Building Fault Diagnosis

Alexander Stephen Bush

Advisor: Dr. Melody Baglione

Spring 2016

Abstract

Building retuning is the process by which cost-free changes in a building’s operation are

made in order to decrease the building’s total energy consumption. The process is iterative,

time consuming, and requires and intimate knowledge of building systems. For these reasons,

the process will benefit greatly from the automation of some or all parts of the retuning

process. Large commercial buildings are the focus of this project, and a university building, 41

Cooper Square, is used as a case study for the testing of this automation. Software is written

which analyzes the performance of an air handler unit and provides and automated diagnosis of

building faults.

Introduction

Minimizing a commercial building’s energy usage is an issue which is often dealt with at

the beginning of a building’s life cycle, during the design phase. However, the importance of the

issue can sometimes be slowly forgotten throughout the building’s operation. This manifests

itself as a steadily upward creeping cost of building operation. Obviously, mission critical

failures will result in the replacement of certain failing aspects of a building. However, these

catastrophic failures are naught but the result a late diagnosis of the issues which can plague a

building. In many cases, refining the operation of a building can reduce the load on the

mechanical systems of a building, resulting in a much longer lifetime for the building as a whole,

while simultaneously reducing the cost of building operation.

Those who are directly responsible for minimizing the operation costs of a building are

usually not the same people who are in the most practical position to fix the issues which cause

the building to operate below its design point. Building engineers’ first priority is to keep the

indoor environment safe and comfortable. The primary method for prioritizing daily tasks is the

influx of occupant complaints. Maintaining happy and healthy building occupants is a time

consuming process, and often leaves little room for monitoring building efficiency. To this end,

in order to allow building engineers the ability to focus on building energy usage, the process

must be made less time consuming and more straightforward. The building engineers need

tools which can assist them in monitoring and evaluating the building’s performance.

Delegating this analysis to a computer will allow building engineers to maximize field work time,

reducing the time commitment, yet still allow engineers to nip problems in the bud, before they

lead to occupant complaints, safety hazards, or mechanical failures.

The purpose of this project is to develop a methodology, and the accompanying

software tools, to assist a building operator in the diagnosis and prioritization of building energy

usage issues. This methodology is broken down by building system(Boilers, Chillers, AHUs, etc.)

and takes advantage of an existing sensor infrastructure in order to analyze the building’s

performance and suggest energy saving modifications.

Problem Statement

The goal of this project is to develop tools for building retuning which can facilitate the

monitoring and verification of building data, increase energy efficiency, and reduce operation

cost.

Methodology

The methodology consists of 6 main steps: Data Collection, Report Generation, Sensor

Verification and Repair(recollect data as necessary), Data Analysis, Implementation, and

Monitoring and Verification.

Step one is the deployment of sensors in order to determine the current operation of

the building. These sensors can be self-contained data loggers, or they can be integrated with

the building management system(BMS). The aim is to collect data from a variety of sensors over

a period of time in order to be able to determine current building operation.

Once the data is being collected, periodic reports should be created. These reports will

contain recent and relevant data in a format which is easily analyzed. An example of a report is

a csv file which contains the date, time and values for all the sensors related to a specific

system.

Before the data can be analyzed and energy saving measures can be determined, the

sensor data must be verified. Sensor data which is indicative of impossible building operation

can be used to diagnose sensor failures. These faulty sensors can then be recalibrated,

repaired, or replaced. For example, a humidity sensor with a negative value is a failed sensor.

Once the sensors have been verified, the data can be recollected. Data only needs to be

recollected if sensor hardware was replaced or recalibrated. Once all of the sensor data is

collected and verified to be true, the data can then be analyzed. This analysis can be done

manually. Often, BMS systems include graphing capabilities, which can be used to search for

energy wasting building operations. This step is one of the most tedious and time consuming

tasks, as it involves poring over large amounts of data, searching for hidden errors and patterns

which would be indicative of poor building operation. In addition, this step requires an operator

with an intimate knowledge of the entire building. Automation of this step can be extremely

beneficial for finding possible energy saving changes. In addition, energy savings and monetary

savings of proposed changes can be calculated, in order to gauge the effect on the building. The

predicted energy savings can also be used to prioritize building operation modifications.

The next step is implementation. The building schedule can be adjusted in order to

affect the building’s operation.

Of course, the process can be iterated multiple times, at regular intervals, in order to

keep the building operation from degrading. During this process, a solid monitoring and

verification plan should be in place, so that the benefits and savings can be quantified, and

errors can be minimized.

Over the course of this project, in order to minimize the time required to search for

building energy usage faults, automation of certain steps is implemented, through the use of a

Matlab script.

Air Handler Case Study

In order to test this methodology, the air handlers of 41 Cooper Square are used as a

case study. However, before integrating automated retuning, the current air handler operation

was determined by reading the ppcl(Powers Process Control Language) code which controls air

handler operation. From the code, a series of visual representations of the algorithm was

created, with the goal of verifying current operation. These slides are shown in APPENDIX

SOMETHING.

In order to begin automated retuning, data is collected from the building management

system(BMS) computer. This is done by setting up the built-in trending capability of the BMS

software. 33 individual points are trended at 15 minute intervals. Trending means that the BMS

will record the value of each data point at regular intervals. The following pages discuss in detail

the steps required to use the Matlab script in order to analyze the air handler.

Air Handler w/Economizer Retuning Guide(featuring AHUanalyzer.m):

Step 1: Trend points using Building Management System(BMS) software. Examples of BMS

point names for Siemens Insight points shown in parentheses.

Points to Trend for Fault Diagnosis(shown in red):

- Supply Temperature (41CS.RF.AH04.SUP.TEMP)

- Supply Temperature Setpoint (41CS.RF.AH04.SUP.TEMP.STPT)

- Heating Coil Valve Position (41CS.RF.AH04.HCOIL.VLV)

- Cooling Coil Valve Position (41CS.RF.AH04.CCOIL.VLV)

- Supply Static Pressure (41CS.RF.AH04.STATIC)

- Supply Static Pressure Setpoint (41CS.RF.AH04.HI.STATIC.STPT)

- Zone Damper Positions (41CS.303.VAV.301:SUP DMP CMD)

- Zone Temperatures (41CS.508.VAV.408:ROOM TEMP)

- Zone Temperature Setpoints (41CS.405.SAV.404:ROOM STPT)

Points to Trend for Energy Savings Estimation(shown in green):

- Mixed Air Temperature (41CS.RF.AH04.MIX.TEMP)

- Air Temperature after the Heating Coil (41CS.RF.AH04.HCOIL.TEMP)

- Air Temperature after the Cooling Coil (41CS.RF.AH04.CCOIL.TEMP)

- Supply Flow CFM (41CS.RF.AH04.SUP.FLOW)

- Supply Fan Energy Usage (41CS.RF.AH04.kW)

- Building Occupation Level

.

Step 2: Utilize Building Management Software to create a report. Schedule report for automatic

weekly data collection. If the software functionality exists, the report can be automatically

emailed as a comma separated value(.csv) file.

Points to Trend for Fault Diagnosis Points to Trend for Energy Estimation

Step 3: Run the AHUanalyzer Matlab script. This Matlab script will prompt the user to import

the csv file. The Matlab script will output a series of graphs and messages.

In addition to identifying humidity sensors which read negative values, the MATLAB script also

identifies possible changes in the air handler operation which can result in energy consumption

decreases. The program answers six basic building retuning questions. These questions are

discussed on the following pages:

Retuning Question #1: Is reset being used to control the discharge-air temperature setpoint?

Explanation: The discharge-air temperature requires energy from the heating and cooling coils

to maintain. During unoccupied building operation, the discharge-air setpoint can be allowed to

float within a wider margin, consuming less energy.

Pseudocode:

Alert user if discharge air temperature setpoint never changes.

Example:

The difference between any two

sequential data points of the Supply

Temperature Setpoint(green line) is zero

in all cases. Therefore, it can be

concluded that there are no supply

temperature setbacks.

Potential Energy Savings:

Hc = Heating Coil Temperature(°F)

Cc = Cooling Coil Temperature(°F)

M = Mixed Air Temperature(°F)

CFM = Supply Air Flow(ft3/min)

Cp = Specific Heat of Air(0.5861 kg/btu/°F)

ρ = density of air(0.03612 kg/ft3)

∫ ( )

Retuning Question #2: Is the discharge-air meeting set point, or do deviations occur?

Explanation: If the discharge-air temperature is not able to meet the setpoint, there are a few

possible explanations. The discharge-air setpoint could be improperly set. Any number of AHU

control points could be in operator override. A damper could be stuck. If the discharge-air is not

able to meet the setpoint, further investigation is required to determine the source of the

problem.

Pseudocode:

If Temp Error > 2 degrees, Alert user.

Example:

The aggregated difference between the

Supply Temperature(Red) and the

Supply Temperature Setpoint(Green) is a

difference of 5.5 °F. This is above the

threshold of 2 °F, therefore it can be

concluded that something is hindering

the building’s ability to regulate the

Supply Temperature.

Retuning Question #3: Are set points too high or too low; discharge-air temperature too warm

or too cold?

Explanation: If the discharge air temperature is too warm, then the zone temperature could be

too warm for comfort in certain parts of the building. Other parts of the building will then waste

energy to re-cool the air. If the discharge-air temperature is too cold, then there will be

significant waste in reheating the air.

Pseudocode:

HeatFaultCounter = # of instances where sup temp is greater than 60°F

ColdFaultCounter = # of instances where sup temp is less than 50°F

If Heat Fault Counter > 0, alert user.

If Cold Fault Counter > 0, alert user.

Example: The Supply

Temperature(Red) rises above 60°F at

least once. This behavior triggers the

program to throw a flag.

Potential Energy Savings:

T = Discharge Air Temperature(°F) Cp = Specific Heat of Air(0.5861 kg/btu/°F)

ρ = density of air(0.03612 kg/ft3) CFM = Supply Air Flow(ft3/min)

∫| |

Retuning Question #4: Do the discharge-air temperatures remain relatively stable?

Explanation: If the discharge-air temperatures are not stable, then it is indicative of an error

within the control algorithm. This type of error can also indicate that the discharge-air

temperature is improperly set.

Pseudocode:

If Temp Error > 2 degrees, Alert user.

Example: The aggregated slope of the

Supply Temperature(Red) is 20°F/min.

This value is above the threshold of

2°F/min, therefore it can be concluded

that something causing excessive Supply

Temperature variation.

Retuning Question #5: Is there simultaneous heating and cooling occurring in the AHU?

Explanation: Simultaneous heating and cooling should only be used for dehumidification

purposes. Otherwise, simultaneous heating and cooling is a waste of boiler and chiller energy.

Pseudocode:

If (Heating Coil ≠ 0 AND Cooling Coil ≠ 0 AND outside humidity<humidity setpoint),

Then Alert User

Example: The Heating Valve(Dark Orange) and the Cooling Valve(Orange) are never open at the

same time. This is desirable behavior.

Potential Energy Savings:

Hc = Heating Coil Temperature(°F) Cc = Cooling Coil Temperature(°F)

M = Mixed Air Temperature(°F) T = Discharge Air Temperature(°F)

CFM = Supply Air Flow(ft3/min)

Cp = Specific Heat of Air(0.5861 kg/btu/°F)

ρ = density of air(0.03612 kg/ft3)

∫ ( )

∫| |

Retuning Question #6: Is there a reset-schedule for the duct static pressure?

Explanation: The duct static pressure can be allowed to float during unoccupied times, as

ventilation and temperature load decreases heavily. This will potentially allow for the greatest

savings, as the duct static pressure directly relates to the fan speed.

Pseudocode:

Alert user if Discharge Static Pressure Setpoint is constant.

Potential Energy Savings:

( ) ∫ ( )

This graph is generated using empirical data. The raw data for this graph is shown in the

following table:

Supply Fan Energy Usage vs. Supply Air Flow

Fan Energy (kW) 0 5.6 15.49 18.59 22.19 31.79

Fan Speed (%) 0 60 78.80 83.80 88.83 100

Fan Flow (CFM) 0 17820 23404 24889 26383 29700

Retuning Question #7: Is the supply air static pressure too high?

Explanation: The supply air static pressure can be regulated by adjusting the zone dampers, or

by changing the supply fan speed. Increasing the supply fan speed requires a significant

increase in energy consumption, while opening the zone dampers requires a negligible amount

of energy. Therefore, it is considered better operation to have the zone dampers mostly open,

while the fan runs at a minimum speed.

Pseudocode:

If: 60<Average Damper Position<80, this indicates good operation.

Else: Alert User.

Example: The dampers vary

over a wide range. The

average damper position is

50%. This is moderately

desirable behavior, but it

could be slightly improved

to 70%.

In addition to the message box, the graph of the data which is being used to answer these

questions is shown:

There is also a pair of graphs which compare temperature economization with enthalpy

economization. The line labelled “Free Cooling” represents when conditions are favorable for

using outside air. When “Free Cooling” is high, then outside air can be mixed into the return air.

When “Free Cooling” is low, then mixing outside air into the supply would be inefficient.

The following flowchart can be used to determine the amount of energy used by the air handler

unit to treat the air. There are three possible paths of energy usage. There is a heating coil, a

cooling coil, and a reheat coil. If the air is too cold, the heating coil will heat the air to the correct

temperature. If the air is too hot and/or too humid, then the cooling coil will cool the air to the

correct temperature. Then the cooling coil will cool the air to the required temperature for

dehumidification. Then, the reheat coil reheats the air to the setpoint temperature.

Mixed Air

𝐻𝑒𝑎𝑡𝑖𝑛𝑔 𝐸𝑛𝑒𝑟𝑔𝑦

∫ |55 𝐹 𝑀| 𝐶𝑝 𝐶𝐹𝑀 𝜌 𝑑𝑡

𝐶𝑜𝑜𝑙𝑖𝑛𝑔 𝐸𝑛𝑒𝑟𝑔𝑦

∫ |𝑀 55 𝐹| 𝐶𝑝 𝐶𝐹𝑀 𝜌 𝑑𝑡

>55°F

<55°F

𝐷𝑒ℎ𝑢𝑚𝑖𝑑𝑖𝑓𝑦 𝐸𝑛𝑒𝑟𝑔𝑦

∫ |𝑀 4 𝐹| 𝐶𝑝 𝐶𝐹𝑀 𝜌 𝑑𝑡

𝑅𝑒ℎ𝑒𝑎𝑡 𝐸𝑛𝑒𝑟𝑔𝑦

∫ |55 𝐹 4 𝐹| 𝐶𝑝 𝐶𝐹𝑀 𝜌 𝑑𝑡

>60% RH <60% RH

Supply Air

The equations used in the flowchart are implemented in the program. As a case study, the

program analyzed a time span of three spring weeks for average energy usage, based on the

currently implemented enthalpy economization. This energy usage is compared with the

projected energy usage based temperature economization. The temperature economization

projected lower energy usage during all three weeks. Further case studies based on different

types of weather should be analyzed in order to determine when it is beneficial to use enthalpy

economization, and when it is beneficial to use temperature economization.

0 50000000 100000000 150000000 200000000

Feb29-Mar6

Mar7-Mar13

Mar14-Mar20

btu/week

Enthalpy vs Temperature Economization

Enthalpy

Temp

Economization: The purpose behind an economizer is to minimize the amount of energy

required to generate usable supply air. It does this by mixing the outside air and the return air.

The following figure shows the relative amount of energy required to generate usable supply air

at 55F and less than 60%RH.

The most energy is required when the mixed air is hot and humid. The least energy is required

when the mixed air already meets the temperature and relative humidity setpoints. Notice the

discontinuity within the energy function. This discontinuity is due to the energy required to

dehumidify the air by overcooling and reheating.

Sample Energy Calculation:

Given:

Outside Air: relative humidity = 60%, outside air temperature = 70F

Setpoint: relative humidity < 60%, supply air temperature = 55F

Find: Energy per minute required to make outside air meet setpoint.

Step 1: Use a Mollier diagram in order to determine if dehumidification is necessary. Based on

the diagram, the grains of moisture per pound of dry air of the setpoint is about 40. The outside

air, however, is about 65 grains/lb. This difference indicates that dehumidification is in order.

https://upload.wikimedia.org/wikipedia/commons/thumb/5/59/Mollier.pdf/page1-1275px-Mollier.pdf.jpg

Step 2: Since the air is too warm, it must be cooled. In addition, because dehumidification is

necessary, it must be cooled even further. At 42F and 100%RH, the air will contain the desired

water content of 40 grains/lb. The energy required to cool the air from 70F to 42F can be

calculated with the following equation:

| |

Where Cp is the specific heat of air, CFM is the volumetric flow rate of the air, and is the

density of the air.

|7 4 | 586

5

6

9 64

Step 3: After the air is dehumidified, it must be reheated to meet the setpoint temperature:

| |

|55 4 | 586

5

6

76

Step 4: Combine heating and cooling energy costs.

76

9 64

4

Conclusion

The Matlab script created in this project provides a proof of concept of automated

building retuning. Building upon existing automated data collection abilities of modern building

management systems, and entirely automated retuning analysis system is not only feasible and

practical, but also provides large long term monetary and time savings for buildings and

building operators.

In the future, the Matlab script can be expanded to be able to handle more building

retuning questions, and the script will be applied to other core areas of building retuning, such

as the chillers, boilers, interior zones, and cogeneration. In addition, as more data is collected, a

more detailed study of the benefits and detriments of enthalpy economization and

temperature economization can be conducted.

References

S. T. Taylor. “Why Enthalpy Economizers Don’t Work”. ASHRAE Journal, November 2010.

S. T. Taylor. “Sizing VAV Boxes”. ASHRAE Journal, March 2004.

M. Hydeman, et all. “Advanced Variable Air Volume System Design Guide”. California Energy Commission. October 2003.

DJ. Taasevigen, et all. “User’s Guide to Energy Charting and Metrics plus Building Re-tuning and Measurement and Verification”. US Department of Energy. Pacific Northwest National Laboratory. June 2013.

“Large Commercial Buildings: Re-tuning for Efficiency”. Pacific Northwest National Laboratory. January 2012. “APOGEE Insight-Basse Workstation” SIEMENS. June 2007.

N. Fernandez et all.“Energy Savings Modeling of Standard Commercial Building Re-tuning Measures: Large Office Buildings”. Pacific Northwest National Laboratory. June 2012.

Rodriguez, Jonathan O. "Technical and Economic Assessment of a Cogeneration System in an Urban Academic Building." Thesis. The Cooper Union, 2014. Print.

Appendix A: Navigating the BMS software

In this tutorial, you will learn to navigate the graphics window and check if a point is being

trended.

Log on to the BMS computer

1. Select Start -> All Programs -> Accessories -> Remote Desktop Connection

2. Enter IP Address: 199.98.16.168

3. Enter User ID: readonly2 and password: readonly2. (you are now remotely logged on the

BMS computer)

4. Click Insight icon on desktop

4a. If Insight does not open, it may already be open, so click the Graphics icon on the upper

control panel

5. Click the picture of the Academic Building.

6. Click “Air Systems” to open the list of air handlers.

7. Click “AH04” to select air handler number four. Alternatively, click the back arrow in order to

return to the previous screen.

8. Hover the cursor over the data point for the outside air damper. Notice the yellow box which

appears. This box contains the name of the point, a description of the point, the status of the

point, the priority of the point(“NONE” is normal operation, “OPER” is operator override, “OVRD”

is an automatic building system override.), the current value of the point, the ex-state, and total.

9. Drag the point to the Trend Definition Editor icon.

This will open the Trend Definition Editor and

automatically select the Outside Air Damper point. Notice

that the point is already being trended in fifteen minute

intervals and also five minute intervals.

10. Opening the Trend Definition Editor simply by clicking the icon will allow a user to manually

select a point to begin trending. By selecting “File”->”New”, the user can then manually browse

to a point which can be selected for trending. This will bring up the Object Selector Window:

Object selector tips:

a. The system queries the database for variable names every time “Find now” is clicked.

b. If you typed a query and don’t appear to have any variables when you think you should,

do a query for “*”. If you see the folder called “trended points”, enter that folder and re-enter

your query.

c. To select more than one variable

at once, hold ctrl while clicking on the

second and subsequent variable

names.

d. “*” is a wildcard placeholder and

can be used in place of any unknown

number of unknown letters or symbols

in the search bar.

e. “?” is also a wildcard, but will

only represent a single unknown letter

or symbol.

11. Alternatively, The trending wizard can be used. This will walk the user through the process

of selecting points to trend and also set up a report at the end.

7. Once the points have been trended, they can then be compiled into a report. To do this,

select Report Builder.

In the Trend Points section, click Configure -> Add in order to select the points to add to the

report. In the Output section, click Configure to set the output of the report to a csv file. Click the

… in order to select the location where the file will be saved. Be sure to save the report before

running it by clicking the floppy disk icon. Saving a report requires admin access.

8. Once a Report has been created, it can be run at any time using the Report Viewer.

.

9. In order to automate the process of running a report, use the Scheduler. Click Schedule ->

Report in order to set up an automatic schedule which will run the report at regular intervals.

This requires admin access.

12. IMPORTANT: In order to end the session, it is imperative that the Insight software is closed.

This will free up a license for others to use. Close the software by rightclicking on the blank

space of the Insight toolbar and selecting “Exit”.

Appendix B: Air Handler 4 PPCL Diagrams

Appendix C: MATLAB Code Temperature vs Enthalpy 3D Graph Generator: clear all close all clc

testTemp = [0:1:100]; testHumid = [0:1:100]; energy = zeros(100,100); %t,h

cpAir = 0.5861; %btu/(kg*F) airDensity = 0.03612; %kg/ft^3 supplyFlow = 50; setPoint = 55;

%relHumidity = 60 temp2check = [40,45,50,55,60,65,70,75,80,85,90,95,100,105,110]; allowableRH = [105,90,75,60,51,42,37,31,26,22,19,17,14,12,10]; polyRHcheck = polyfit(temp2check,allowableRH,3); x = linspace(55,110); y = polyval(polyRHcheck,x); plot(x,y) title('allowable relative humidity') xlabel('temperature') ylabel('maximum RH')

for t = 1:length(testTemp) for h = 1:length(testHumid) if(testTemp(t)<setPoint &&

testHumid(h)<polyval(polyRHcheck,testTemp(t))) %heat without dehumid heatingEnergy = ((setPoint-

testTemp(t))*cpAir*supplyFlow*airDensity); %btu/min energy(t,h) = heatingEnergy; %btu/min elseif(testTemp(t)>=setPoint &&

testHumid(h)<polyval(polyRHcheck,testTemp(t))) %cool without dehumid coolingEnergy = ((testTemp(t)-

setPoint)*cpAir*supplyFlow*airDensity); %btu/min energy(t,h) = coolingEnergy; %btu/min else %cool/heat with dehumid dehumidifyEnergy = ((testTemp(t)-

42)*cpAir*supplyFlow*airDensity); %btu/min reheatEnergy = ((setPoint-42)*cpAir*supplyFlow*airDensity);

%btu/min energy(t,h) = dehumidifyEnergy+reheatEnergy; %btu/min end end end

figure surf(testTemp,testHumid,energy) ylabel('temp (F)')

xlabel('humid (%RH)') zlabel('btu/min') title('Heating and Cooling Energy')

Air Handler Unit Analyzer: close all clc

button = questdlg('Import a new csv file?'); if strcmp(button,'Yes') clear all button = 'Yes'; [filename1, pathname] = uigetfile('*.csv', 'Select CSV file:'); if (isequal(filename1,0) | isequal(filename1,0)), error('Must provide file or disable the option in "builddr.m" program

file'); return; end end global bmsData; bmsData =

readtable([pathname,filename1],'Delimiter',',','ReadVariableNames',false);

wb = waitbar(0.01,'gathering variable names');

% figure out which points correspond to which variable name. j = 1; for i = 1:height(bmsData) if strncmp(bmsData{i,1},'Point',5) if strncmp(bmsData{i+1,1},'Point',5) break; end bmsDataHeaders(j,1) = bmsData{i,1}; bmsDataHeaders(j,2) = bmsData{i+1,1}; j=j+1; end end

waitbar(0.05,wb,'parsing csv file')

%% %csv2cell if strcmp(button,'Yes')

filename = [pathname,filename1]; fid = fopen(filename); text = char(fread(fid))'; fclose(fid); % First split it into lines lines = regexp(text,'(\r\n|[\r\n])','split'); % lines should now be a

cell array of text split by newlines

% a character is either a delimiter or a field inField = true; inQuoteField = false;

% if inField && ~inQuoteField --> then we're in a raw field

skipNext = false; data = {}; field = ''; for lineNumber = 1:length(lines) nChars = length(lines{lineNumber}); % number of characters in this

line fieldNumber = 1; for charNumber = 1:nChars if skipNext skipNext = false; continue end thisChar = lines{lineNumber}(charNumber); if thisChar == ',' if inField if inQuoteField % this comma is part of the field field(end+1) = thisChar; else % this comma is the delimiter marking the end of the

field data{lineNumber,fieldNumber} = field; field = ''; fieldNumber = fieldNumber + 1; end else % we are not currently in a field -- this is the start

of a new delimiter inField = true; end if charNumber == nChars % this is a hanging comma, indicating

the last field is blank data{lineNumber,fieldNumber} = ''; field = ''; fieldNumber = fieldNumber + 1; end elseif thisChar == '"' if inField if inQuoteField if charNumber == nChars % it's the last character, so

this must be the closing delimiter? inField = false; inQuoteField = false; data{lineNumber,fieldNumber} = field; field = ''; fieldNumber = fieldNumber + 1; else if lines{lineNumber}(charNumber+1) == '"' % this

is translated to be a double quote in the field field(end+1) = '"'; skipNext = true; else % this " is the delimiter ending this field data{lineNumber,fieldNumber} = field; field = ''; inField = false; inQuoteField = false; fieldNumber = fieldNumber + 1; end

end else % this is a delimiter and we are in a new quote

field inQuoteField = true; end else % we are not in a field. This must be an opening quote

for the first field? inField = true; inQuoteField = true; end else % any other character ought to be added to field field(end+1) = thisChar; if charNumber == nChars data{lineNumber,fieldNumber} = field; field = ''; fieldNumber = fieldNumber + 1; elseif charNumber == 1 % we are starting a new raw field inField = true; end end end end bmsData2 = data;

%endcsv2cell %% waitbar(0.10,'removing empty cells')

%find where data starts for y = 1:size(bmsData2,1) if strcmp(bmsData2(y,1),'Report Timings:') dataStarty = y; end end

replaced = 0; breakout = 0; for y = dataStarty:size(bmsData2,1) for x = 1:size(bmsData2,2) for k = 1:size(bmsDataHeaders,1) if strcmp(strcat(bmsData2(y,x),':'),bmsDataHeaders(k,1)) bmsData2(y,x) = bmsDataHeaders(k,2); replaced = replaced + 1; end if replaced == size(bmsDataHeaders,1) breakout = 1; break; end end if breakout == 1; break; end end if breakout == 1; break;

end end

for y = 1:size(bmsData2,1) for x = 1:size(bmsData2,2) if(ischar(bmsData2{y,x}) == 1) bmsData2(y,x) = strrep(bmsData2(y,x), '<', ''); bmsData2(y,x) = strrep(bmsData2(y,x), '>', ''); bmsData2(y,x) = strrep(bmsData2(y,x), 'MIN OA', '0'); bmsData2(y,x) = strrep(bmsData2(y,x), 'FREE CLG', '1'); bmsData2(y,x) = strrep(bmsData2(y,x), 'No Data', 'NaN'); bmsData2(y,x) = strrep(bmsData2(y,x), 'Data Loss', 'NaN'); end if(strncmp(bmsData2{y,x},'41CS',4)) bmsData2{y,x} = strcat('x',bmsData2{y,x}); bmsData2(y,x) = strrep(bmsData2(y,x), '-', '_'); bmsData2(y,x) = strrep(bmsData2(y,x), '.', '_'); bmsData2(y,x) = strrep(bmsData2(y,x), ':', '_'); bmsData2(y,x) = strrep(bmsData2(y,x), ' ', '_'); end end end end

bmsData3 = bmsData2((size(bmsDataHeaders,1)+7):(size(bmsData2,1)-1),:); bmsData3(:,3:size(bmsData3,2)) =

cellfun(@str2num,bmsData3(:,3:size(bmsData3,2)),'UniformOutput',0); bmsData = cell2table(bmsData3); bmsData.Properties.VariableNames = bmsData2((size(bmsDataHeaders,1)+6),:);

global dates; dates = zeros(height(bmsData),1); hAndC = zeros(height(bmsData),1);

for k = 1:height(bmsData) dates(k) = datenum([char(bmsData{k,1}),'

',char(bmsData{k,2})],'mm/dd/yyyy HH:MM:SS'); end

waitbar(0.20,wb,'wasting time')

global avgFan; avgFan = sum(bmsData.x41CS_RF_AH04_SPEED); avgFan = avgFan/height(bmsData);

global avgStaticPressure; avgStaticPressure = sum(bmsData.x41CS_RF_AH04_HI_STATIC_STPT); avgStaticPressure = avgStaticPressure/height(bmsData);

for y = 1:height(bmsData)

ARG4 = 273.16 / ((bmsData.x41CS_RF_AH04_SUP_TEMP(y) - 32.0) / 1.8 +

273.16); ARG4 = -(10.79586) * (1.0 - ARG4) - 2.1836 * log(ARG4) + 2.219598; ARG4 = 29.9 * (1.0 / exp(2.3026 * ARG4)); ARG4 = bmsData.x41CS_RF_AH04_SUP_HUMID(y) * ARG4 / 100; ARG4 = 0.622 * ARG4 / (29.0 - ARG4); SUP_ENTHALPY(y) = (0.24 + 0.45 * ARG4) *

bmsData.x41CS_RF_AH04_SUP_TEMP(y) + 1061 * ARG4; end

for y = 1:height(bmsData) if bmsData.x41CS_RF_AH04_SUP_HUMID(y) < 0 NEGATIVE_HUMIDITY = 1 end end

waitbar(0.30,wb,'determining allowable relative humidity')

%relHumidity = 60 temp2check = [55,60,65,70,75,80,85,90,95,100,105,110]; allowableRH = [60,51,42,37,31,26,22,19,17,14,12,10]; polyRHcheck = polyfit(temp2check,allowableRH,3); x = linspace(55,110); y = polyval(polyRHcheck,x); figure plot(x,y) title('allowable relative humidity') xlabel('temperature') ylabel('maximum RH')

waitbar(0.40,wb,'temperature economization anlysis')

%temperature economization cpAir = 0.5861; %btu/(kg*F) airDensity = 0.03612; %kg/ft^3 heatingEnergy = 0; coolingEnergy = 0; dehumidifyEnergy = 0; reheatEnergy = 0; tempEnergy = 0; %FORGOT TO ADD DEHUMIDIFICATION CHECK

for y = 1:height(bmsData) oa = abs(bmsData.x41CS_RF_AH04_SUP_TEMP(y) -

bmsData.x41CS_RF_OA_TEMP(y)); ret = abs(bmsData.x41CS_RF_AH04_SUP_TEMP(y) -

bmsData.x41CS_RF_AH04_RET_TEMP(y)); % TEMPECON(y+1) = TEMPECON(y) + 1; if oa-ret < 0 TEMPECON(y) = 1; %outside air heatingEnergy = ((55-

bmsData.x41CS_RF_OA_TEMP(y))*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensi

ty); %btu/min coolingEnergy = ((bmsData.x41CS_RF_OA_TEMP(y)-

55)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity); %btu/min

dehumidifyEnergy = ((bmsData.x41CS_RF_OA_TEMP(y)-

42)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity); %btu/min reheatEnergy = ((55-

42)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity); %btu/min tempEnergy = tempEnergy + (heatingEnergy + coolingEnergy +

dehumidifyEnergy + reheatEnergy)*15; %btu else TEMPECON(y) = 0; %inside air heatingEnergy = ((55-

bmsData.x41CS_RF_AH04_RET_TEMP(y))*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*ai

rDensity); %btu/min coolingEnergy = ((bmsData.x41CS_RF_AH04_RET_TEMP(y)-

55)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity); %btu/min dehumidifyEnergy = ((bmsData.x41CS_RF_AH04_RET_TEMP(y)-

42)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity); %btu/min reheatEnergy = ((55-

42)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity); %btu/min tempEnergy = tempEnergy + (heatingEnergy + coolingEnergy +

dehumidifyEnergy + reheatEnergy)*15; %btu end end %btu $ conversion tempEnergyDollars = tempEnergy*(3/1000000); tempEnergy = tempEnergy/1000000;%convert to million btu output11 = ['energy used during TEMPERATURE Economization: '

num2str(round(tempEnergy)) ' million btu/week = $'

num2str(round(tempEnergyDollars))];

%% %energy usage humidityRatio = zeros(height(bmsData),1); %kilograms water vapor per kilogram

of dry air mySupEnthalpy = zeros(height(bmsData),1); for y = 1:height(bmsData) if TEMPECON(y) == 1 % kg / kmol, molar mass of water vapor % divided by c = 18.0152 / 28.9644; % kg / kmol, molar mass of dry air

P = 101325; RH = bmsData.x41CS_RF_OA_HUMID(y); T = (bmsData.x41CS_RF_OA_TEMP(y)+459.67)*(5/9); temp = 54.842763 - 6763.22 ./ T - 4.210 .* log(T) + 0.000367 .* T ... + tanh( 0.0415 * (T - 218.8) ) ... .* (53.878 - 1331.22 ./ T - 9.44523 .* log(T) + 0.014025 .* T); es = exp(temp); e = RH./100 .* es;

Pd = P - e; humidityRatio(y) = (e./Pd) .* c; %kg/kg humidityRatio(y) = humidityRatio(y)*1000; %g/kg

tempC = (bmsData.x41CS_RF_AH04_SUP_TEMP(y)-32)*(9/5); mySupEnthalpy(y) =

(1010*tempC)+((humidityRatio(y)/1000)*(1840*tempC+2502)); %J/kg

mySupEnthalpy(y) = mySupEnthalpy(y)*0.00043; %BTU/lb end end

%% %BASAT questions

waitbar(0.50,wb,'answering BASAT questions')

%Is reset being used to control the discharge-air set point? energySaved1 = 0; energySaved2 = 0; tempChange = 0; for y = 1:(height(bmsData)-1) if isnan(bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(y)) == 0 &&

isnan(bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(y+1)) == 0 tempChange = tempChange + (bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(y)-

bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(y+1)); end %energyCalc tempDiff1 = ((2*bmsData.x41CS_RF_AH04_HCOIL_TEMP(y))-

bmsData.x41CS_RF_AH04_MIX_TEMP(y)-bmsData.x41CS_RF_AH04_CCOIL_TEMP(y)); energyRate1 =

tempDiff1*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity; %btu/min energySaved1 = energySaved1 + energyRate1*15; %15min intervals (btu/week) if (strncmp(bmsData.Time(y),'00',2)==1 |

strncmp(bmsData.Time(y),'01',2)==1 | strncmp(bmsData.Time(y),'02',2)==1 |

strncmp(bmsData.Time(y),'03',2)==1 | strncmp(bmsData.Time(y),'04',2)==1 |

strncmp(bmsData.Time(y),'05',2)==1 | strncmp(bmsData.Time(y),'06',2)==1) energySaved2 = energySaved2 + energyRate1*15; %15min intervals

(btu/week) end end energySaved2 = energySaved2*(3/1000000); %convert to money if tempChange == 0 output1 = 'WARNING: No Discharge Air Temperature Setbacks!'; output1p1 = [' Potential Energy Savings: $'

num2str(round(energySaved2)) '/week']; else output1 = 'Discharge Air Temperature Setbacks Enabled'; output1p1 = [' Potential Energy Savings: $'

num2str(round(energySaved2)) '/week']; end energySaved1Dollars = energySaved1*(3/1000000); energySaved1 = energySaved1/1000000; % convert to million btu output10 = ['Energy used during ENTHALPY Economization: '

num2str(round(energySaved1)) ' million btu/week = $'

num2str(round(energySaved1Dollars))];

%Is the discharge-air meeting set point, or do deviations occur? tempError = 0; for y = 1:height(bmsData) if isnan(bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(y)) == 0 &&

isnan(bmsData.x41CS_RF_AH04_SUP_TEMP(y)) == 0

tempError = tempError + abs(bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(y)-

bmsData.x41CS_RF_AH04_SUP_TEMP(y)); end end tempError = tempError/height(bmsData); if abs(tempError) > 2; output2 = 'WARNING: Discharge Air Temperature Unable to Meet Setpoint!'; else output2 = 'Discharge Air Temperature Meets Setpoint'; end

%Discharge Temperature too warm or too cold? energySaved3 = 0; tooHot = 0; tooCold = 0; for y = 1:height(bmsData) if bmsData.x41CS_RF_AH04_SUP_TEMP(y) > 60 tooHot = tooHot + 1; end if bmsData.x41CS_RF_AH04_SUP_TEMP(y) < 50 tooCold = tooCold + 1; end energyRate3 = (bmsData.x41CS_RF_AH04_SUP_TEMP(y) -

55)*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity; %btu/min energySaved3 = energySaved3 + energyRate3*15; %15min intervals (btu/week) end energySaved3 = energySaved3*(3/1000000); if tooHot > 0 output3 = 'WARNING: Discharge Air Temperature > 60F'; output3p1 = [' Potential Energy Savings: $'

num2str(round(energySaved3)) ' per week']; end if tooCold > 0 output3 = 'WARNING: Discharge Air Temperature < 50F'; output3p1 = [' Potential Energy Savings: $'

num2str(round(energySaved3)) ' per week']; end if tooHot == 0 && tooCold == 0 output3 = '50F < Discharge Air Temperature < 60F'; output3p1 = [' Potential Energy Savings: $'

num2str(round(energySaved3)) ' per week']; end

%Optimization problem: energyUsage(supTemp,fanSpeed) supTemp = 50; %degrees F supTemp = (supTemp - 32) / 1.8; %degrees C roomTemp = 70; %degrees F roomTemp = (roomTemp - 32) / 1.8; %degrees C CFM = 29700; %CFM cvAir = 0.718; %Kj/kg/C

massFlow = CFM*0.03612/60; %kg/s thermalEnergy = cvAir*massFlow*(roomTemp-supTemp); %kW of chilling power

required for normal operation. operatingTons = thermalEnergy/3.517; %tons of chilling power required for

normal operation.

chillerElectrical = operatingTons*0.55; %kW electrical energy fankW4 = [0,5.6,15.49,18.59,22.19,31.79]; fanSpeed4 = [0,60,78.80,83.80,88.83,100]; for y = 1:length(fanSpeed4) fanCFM(y) = fanSpeed4(y)*CFM/100; end polyFankW4 = polyfit(fankW4,fanCFM,5);

x = linspace(1,32); y = polyval(polyFankW4,x); figure plot(x,y) title('Fan Energy Usage') xlabel('CFM') ylabel('kW') hold on

%y = polyval(polyFankW4,x); fankW = linspace(1,32); for i = 1:length(fankW) supTemp(i) = -

(thermalEnergy/(cvAir*polyval(polyFankW4,fankW(i))*0.03612/60))+roomTemp;

%degrees C supTemp(i) = (supTemp(i)*1.8)+32; %chillkW(i) = end

figure plot(supTemp,fankW) xlabel('sup Temp') ylabel('fan kW')

%Do the discharge-air temperatures remain relatively stable? tempStable = 0; for y = 1:(height(bmsData)-1) if isnan(bmsData.x41CS_RF_AH04_SUP_TEMP(y)) == 0 &&

isnan(bmsData.x41CS_RF_AH04_SUP_TEMP(y+1)) == 0 tempStable = tempStable + abs(bmsData.x41CS_RF_AH04_SUP_TEMP(y)-

bmsData.x41CS_RF_AH04_SUP_TEMP(y+1)); end end if abs(tempStable) > 2; output4 = 'WARNING: Discharge Air Temperature Fluctuates!'; else output4 = 'Discharge Air Temperature Stable'; end

%Is there simultaneous heating and cooling occurring in the AHU? energySaved5 = 0; heatcool = 0;

for y = 1:height(bmsData) if isnan(bmsData.x41CS_RF_OA_HUMID(y)) == 0 &&

isnan(bmsData.x41CS_RF_AH04_SUP_HUMID_STPT(y)) == 0 humidifying = bmsData.x41CS_RF_OA_HUMID(y) -

bmsData.x41CS_RF_AH04_SUP_HUMID_STPT(y); else humidifying = 0; %assume not humidifying end if (bmsData.x41CS_RF_AH04_CCOIL_VLV(y) ~= 0 &&

bmsData.x41CS_RF_AH04_HCOIL_VLV(y) ~= 0 && humidifying <= 0) heatcool = 1; tempDiff5 = ((2*bmsData.x41CS_RF_AH04_HCOIL_TEMP(y))-

bmsData.x41CS_RF_AH04_MIX_TEMP(y)-bmsData.x41CS_RF_AH04_CCOIL_TEMP(y)); energyRate5 =

tempDiff5*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*airDensity; %btu/min potentialEnergyRate5 = (bmsData.x41CS_RF_AH04_MIX_TEMP(y)-

bmsData.x41CS_RF_AH04_SUP_TEMP(y))*cpAir*bmsData.x41CS_RF_AH04_SUP_FLOW(y)*ai

rDensity; %btu/min energySaved5 = energySaved5 + (energyRate5-potentialEnergyRate5)*15;

%15min intervals (btu/week) end end energySaved5 = energySaved5*(3/1000000); if heatcool == 1; output5 = 'WARNING: Simultaneous Heating and Cooling!'; output5p1 = [' Potential Energy Savings: $'

num2str(round(energySaved5)) ' per week']; else output5 = 'Heating and Cooling are Independant'; output5p1 = [' Potential Energy Savings: $'

num2str(round(energySaved5)) ' per week']; end

%Is there a reset-schedule for the duct static pressure? energySaved6 = 0; pressureChange = 0; for y = 1:(height(bmsData)-1) if isnan(bmsData.x41CS_RF_AH04_HI_STATIC_STPT(y)) == 0 &&

isnan(bmsData.x41CS_RF_AH04_HI_STATIC_STPT(y+1)) == 0 pressureChange = pressureChange +

(bmsData.x41CS_RF_AH04_HI_STATIC_STPT(y)-

bmsData.x41CS_RF_AH04_HI_STATIC_STPT(y+1)); if (strncmp(bmsData.Time(y),'00',2)==1 |

strncmp(bmsData.Time(y),'01',2)==1 | strncmp(bmsData.Time(y),'02',2)==1 |

strncmp(bmsData.Time(y),'03',2)==1 | strncmp(bmsData.Time(y),'04',2)==1 |

strncmp(bmsData.Time(y),'05',2)==1 | strncmp(bmsData.Time(y),'06',2)==1) energySaved6 = energySaved6 + bmsData.x41CS_RF_AH04_kW(y)*900;%kJ end end end % energySaved6 = energySaved6*0.947817; %convert to btu % energySaved6 = energySaved6*(3/1000000); %convert to money energySaved6 = energySaved6*0.002777; %convert to kwh energySaved6 = energySaved6*.10; %convert to money

if pressureChange == 0

output6 = 'WARNING: No Static Pressure Setbacks!'; output6p1 = [' Potential Energy Savings: $'

num2str(round(energySaved6)) ' per week']; else output6 = 'Static Pressure Setbacks Enabled'; output6p1 = [' Potential Energy Savings: $'

num2str(round(energySaved6)) ' per week']; end

%Is the supply air static pressure too high? %step one: which data points are VAV dampers? isDamperList = {}; for y = 1:(length(bmsData.Properties.VariableNames)) isDamper = strfind(bmsData.Properties.VariableNames(y),'DMP'); isRoof = strfind(bmsData.Properties.VariableNames(y),'RF'); if (isempty(isDamper{1}) == 0 && isempty(isRoof{1}) ~= 0) %isDamperList = [isDamperList;bmsData.Properties.VariableNames(y)]; isDamperList = [isDamperList y]; end end

openedDampers = {}; closedDampers = {}; failedDampers = {}; damperPositions = int16([]); for variable = isDamperList{1}:isDamperList{end} for y = 1:(height(bmsData)) if isnan(bmsData{y,variable}) == 0 damperPositions = [damperPositions;bmsData{y,variable}]; else if length(failedDampers) == 0 failedDampers = bmsData.Properties.VariableNames(variable);

%damper reads NaN elseif

strcmp(failedDampers{end},bmsData.Properties.VariableNames{variable}) == 0; failedDampers = [failedDampers

bmsData.Properties.VariableNames(variable)]; %damper reads NaN end end if length(damperPositions) >= 1 if damperPositions(end) == 100 %damper is fully open if length(openedDampers) == 0 openedDampers =

bmsData.Properties.VariableNames(variable); elseif

strcmp(openedDampers{end},bmsData.Properties.VariableNames{variable}) == 0 openedDampers = [openedDampers

bmsData.Properties.VariableNames(variable)]; end end if damperPositions(end) == 0 %damper is fully closed if length(closedDampers) == 0 closedDampers =

bmsData.Properties.VariableNames(variable); elseif

strcmp(closedDampers{end},bmsData.Properties.VariableNames{variable}) == 0

closedDampers = [closedDampers

bmsData.Properties.VariableNames(variable)]; end end end

end end

avgDamperPosition = mean(damperPositions); if avgDamperPosition <= 70 output7 = 'WARNING: Static Pressure is TOO HIGH!'; elseif avgDamperPosition >= 80 output7 = 'WARNING: Static Pressure is TOO LOW!'; else output7 = 'Static Pressure Within Acceptable Range'; end

output8 = char(['Dampers at maximum:' openedDampers]); output9 = char(['Dampers at minimum:' closedDampers]);

totalSavings = 52*(energySaved2 + energySaved3 + energySaved5 + energySaved6

+ (energySaved1Dollars-tempEnergyDollars)); output12 = ['Total Potential Savings: $' num2str(round(totalSavings)) ' per

year']; output =

{output1;output1p1;output2;output3;output3p1;output4;output5;output5p1;output

6;output6p1;output7;output8;output9;output10;output11;output12};

h = msgbox(output,'Summary of Retuning Analysis');

%%

% global weeks; % weeks = floor(height(bmsData)/1008);

week = 1;

limitL = (1008*week)-1007; limitH = size(bmsData,1);

waitbar(0.60,wb,'generating graphs')

%% %plot 1 figure hold on p5 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_OA_DMPR(limitL:limitH),'b'); p4 = plot(dates(limitL:limitH),SUP_ENTHALPY(limitL:limitH)); p3 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_RET_ENTHALPY(limitL:limitH),'

r');

p1 =

plot(dates(limitL:limitH),20+20*bmsData.x41CS_RF_AH4_5_ECON(limitL:limitH),'c

'); p2 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_OA_ENTHALPY(limitL:limitH),'g'); % [ax,p3,p6] =

plotyy(dates(limitL:limitH),bmsData.x41CS_RF_AH04_RET_ENTHALPY(limitL:limitH)

,dates(limitL:limitH),bmsData.x41CS_RF_OA_TEMP(limitL:limitH)); % [ax,p4,p5] =

plotyy(ax,dates(limitL:limitH),SUP_ENTHALPY(limitL:limitH),dates(limitL:limit

H),bmsData.x41CS_RF_AH04_OA_DMPR(limitL:limitH)); % [ax,p2,p1] =

plotyy(ax,dates(limitL:limitH),bmsData.x41CS_RF_OA_ENTHALPY(limitL:limitH),da

tes(limitL:limitH),100*bmsData.x41CS_RF_AH4_5_ECON(limitL:limitH)); p6 = plot(dates(limitL:limitH),bmsData.x41CS_RF_OA_TEMP(limitL:limitH)); set(p5,'linewidth',2,'color','g') %oa damper set(p1,'linewidth',2,'color','c') %enth econ set(p3,'color',[.7 0.2 0.2]) set(p6,'linestyle','--','color',[0.5 0 0.5]) set(p2,'color',[0.2 0.8 0.5]) if(strcmp(version('-release'),'2014b') || strcmp(version('-

release'),'2015b')) set(gca,'XTickLabelRotation',-45) end

set(gcf,'name','Enthalpy Economizer','NumberTitle','off') axis([limitL limitH 0 inf])

limitLVec = datevec(dates(limitL)); limitLVec = limitLVec([1:3]); limitHVec = datevec(dates(limitH)+1); limitHVec = limitHVec([1:3]);

tick_locations = limitLVec; days = 1; limitLVec = datevec(dates(limitL)+days); limitLVec = limitLVec([1:3]); while isequal(limitLVec,limitHVec) == 0 tick_locations = [tick_locations; limitLVec]; days = days + 1; limitLVec = datevec(dates(limitL)+days); limitLVec = limitLVec([1:3]); end tick_locations = [tick_locations; limitHVec]; tick_locations2 = double(datenum(tick_locations));

set(gca,'XTick',tick_locations2) datetick('x','dddd mmm dd HH:MM','keepticks') legend([p1,p2,p3,p4,p5,p6],'FREE COOLING','OA ENTHALPY','RET ENTHALPY','SUP

ENTHALPY','OA DAMPER','OA TEMP') legend('location','best')

%% %plot 2

figure

hold on p1 = plot(dates(limitL:limitH),40+60*TEMPECON(limitL:limitH),'c'); p2 = plot(dates(limitL:limitH),bmsData.x41CS_RF_OA_TEMP(limitL:limitH),'g'); p3 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_RET_TEMP(limitL:limitH),'r'); p4 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_SUP_TEMP(limitL:limitH),'b'); %[ax,p2,p1] =

plotyy(dates(limitL:limitH),bmsData.x41CS_RF_OA_TEMP(limitL:limitH),dates(lim

itL:limitH),TEMPECON(limitL:limitH));

set(p1,'linewidth',2) if(strcmp(version('-release'),'2014b') || strcmp(version('-

release'),'2015b')) set(gca,'XTickLabelRotation',-45) end

set(gcf,'name','Temperature Economizer','NumberTitle','off') axis auto

set(gca,'XTick',tick_locations2) datetick('x','dddd mmm dd HH:MM','keepticks') legend([p1,p2,p3,p4],'FREE COOLING','OA TEMP','RET TEMP','SUP TEMP') legend('location','best') %% %plot 3 % figure % hold on % p1 = plot(dates(limitL:limitH),mySupEnthalpy(limitL:limitH)); % p2 = plot(dates(limitL:limitH),humidityRatio(limitL:limitH)); % p3 = plot(dates(limitL:limitH),bmsData.x41CS_RF_OA_HUMID(limitL:limitH)); % if(strcmp(version('-release'),'2014b')) % set(gca,'XTickLabelRotation',-45) %end

% axis auto %

% set(gca,'XTick',tick_locations2) % datetick('x','dddd mmm dd HH:MM','keepticks') % legend([p1,p2,p3],'mySupEnthalpy','humidityRatio','OA HUMID') %

%% %plot 3 % % figure % hold on % p1 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_CCOIL_VLV(limitL:limitH),'g')

;

% p2 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_HCOIL_VLV(limitL:limitH),'r')

; % p3 = plot(dates(limitL:limitH),bmsData.x41CS_RF_OAT(limitL:limitH),'b'); % p4 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_CCOIL_TEMP(limitL:limitH),'c'

); % p5 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_SUP_TEMP(limitL:limitH)); % set(p5,'color',[.7 0.2 0.2]) % if(strcmp(version('-release'),'2014b')) % set(gca,'XTickLabelRotation',-45) %end

% %set(gcf,'name','Cooling','NumberTitle','off') % axis auto % % set(gca,'XTick',tick_locations2) % datetick('x','dddd mmm dd HH:MM','keepticks') % legend([p1,p2,p3,p4,p5],'cool vlv','heat vlv','OAT','ccoil temp','sup

temp')

%% %plot 4

figure hold on p1 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_SUP_TEMP_STPT(limitL:limitH),

'g'); p2 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_SUP_TEMP(limitL:limitH),'r'); p3 = plot(dates(limitL:limitH),bmsData.x41CS_RF_OA_HUMID(limitL:limitH),'b'); p4 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_SUP_HUMID_STPT(limitL:limitH)

,'c'); p5 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_CCOIL_VLV(limitL:limitH)); p6 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_HCOIL_VLV(limitL:limitH)); p7 =

plot(dates(limitL:limitH),bmsData.x41CS_RF_AH04_HI_STATIC_STPT(limitL:limitH)

); set(p5,'color',[.7 0.2 0.2]) if(strcmp(version('-release'),'2014b') || strcmp(version('-

release'),'2015b')) set(gca,'XTickLabelRotation',-45) end

set(gcf,'name','data that may or may not contain faults','NumberTitle','off') axis auto

set(gca,'XTick',tick_locations2) datetick('x','dddd mmm dd HH:MM','keepticks')

legend([p1,p2,p3,p4,p5,p6,p7],'SUP TEMP STPT','SUP TEMP','OA HUMIDITY','SUP

HUMIDITY STPT','CCOIL VLV','HCOIL VLV','PRESSURE STPT') legend('location','best') %% %plot 5

figure hold on for variable = isDamperList{1}:isDamperList{end} if isnan(bmsData{y,variable}) == 0 p1 = plot(dates(limitL:limitH),bmsData{(limitL:limitH),variable}); end end

if(strcmp(version('-release'),'2014b') || strcmp(version('-

release'),'2015b')) set(gca,'XTickLabelRotation',-45) end

set(gcf,'name','Damper Positions','NumberTitle','off') axis auto

set(gca,'XTick',tick_locations2) datetick('x','dddd mmm dd HH:MM','keepticks') title('Damper Positions')

close(wb)