destination space.


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DIAGRAM 5.2 Air Handling Unit with heating and cooling devices

Diagram 5.3 builds on the previous AHU design by incorporating mixed air, an important energy-

saving tool. As opposed to exhausting 100% of air returned from rooms in its building, this system

recycles a portion of the return air to mix with the incoming outside air. This mixed air is often at a

more moderate temperature than the outside air, thus it requires less energy to condition.

DIAGRAM 5.3 Air Handling Unit with heating and cooling devices, incorporating mixed air


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There are five AHUs ventilating Maxwell Dworkin. AHU #1 is the HVAC system for lecture hall

G115; AHU #2 controls the basement; AHU #3 controls the corridors and remaining rooms (aside

from G115) on the ground floor; AHU#4 & AHU #5 controls the systems on Floors 1, 2, and 3. The

power required to operate and control these five units, as well as the chilled and hot water needed to

condition the buildings air all contribute to the buildings total energy use.

5.2.2 Fan Coil Units

While Air Handling Units bring conditioned air to designated spaces, fan coil units recirculate air

within their room. A fan coil unit is a radiator that has hot and/or cold water to re-heat or re-cool the

air already conditioned by the AHUs.

Maxwell Dworkin uses top-of-the-line four-pipe fan coil units with heating and cooling coils that can

run year-round. Such a design differs from Pierce Halls seasonal system, for example, where there

is only one device that can serve as either heating or cooling at any one time.

With Maxwell Dworkins four-pipe fan coil units, as demonstrated below by Diagram 5.4, air is taken

into the system through a fan operated by APOGEE, passing by either an activated heating or cooling

coil. This active coil status is determined by APOGEE, which is connected to all fan coil unit

thermostats. If the room thermostat is above the set-point thermostat range, an APOGEE command

activates the cooling coil to cool the room and closes the heat coil. If the room thermostat is below

the thermostat set-point range, an APOGEE command activates the heating coil to heat the room and

closes the chilled water supply to the unit. This air is sent back out into the same room at a newly

conditioned temperature and with a different dew point.


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DIAGRAM 5.4 Fan Coil Unit

Maxwell Dworkin is equipped with fan coil units in every office space and research area

on Floors 1, 2, & 3. The power required to operate and control these units, as well as the chilled and

hot water needed to condition the buildings air all contribute to the buildings total energy use.


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6.0 OFFICE ENERGY BALANCE


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6.1 Adaptable Temperature Model

Although construction of an energy balance for an entire building is useful, any recommendations

drawn from such a macroscopic view run the risk of being too general. In other words, what may be

a good recommendation for the building as a whole may be a poor recommendation for individual

offices or laboratories. In order to make temperature recommendations for each of these spaces, it is

essential to understand them thermodynamically. We demonstrate a thermodynamic understanding of

spaces in Maxwell Dworkin through the development of an adaptable temperature model. This model

will predict the temperature in a room over time and is adaptable to any closed space similar to the

offices and laboratories in Maxwell Dworkin.

In this section, we will discuss first the existing temperature regulation for a typical room in Maxwell

Dworkin and then other uncontrollable factors that affect temperature. Although there is a range of

temperatures within a room, for the purposes of our discussion we will define the temperature of the

room to be the air temperature next to the thermostat. This assumption is particularly valid when the

air in the room is circulated, but even at night, when stratification of the air occurs, we find the

temperature strays fewer than two degrees from this value.

6.1.1 The Status Quo

Temperature regulation in Maxwell Dworkin is under the control of the Siemens APOGEE system.

Specifically, in office and research spaces, temperature regulation is achieved by the fan coil units

(FCUs). The FCUs internally circulate either heated or chilled water to condition the air within the

space. The FCUs are active between 7am and 7pm, with the possibility of a three-hour override of

the schedule if there is occupancy outside of this timeframe. When active, the FCUs heat or cool

based on thermostatic control.

Such thermostatic control in Maxwell Dworkin currently takes the form of what we have called a

narrow-band constraint. The thermostat has a static setpointgenerally 72Fand a dead band


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two degrees above and two degrees below that setpoint. Thus, with a 72F setpoint, the room is

considered appropriately conditioned as long as the temperature remains between 70F and 74F. If

the temperature drifts out of this range, active heating or cooling occurs. Of course, individuals

occupying office and research space can adjust the thermostat setpoint, but the APOGEE system does

impose absolute limits.

6.2 Method of Investigation

To assess whether or not we could improve upon the narrow-band constraint strategy currently in

place, we chose to develop a flexible mathematical model that would allow us to simulate the

behavior of an office or research space. With such a tool, we could assess the amount of savings

possible with a proposed control strategy and ensure that it did not compromise the comfort level of

the space.

6.2.1 Background

Before building such a model, some understanding of thermodynamics is necessary. Within a room,

there are several sources and sinks of heat. The largest of these inputs are due to the electrical

loadlights, computers, monitors, and other appliances all produce heat when activeand the

sunload, especially in the case of south-facing office windows. Active FCU heating and human heat

emissions also serve to warm a room, but to a much lesser extent than the other sources, as depicted

in Figure 6.1. The majority of heat removal is in the form of active cooling from the FCUs.

Additional heat loss also occurs through closed windows (via transfer through the glass and leakage

through the seals), although this is more than balanced by the electrical load and sunload. It should

be noted that passive transfer can also be a heat gain, dependent on the relative temperatures between

the interior and exterior of the building. For example, if it is warmer outside a window than inside,

heat will be transferred into a room, causing a rise in temperature to occur.


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FIGURE 6.1 Energy balance for a south-facing office with one-person

occupancy on a sunny April morning. Chart assumes thermal equilibrium (i.e.

constant temperature) for the room.

6.2.2 Heat Capacity of a Room

Another major factor involved in the temperature characteristics of a room is the heat capacity of the

room itself. A homogeneous material requires some finite, characteristic amount of heating to cause

its temperature to rise by one degree Fahrenheit. This is the materials specific heatfor our

purposes measured in units of BTU/(lb-F)and is mass invariant. Thus, the specific heat for

aluminum will be the same no matter what the mass of the sample under investigation. However,

when the specific heat is multiplied by the mass of a particular sample of the material, the value

obtained is mass dependent and is called the heat capacity of that sample, in units of BTU/ F. In the

case of modeling the temperature characteristics of an entire room, a conglomerate heat capacity

value, Cr, would be most useful. Fortunately, this can be calculated by summing the individual heat


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capacities of all the materials comprising the room. Once Cr is known, the rate of temperature change

of the room and the rate of heat gain for that room are related by Equation 6.1:

(Eq. 6.1)

where Tr(t) is the room temperature at time t, and Qr(t) is the rate of heat gain to the room.

To attempt to estimate the heat capacity of a room, we performed the following inventory of the

contents of a faculty office Table 6.1. One can quickly see that the major contributors to Cr are from

the walls, floor, and ceiling, all of which are well insulated and thus designed to retain heat within the

room.

TABLE 6.1 Specific Heats for Common Exposed Surfaces in a Room

Item Mass in lbs Volume in ft3 Specific Heat in BTU/(lb-F) [material]

Books 400 0.4 BTU/(lb-F) [wood]

Shelves 50 0.4 BTU/(lb-F) [wood]

Desk 200 0.2 BTU/(lb-F) [stone, plastic]

Chair 25 0.2 BTU/(lb-F) [plastic]

Air in room 200 0.25 BTU/(lb-F)

Walls (exludingwindows, door)

100* 13 BTU/(ft

3

-F) [gypsum board]

Floor 82* 23 BTU/(ft3-F) [concrete]

Ceiling 82 2.6 BTU/(ft2-F)

Window glass 2.5 0.20 BTU/(lb-F)

Door 150 0.4 [wood]

* Assuming four-inch heat penetration depth Sources: Bobenhausen, William, Simplified Design of HVAC Systems;

www.ac.wwu.edu/~vawter/PhysicsNet/Topics/Thermal/HeatCapTable.html

Assuming 120 ft2 area and 0.25 inch thickness. We ignore the glass due to its negligible total volume.

A final factor to consider is that heat capacity only considers the exposed surfaces of objects. Thus, if

some portion of a wall is obscured by a cabinet, that wall area does not see direct heat input from the

room and thus should not enter into the calculation. Rather, the exposed surfaces of the cabinet

would absorb the heat. We estimate that 40% of the wall space and 15% of the floor space within a

)()(

tQdt

tdTC rrr =


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faculty office is obscured by desks, tables, cabinets, and other such items. Taking this into account,

we estimate Cr to be in the range of 4000-5000 BTU/(lb-F). Similar calculations for a laboratory

such as the Harvard Robotics Laboratory (room 338) yield an estimated value of 6000-7000 BTU/(lb-

F).

6.2.3 Temperature Invariant Heat Sources

As mentioned above, there are some systems in a room that will always add heat regardless of

temperature. However, these heat sources may be time-dependent. For a typical room, these include

the occupants, any electronic devices, and the sunload.

Assuming we have information about the occupancy schedule of the room and the rate at which each

of these systems adds heat to the room, the total rate of heat flow into the room from these

temperature invariant sources, Qinv, is a sum of the rates of each source.

(Eq. 6.2)

Again, we use Q to represent rates of heat gain, with units of [heat / time].

In practice, Qpeople is easy to estimate if one knows the occupancy schedule of the room. The energy

output of a person sitting at a desk working is approximately 400 BTU / hr, and was verified by many

independent sources. Qelec is easy to measure with wattmeters. In general, lighting provides the

majority of electrically supplied heat to a room, with four 32W fluorescent bulbs releasing heat about

as fast as one computer and CRT monitor. For reference, most of the rooms in Maxwell Dworkin

have at least twelve 32W bulbs.

Qsun is the hardest of these sources to predict because it depends on the weather. Using weather data

in part from weather data from NOAA Weather station at Tufts University in Medford, MA, and

confirmed by equations, we found that Qsunwas the most significant of these temperature invariant

sources for rooms with a window facing the sun on a cloudless day. Qsun could be as high as 4000

BTU/hr at noon during January or 8000 BTU/hr at noon in the summer. These are maximum

valuesdepending on the hour of the day, the outside weather, and obstructions outside the window

from shading effects, we expect Qsun will be lower.

Qinv(t) =Qpeople(t)+Qelec(t)+Qsun(t)


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6.2.4 Heat Exchanges

There are also heat exchanges between the system and its environment. One example is the rate of

heat transfer through the windows and the wall. Other exchanges may come from conditioned air

blowing into the room or radiation to the outside. In each of these cases, there is a net gain or loss of

heat that is dependent on the difference in temperatures between the external environment and the

interior of the room. As mentioned above, we ignore effects such as stratification here (measured to

be only ~0.5oF/ft) and assume a constant temperature throughout the roomthe thermostat

temperature.

The rate of heat gain due to conduction and convection through an exterior surface of the room

depends on the R-factor of that surface, Rs, the area through which the heat is conducted, As, and the

difference in temperature between the room and the external environment (Text - Tr). The total rate of

heat gain to the system through these surfaces, Qwall, is just the sum of the rates through each surface:

(Eq. 6.3)

For one of the offices on the south wall of Maxwell Dworkin, Qwallis about 30 BTU/oF-hr times the

temperature differential. This is a low number that suggests Maxwell Dworkin is a well-insulated

building. A temperature differential of more than 13oF is required for the rate of heat passively lost

through the windows and walls to compensate for the heat supplied by a single person. Note also that

more heat is lost for greater temperature differentials. This suggests that more heat loss occurs at

higher room temperatures (Tr), a finding which could be exploited to reduce cooling costs. Our

model will demonstrate significant savings from increasing the set point temperature.

The rate of heat gain due to air changes in the room depends on the mass of air being exchanged and

the difference in temperature between the air entering the room and the air leaving the room. The rate

of heat gain is

(Eq. 6.4)

where r is the density of air (0.08 lbs/ft3), dV(t)/dtis the rate at which air enters the room (measured

in units of [volume / time]), Cp,air is the specific heat of air, and Tair is the temperature of the air

( ) -=surfaces

rext

s

swall tTtT

R

AtQ )()()(

Qair (t) = rdV(t)

dtCp ,air Tair(t)-Tr (t)( )


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entering the room. As will become clear from other sections in this report, Maxwell Dworkin is an

over ventilated building. The Massachusetts Building Code requires a minimum ofdV(t)/dt = 20 cfm

per person, but in practice Maxwell Dworkin provides far more.

We have already considered solar radiation as a temperature invariant heat source (as part of Qinv).

Radiation energy from the room to the environment is small and compensated for in the

manufacturer's R-value for the window.

6.2.5 Active Temperature Regulation

Many of the rooms considered have a fan coil unit with heating and cooling capability and a

thermostat. Based on research on the operation of the fan coil units, we introduce the following

model for fan coil unit operation.

The fan coil unit has only two inputs: Tr, the room temperature, and u t, a thermostat set-point

temperature at time t. We assume the thermostat also has some tolerance associated with it, in which

it will not modify the temperaturethe dead band. Mathematically, we suppose there is some

temperature differential Tl such that the fan coil unit will heat the room ifTr < ut Tl, but otherwise it

will not. Likewise, suppose there is some differential Th such that the fan coil unit will cool the room

ifTr> ut+ Th, but otherwise it will not. Tland Th could be the same value or different tolerances.

Assume that the fan coil unit is perfect at keeping the room temperature in the range ut - Tl< Tr < ut+

Th. We suppose that it does this by opening and closing binary heating and cooling valves as needed,

but mathematically we will write this as follows. The fan coil unit supplies heat to the room at the

rate QFCU(ut) such that the temperature in the room remains in the range ut- Tl< Tr< ut+ Th. As we

will see shortly, we will ultimately work with a discrete form of this model in which time is measured

in hours. The assumption that the fan coil unit controls the temperature perfectly as described above

is more accurate if the fan coil has an hour within which to reach its temperature.

6.2.6 Putting it all together

We have written rates and equations for the heat inputs and outputs to the system. The net heat gain

to the entire system is just the sum of these rates:


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(Eq. 6.5)

where Qsum is

With equation 6.1, we can write the differential equation governing the temperature in the room:

(Eq. 6.6)

Because we work with discrete hourly data, it is helpful to rewrite this equation as a difference

equation.

(Eq. 6.7)

where

and V[n] is the volume of conditioned air that enters the room between the hours n and n + 1.

This is our model for the temperature in a room.

6.2.7 Predicting the Status Quo

To demonstrate the effectiveness of the model, we conducted a five-day prediction of temperature

from April 5, 2002 to April 10, 2002 for the robotics lab in Maxwell Dworkin room 338. Small data

acquisition units were used to measure and record the temperature at distributed locations as well as

)()()()()( tFCUairwallinvr uQtQtQtQtQ +++=

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1 hr


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light levels and fan coil unit activity. The external temperature data came from a commercial weather

station at Tufts University in Medford, MA, within five miles of Maxwell Dworkin11

.

The thermostat was set at a level far below the setting allowed by the APOGEE system. We assumed

a tolerance ofTl= Th = 2 oF and chose ut to match the observed daytime data. ut remained constant

until the final full day of the trial (April 9), where it appears that ut increased by a degree.

FIGURE 6.2. Prediction of the temperature for MD338 and actual temperature

data over a five day period.

Figure 6.2 shows the correlation between the predicted temperature of the room and the actual

temperature, as observed by a data acquisition unit next to the thermostat. The correlation is fairly

good. The discrepancies between the models are probably due to errors in the estimates of when the

room was occupied. During the night of April 9 - 10, the data acquisiton units recorded a significant

temperature drop that was not caused by the fan coil units. Preliminary explanations are a significant

air change in the room, perhaps from opening the window. The model did not include such

11 Weather data from NOAA Weather station at Tufts University, Medford, MA.


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occurrences, and therefore we see a significant discrepancy between the model and the actual

temperature for that time.

6.3 Findings

6.3.1 Application of the Model

Armed with a verified temperature model, we can now predict how changes in Maxwell Dworkins

control strategy will affect the temperature characteristics of a room. Figure 6.3 shows a one-day

simulation run for a graduate student office (Room 342) in Maxwell Dworkin with June 1st

weather

data. The office has one exterior wall with two windows and two FCUs. Since the windows face

north, the sunload is negligible. Investigation of the actual room showed that there were four

computers and four CRT monitors in the room and twenty-four 32W fluorescent lamps (2620

BTU/hr) hanging from the ceiling. From observations of student behavior, occupancy was estimated

to be four people between the hours of 9am and 8pm, with one person remaining until 11pm. When

the room was occupied, we assumed that all lights were on, and that one computer and monitor

combination was active for each person present (480 BTU/hr for each computer-monitor pair). All

unused computers were assumed to be in sleep mode (at 120 BTU/hr) and all unused monitors were

assumed to be off. Thus, between the hours of 11pm and 7am the following day, the only source of

heat would be from the four computers in sleep mode. All values for computer and monitor power

consumption are from the Harvard Green Campus Initiative12

.

12 Harvard Green Campus Initiative, http://www.greencampus.harvard.edu/green_projects/cerp/facts.html


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FIGURE 6.3 Simulation of graduate student office (i.e. Maxwell Dworkin

room 342) on June 1 with constant thermostat setpoint of 72F and dead band

of 2F. Room has two north-facing windows and two FCUs.

In the simulation, there is a two-degree dead band, making the constraint between 71F and 73F.During the night, temperature remains essentially constant at 76F, indicating that the heat emitted by

the four computers in sleep mode nearly balances the passive loss through the windows. At 7am, the

APOGEE system becomes active, and the FCUs immediately begin circulating chilled water to bring

the temperature within the control band. From this point until 7pm, the FCUs maintain the

temperature at the top of the control range, since such a practice minimizes the amount of cooling

requiredand thus cost incurred. At 7pm, the APOGEE system deactivates, and the FCUs shut off.

The temperature then begins to rise, first from the four occupants present until 8pm, and then from the

single occupant remaining until 11pm. The temperature rise ceases when this late-worker departs,remaining steady at 76F until 7am the following morning.

The most striking feature of this narrow-band constraint is the constant need for cooling during the

day. Active heating is almost never required, even in the colder months of the year, as was evidenced

by a simulation done with this model for an entire years worth of data. Cooling comes at a higher


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cost than heating ($30.21 per MMBTU cooling versus $17.97 per MMBTU heating)13

. Indeed, there

is free heating from the sunload and human heat. Furthermore, both steam and chilled water are used

during some months of the year, implying that there may be both heating and cooling of rooms on a

single day14

. Such a scenario is easily imagined, for on a very cold evening, the passive heat loss

through a window may outweigh the input from the computers in sleep mode. Thus the temperature

of the room would drop during the night, perhaps falling below the lower limit of the narrow band

constraint. An example of this scenario is shown in Figure 6.4, which represents a simulated office

during a day in January. In this case, at 7am the subsequent morning, the FCUs would have to

circulate hot water to warm the room. However, after this occurs, people begin to arrive at work,

turning on lights and equipment and thus increasing the heat input to the room. At this point, the heat

flowing into the room may exceed the passive loss, causing the room temperature to rise until it

exceeds the upper limit of the control band, initiating cooling. Clearly, such a costly scenario should

be avoided.

13 FAS Planning numbers for Fiscal Year 2003. Courtesy of the Office of Physical Resources.

14 Steam and Chilled Water billing data, University Operations Services


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FIGURE 6.4. Simulation of an office for a day in January demonstrating

the risks of heating and cooling in the same day. The first bump in the

conditioning energy between hours 7 and 8 represents hot water heating

of the room, while the subsequent steady rise represents chilled water

cooling. These risks are associated with a narrow band constraint, here

shown as 2F for emphasis.

6.3.2 Optimizing the Office ControlsOur temperature model allows us to determine an optimal strategy for regulating a rooms

temperature in Maxwell Dworkin by formulating it as a control problem. For our purposes, we will

define the optimal strategy for temperature regulation as the strategy that minimizes the money spent

in heating and cooling at the FCU. This objective can be expressed as:

Minimize overu:

=1

])[(k

k

kFCU uQf g (Eq. 6.8)

wheref(QFCU[uk]) is a function that converts the amount of heat added or removed by the fan coil unit

into a cost and g (0,1) is a discount factor that weights immediate costs higher than costs in the

future. We define f(QFCU[uk]) from the costs for heating and cooling given above and in the FAS

Planning number for Fiscal Year 2003.


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We can minimize this sum subject to constraints defined by peoples comfort levels. For example,

we can make the constraint that the room temperature must always be between 65oF and 85

oF, i.e. 65

Tr 85. Furthermore, this temperature range may vary with time, relaxing to this range at night,

and becoming more strict when the room is occupied. Another constraint could be that the

temperature can only change so much from hour to hour, i.e. Tr[n] Td[n] < Tr[n + 1] < Tr[n] + Td[n].

For example, a value ofTd[n] = 1 for some n represents the constraint that the temperature at time n +

1 must be within one degree of the temperature an hour earlier. This constraint would protect against

rapid temperature swings that some might find uncomfortable. These are just two plausible

constraintsthis problem can be solved under any feasible constraint.

The formulation of our problem is:

Minimize:

=1

])[(k

k

kFCU uQf g

State Evolution Equation: ( )][][1

][][]1[ nFCUsumr

rr uQnQC

nTnnT ++=+ a

Subject to: Tmin[n] Tr[n] Tmax[n]

Tr[n] Td[n] < Tr[n + 1] < Tr[n] + Td[n]

One can solve this problem in a number of ways. We solved it using reinforcement learning, but this

is a simple dynamic programming problem and can be solved using many other methods. The

solutions to this problem are not expressible in closed form and require a computer to solve; however,

we quickly note that the solution of this problem is almost intuitive. The less we have to regulate the

temperature, the more money we save.


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FIGURE 6.5 Winter and summer comfort zones for peoplein typical winter and summer clothing during primarily

sedentary activity. From 2001ASHRAE Handbook.15

Because our fan coil unit operation overlaps fairly well with when Maxwell Dworkin is occupied, an

obvious solution would be to raise the thermostat setpoint and widen the dead band beyond the four

degrees currently used. To determine how much widening should occur without compromising

comfort, we consulted the ASHRAE comfort zones, depicted in Figure 6.5. These zones are plotted

on what is known as a psychrometric chart. Such charts allow us to characterize a volume of air

based on temperature and relative humidity. The hatched regions on the chart depict the comfort

zones as determined by submitting test subjects to air of varying temperatures and humidity levels

and recording their comfort level. From the chart, we approximated the ideal temperature ranges to

be between 69F and 75F in the winter and 74F and 80F in the summer. Returning to our June 1

graduate student office simulation, we included this new information, widening our control band to

encompass the full summer comfort zone. Additionally, we utilized a floating setpoint strategy.


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Instead of keeping the setpoint at a fixed temperature, we allowed it to self-adjust throughout the day.

The resulting plot, presented in Figure 6.6, at first glance looks very similar to the narrow band

constraint strategy seen in Figure 6.3. However, the important difference is that the temperature of

the room is at all times higher than with the narrow band constraint. Between 7am and 7pm, we again

observe that the FCUs cool the room to remain at the top of the temperature range80F. With this

widened control band and floating setpoint, cooling cost is greatly reduced. Running this simulation

with weather data for the entire first week of June, savings of 18% over the narrow band strategy

were possible.

FIGURE 6.6 Simulation of same graduate student office as in Figure 3 on June 1

with floating thermostat setpoint and control band broadened to encompass

summer comfort zone of 74F to 80F.

However, this example assumed a two-degree dead band, whereas Maxwell Dworkin actually

operates with a four-degree band. We incorporated this factor into the aforementioned simulation run

with an entire years worth of data. We assumed the same room parameters as in the simulations

15 2001 ASHRAE Handbook


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already presented. It is here that we found the amount of heating done by the FCUs to be negligible.

Comparing the narrow band and optimal strategies via this simulated year, we found that savings up

to 34% were possible. Realizing that the room simulated may not be entirely typical of the spaces in

Maxwell Dworkin and that other changes to building control would affect the need for FCU cooling,

we selected a more conservative estimate of 20% savings. Realizing that this savings comes almost

entirely from chilled water use in the FCUs, we calculated a cost savings of approximately $14,000

per year, or an equivalence of 30 acres of US commercial forest.

6.4 Recommendations

From the observations and simulations described above, we feel that an optimal control strategy

utilizing either a widened control band or an intelligently floating setpoint should be implemented in

Maxwell Dworkin. These changes would require a one-time cost to modify the APOGEE control

systems programming. Indeed, widening the dead band should be an almost trivial task. However,

some people may regard 80F as uncomfortably warm during the summer, despite the ASHRAE

suggestions. If this is the case, the control band could be slightly narrowed or shifted down to

encompass a slightly lower temperatures. While these would reduce the amount of savings that could

be reaped, they would ensure that the occupants of the building remained comfortable. Ideally, the

temperature control of a few volunteers rooms would be switched to this new strategy as a case study

before employing it building-wide. Additional simulations could also be run with the model to assess

the effect on savings if the band were narrowed or shifted. Regardless of the strategy chosen, our

model clearly demonstrates two trends that make intuitive sense:

1. Wider control bands are cheaper to maintain than narrower control bands2. Higher building temperatures are cheaper to maintain year round than lower temperatures.

These two trends are direct consequences of operating a well-insulated building. The heat supplied

by the buildings electrical load alone is enough to require cooling on many days of the year. In

choosing a strategy that follows either of these two trends, there is potential for significant

savingsboth in dollars and in adverse environmental impactat comparatively little cost.


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7.0 COOLING IN MAXWELL DWORKIN


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7.1 Introduction

Maxwell Dworkin is such a well-insulated building, and, as a result, the majority of the heat that

enters the building via steam, electricity, sunload, and other means must be actively removed through

the buildings chilled water system. During our investigation of Maxwell Dworkin, we discovered

various inefficiencies in the way that this cooling is being controlled on a daily, weekly, and seasonal

basis and in the management and operation of the control system in general. The results of these

inefficiencies are surprising trends in chilled water usage, such as the significant use during the winter

months. In order to reduce chilled water consumption in Maxwell Dworkin, we recommend a

combination of certain changes to the scheduling of cooling within the building and the use of

alternative forms of cooling.

7.1.1 Chilled Water System in Maxwell DworkinChilled water is produced in a facility in the basement of the Science Center using large machines

called chillers, distributed to the various buildings on campus via buried insulated pipes, and then

returned to the Science Center for re-cooling. The chilled water facility attempts to maintain a supply

water temperature of 45F and requests that each building return its used chilled water at

approximately 60F, in order to achieve maximum efficiency in the cooling process.

Chilled water is measured in a unit of energy called a ton-day, which is equivalent to approximately

288,000 BTUs. Each ton-day of chilled water is billed by the university at $8.70, based on planning

figures for the fiscal year 200316

. Chilled water is metered by recording both the flow rate of the

water, in thousands of gallons per minute, to each building and the temperature difference between

the water supplied and the water returned. These two values are used to calculate the ton-day unit for

billing purposes in two-hour intervals.

16 From Eugene Arcand, FAS Operations.


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Once the chilled water reaches Maxwell Dworkin, it enters the building through a mechanical room in

the basement, where it is pumped throughout the building to provide cooling. It is distributed to the

five Air Handling Units, all of the fan coil units on the top three floors, and a stand-alone cooling unit

in the DEAS computer server room in the basement. At these various locations the water may absorb

heat from the air, if cooling is necessary, and experience a rise in temperature. It is then returned to

the mechanical room where it entered the building and may either be returned to the Science Center

facility or re-circulated within the building to provide more cooling. Currently, the APOGEE control

system, which controls the flow of chilled water through the manipulation of a set of valves, is set to

re-circulate the water when its temperature is below 60F. Once the water temperature reaches the

setpoint of 60F, it is returned to the Science Center facility, in accordance with the facilitys

requested return water temperature.

A very basic diagram of the chilled water system within Maxwell Dworkin is shown in Figure 7.1:

FIGURE 7.1 Diagram of the Chilled Water System in Maxwell Dworkin


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In this diagram, the box marked cooling load represents the various devices within the building that

use chilled water to provide cooling. The valves shown are a simplified representation of the valves

controlled by the APOGEE system in order to maintain a set return temperature.

While inside Maxwell Dworkin, chilled water is used to provide two main of types of cooling:

comfort cooling and computer load cooling. Comfort cooling is provided to all areas within the

building that are occupied on a regular basis, such as offices, research spaces, classrooms, lecture

halls, and common spaces. On the ground floor and in the basement, this type of cooling is provided

strictly through Air Handling Units, while on the upper three floors, it is accomplished via a

combination of the Air Handling Units and the fan coil units within each office, research space,

classroom, and common area. The amount of chilled water required to provide adequate comfort

cooling in Maxwell Dworkin is difficult to estimate because it depends on a variety of factors,

including occupancy levels, electrical usage, and outside air temperature. Currently, the APOGEE

system is scheduled to provide comfort cooling 7 days a week from 7 a.m. to 7 p.m.

Computer load cooling is provided for areas within Maxwell Dworkin that contain sensitive electrical

equipment, which requires precise control of environmental conditions. There are four such areas in

the building: the DEAS computer server and telephone equipment rooms in the basement and two

EECS mechanical rooms on the first and second floors. By visiting these areas, we were able to

estimate the total amount of electrical power consumed by the various pieces of equipment to be

approximately 20 kilowatts, and thus estimate the amount of cooling necessary. The computer server

room has a stand-alone power supply unit, which can provide data on total electrical usage within the

room, the telephone equipment room contains very little equipment, and the two EECS rooms contain

similar numbers and types of units to the server room.

7.2 Method of InvestigationOur research of the chilled water system in Maxwell Dworkin proceeded along two main avenues: theacquisition of chilled water usage statistics for the entire building and the investigation of the control

system and mechanical units that provide cooling within the building. Using the data thus acquired,

we were able to identify potential areas for improvement in the o

Improving Energy Utilization

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