dabotm: a bems assisted on-going commissioning tool · data analysis using artificial intelligence...

National Conference on Building Commissioning: April 22- 24, 2008

Choinière, DABO™: A BEMS Assisted On-Going Commissioning Tool 1

DABOTM: A BEMS ASSISTED ON-GOING COMMISSIONING TOOL

Daniel Choinière, P.E. Natural Resources Canada

About the Author

Daniel Choinière joined the CANMET Energy Technology Centre (CETC-Varennes) as Technical expert of the Intelligent Building Team in October 1998. His primary role is to manage projects and develop technologies to improve building HVAC systems operation and energy performance. This includes Automated Fault Detection, fault diagnosis, commissioning and energy management tools linked to building control systems. At the international level, Daniel is the co-operating agent of the IEA-Annex 47 project “Cost Effective Commissioning for Existing and Low Energy Buildings” with the participation of experts from 14 countries. Prior to joining the CTEC-Varennes, Daniel spent over 15 years as a Senior Energy Analysis and HVAC Engineer at Publics Works Canada in Montreal.

1 Introduction A national program on continuous building optimization (also known as on-going and retro-commissioning) is under preparation in Canada with the participation of government agencies and national energy utilities. The program includes the development of guides and tools that facilitate the implementation of the optimization process, as well as the delivery of training and awareness programs aimed at addressing the needs of building owners, commissioning providers and building operators. The optimization process and a tool ‘DABOTM’ (Diagnostic Agent for Building Operation) developed in Canada are being demonstrated in more than 10 projects. Demonstration projects include some of the first Canadian LEED buildings and the participation of major Canadian facility management firms and commissioning providers.

Building Energy Management Systems (BEMS) offer opportunities to automate some aspects of commissioning. Reduction of process cost and manual effort on site, transformation of a one-time application to a continuous process generating benefits over the entire life of a building, development of a detailed systematic approach to improve quality assurance, and integration of energy audit capabilities to improve the overall performance of buildings are some of them.

This paper presents the concept for DABO, an automated commissioning tool that helps users verify and optimize the performance of building HVAC systems using the capabilities of BEMS. The tool is applicable mainly to commercial and institutional buildings. In its simplest form, the tool monitors building control data and stores it in a structured database to be used on-line or upon request. A reasoning algorithm performs an intelligent analysis of the monitored data and

also performs additional automated commissioning of HVAC components and systems, identifying faults, diagnosing them, calculating performance indices and facilitating the evaluation of potential energy efficiency improvements. DABO also automatically generates detailed reports tailored to the user needs.

2 Background The work presented in this paper describes some Canadian contributions to various research projects within the framework of the Energy Conservation in Building and Community Systems (ECBCS) program of the International Energy Agency (IEA). Mainly the contributions include:

IEA-ECBCS-ANNEX 34: Computer-Aided Evaluation of HVAC System Performance (1997-2000)

• Development of an embedded FDD tool for variable air volume boxes

• Development of a stand alone air handling unit fault detection and diagnosis tool. This tool was the primary component in the first generation of DABO.

IEA-ECBCS-ANNEX 40: Commissioning of Building HVAC Systems for Improved Energy Performance. (2000-2004)

• Development and demonstration of a stand alone commissioning tool for air handling units and air distribution systems (many types of terminal devices). The new tools where incorporated into DABO.

IE -ECBCS-ANNEX 47: Cost Effective Commissioning of Existing and Low Energy Buildings (2004-2008)

• Development and demonstration of a stand alone commissioning tool for heating and cooling hydronic networks, as well as improvement of the commissioning tool for air distribution systems with application to low energy buildings. The new tools have been incorporated into DABO.

• Demonstration of the application of DABO as a tool for enhancing the recommissioning and commissioning processes in existing and low energy buildings.

3 DABOTM: A BEMS-assisted commissioning tool In order to go beyond the available capabilities of Building Energy Management Systems (BEMS) and limit the waste of energy, the Intelligent Buildings Team from the CANMET Energy Technology Centre in Varennes, Canada (CETC-Varennes) has developed DABO (figure 1), a platform to support connection between building energy management system (BEMS) building data and advanced analytical processes such as Fault Detection and Diagnosis, On-Going Commissioning, Energy Prediction (Future) and Predictive Maintenance (Future).

DABO is a software package that uses various technologies, both conventional and based on artificial intelligence techniques, to perform data analyses aimed at ensuring optimum operation



of building systems. DABOTM allows the detection and diagnosis of major faults and sub-optimal operating parameters in air handling equipment, room control devices, heating circuits, cooling circuits, lighting devices and energy meters linked to a central building control network.

DABO resides on a Personal Computer and analyzes incoming data from the BEMS. It is compatible with most existing building control systems.

Figure 1. General architecture of the Diagnostic Agent for Building Operation developed by the CANMET Energy Technology Centre.

Diagnostic A

gent for Building

OperatoionD ata B ase

D D E /O P C /O D B C

OD

BC

E n erg yP red ic to r

F au lt D e tec tio n &D iag n o stic A g en t

C o m m issio n in gA g en t

E x is tin g B u ild in g E n erg ym an ag em en t S ys tem

A rtific ia l In te llig en ceA lg o rith m s

C o n d itio n -B asedM ain ten an ce A g en t

Diagnostic A

gent for Building

OperatoionD ata B ase

D D E /O P C /O D B C

OD

BC

E n erg yP red ic to r

F au lt D e tec tio n &D iag n o stic A g en t

C o m m issio n in gA g en t

E x is tin g B u ild in g E n erg ym an ag em en t S ys tem

A rtific ia l In te llig en ceA lg o rith m s

C o n d itio n -B asedM ain ten an ce A g en t

Fault Detection and Diagnostic (FDD) and On-Going Commissioning (COMM).

The FDD/COMM functionalities receive monitoring and control point data and analyse them to detect symptoms of abnormal behaviour in various HVAC components, such as un-calibrated or failed sensors, actuator or linkage failures, controller instabilities, non-optimal sequences of operation, etc. These functionalities can also diagnose the possible causes and provide explanations for abnormal behaviour. By utilising the same information as the BEMS but applying the diagnostic reasoning of an expert buildings engineer, DABO is able to go beyond the capabilities of conventional BEMS alarms. The On-Going Commissioning functionality also monitors various levels of energy performance.

Systems are supervised continuously (24 hours a day, 365 days per year).

Various types of reports adapted to the needs of the various users can also be issued by DABO. These will be described later in this document.

Figure 2. Structure of the FDD/COMM functionalities for HVAC systems embedded in DABO.

Defective devices

Building optimisationsetpoint and sequence of operation

Performance reportenergy, comfort, operation quality

BEMS - Building Energy Management SystemBuilding-Plants-Systems-Rooms(Johnson Controls, Delta Controls, Siemens, Honeywell ,Any Bacnet control system, or OPC server, etc.)

FDD - Systems level

Report G

enerator

FDD - Component Level

Global Analysis level

DABOTM – Diagnostic Agent for Building Optimisation

a

b

c

DATA Analysis using artificial intelligence techniques

Gross data from BEMS (OPC or ODBC client)DABOTM – Data acquisition application

SQLData Base



The three levels of analysis for FDD and COMM functionalities

As shown in Figure 2, the analysis process is performed at three levels.

Component level

At the first level, an automatic component analysis of individual HVAC devices and equipment is performed using current commissioning and FDD procedures. Tests are performed every hour. This level uses a combination of calculated performance indices and a Rule Based Expert System to perform the analysis; more detailed explanations are provided in following sections.

System level

The second level of testing consists of an integrated semi-automatic system analysis for the operation and energy performance of the overall HVAC systems. This is done over a longer period of time (e.g., hours, days, weeks or months). A combination of calculated performance indices, statistical analysis, and HVAC system optimisation reference tables are used. More detailed explanations on the performance indices, statistical analysis, and reference optimisation tables are discussed in the following sections.

Global Analysis level

On the third level basic auditing is performed for energy consumption, comfort levels, and control accuracy. This audit uses a combination of calculated performance indices, statistical analysis, and user defined report structures. It can also be used to monitor energy saving improvements and to provide building historical data for energy audits or for HVAC and lighting conditions.

Figure 3 provides a table summarising the actions that DABO performs for fault detection and diagnosis at component level, system level and energy and comfort performance auditing.

Figure 3. Functionalities of DABO and examples

Component Level: Fault Detection and Diagnosis -

Sensors: Temperature, Humidity, Air flow, Pressure, CO2 levels.

Faults detected: incorrect reading, complete failure.

Damper, Valve, Actuator:

Faults detected: stuck, incorrect position feedback, incorrect minimum position, defective leakage

Coil, Humidifier, Fan:

Faults detected: insufficient capacity

Controllers:

Faults detected: logic, tuning, signal, instability (set point, output)

Set points: Temperature, Pressure, Ventilation rate, Relative Humidity, CO2 levels:

Faults detected: set point switched to manual

System Level: Fault Detection and Diagnosis + Optimisation -

Helps users perform analysis for:

Undersized and oversized components, systems and plants

Non optimum set points: temperature, pressure, humidity

Ventilation start/stop schedules

Inappropriate sequences of operation and schedules

Poor energy management and peak load control

Global Analysis level: Energy, Control Accuracy and Comfort Performance -

Energy and comfort profile (hour, day and month):

Individual room

Specific equipment (terminal unit device, AHU, heating/cooling power plant)

Whole building (electric, gas and oil meter)

Historical database for energy audit or retrofit and also for estimating energy savings.

DABO is a software platform with a user-friendly GUI (graphical user interface). This interface enables an easy configuration of the system, and invokes the various detection algorithms. The platform ensures communication and management of all data between the BEMS, the database used by DABO the artificial intelligence algorithms, and the report generator.



3.1 Additional details on functionalities

3.1.1 Rule-Based Expert System The FDD Component level tool is based on artificial intelligence algorithms (Rule Based Expert System) and uses building data and performance indices. In order to mimic human reasoning, an expert system uses a knowledge base containing specific domain knowledge. The domain knowledge is expressed by «If-Then-Else» rules. These rules are used to draw conclusions about the operation of a particular component.

The rules are coded with an expert system programming language called “OPS/JAVA.” The DABO expert system contains more than 800 rules.

3.1.2 Performance Indices The FDD at system level uses performance indices, statistical analysis, and an HVAC system optimisation reference table (user manual cross-check analysis) to evaluate whether the selected systems are at maximum performance. Performance indices are BEMS measurement and control values or values calculated from BEMS values. They quantify the performance of a control loop, a component, or a system. They are divided into seven groups as indicated hereunder.

3.1.2.1 Basic HVAC monitored point values

This includes any DABO BEMS monitored control point. Example: Supply air temperature (SAT), supply air pressure (SAP), etc.

3.1.2.2 Set point performance indices

These indices are relative values that quantify, in percentage form, how far a sensor output is from its set point. For example, the temperature set point performance index (PI_TSP) displays, in percentage, how the temperature differs from its corresponding set point. If the temperature is equal to the set point, the PI_TSP will have a value of 0%.

3.1.2.3 Output performance indices

These indices quantify, in percentage form, the relative output of a sensor over its annual design set point range. For example, if the supply air temperature of an air-conditioning unit can vary from 13°C to 21°C over a year and the actual temperature is 13°C, the PI_T will have a value of 100%. If the actual air supply temperature is 21°C, the PI_T will be 0%.

3.1.2.4 Device performance indices

These indices quantify, in percentage form, the output of a device (coil, fan, chiller, boiler, pump, etc.). A value of 0% means the device is off or not being used and 100% implies the

device is operating at full load. For example a fan with its drive command at 50% will have PI_DEV = 50%.

These indices can also be expressed in relation to the outside air temperature or per unit of area.

3.1.2.5 Input performance indices

These indices show the average and maximum performance indices of loads connected to a device as well as information from the source of heating and cooling of this device.

For example, in a case of an AHU, input performance indices will be calculated for the following:

• From all control zones supplied by the AHU: o The average and maximum heating performance indices of the control zone, o The average and maximum cooling performance indices of the control zone, o The average and maximum damper performance indices of the control zone.

• From the heating network, cooling network or heating and cooling generator: o The supply heat and cool water temperature, o The supply heat and cool water supply pressure, o The cooling and heating performance indices from the cooling and heating

generators where applicable.

3.1.2.6 Power value indices

These indices show in kilowatts (kW) the electric power used by devices such as fans, pumps, chillers, boilers, etc.).

The electric power values can be obtained directly from power meter readings or calculated from current sensors or from virtual meters.

3.1.2.7 Energy value indices

These indices show, in user defined energy units, the energy exchange rate on a device such as a chiller, boiler, hydronic network, cooling tower, etc.

The energy values can be obtained directly from energy meters or calculated from temperature and flow sensors, or from temperature sensors and virtual flow meters.

3.1.3 Performance Indice Analysis The performance index-based method compares indices over a specific period (one hour, one week, one month). Limits can be set to define a range of values corresponding to acceptable behaviour. Values that lie outside the range can indicate that a problem exists. Performance index values can also be used to optimise set points and improve system performance. Limits can be manually set or estimated continuously. Performance indices can be analysed by expert rules (FDD component level) or by users who can cross check values with HVAC system optimisation reference tables as described hereunder.



3.1.4 HVAC System Optimisation Reference Tables The HVAC system optimisation reference tables show how to use and interpret DABO performance indices in the manual detection of faults or non-optimised set points and parameters. These matrixes are developed for air terminal devices, air handling equipments, heating-cooling networks, boilers, and chillers. They show the usual applicable optimisation measures with their corresponding performance indices to use during the screening, the analysis, and the detail evaluation of each measure.

4 Specifications for the main DABO capabilities

4.1 Data Analysis available in DABO as of July 2007 DABO provides automatic data analyses, such as artificial intelligence algorithms, engineering calculations, and statistical analysis that can be executed automatically by DABO based on a user’s request.

Figure 4 shows where data analysis is available for a specific device type. Figure 5 illustrates the structure of various devices within a system.

Figure 4. List of Data Analysis available in DABO as of July 2007

DEVICES (see figure 5 for more details)

Point monitoring

FDD COMMISSIONING

Air Handling Unit (AHU) √ √ √

Dual Duct AHU √ √ √

Building Exhaust System √ √ √

Air Terminal Device √ √ √

Dual Duct Terminal Device √ √ √

Zone Control √ √ √

Cooler Circuit √ √

Cooling Generator √ √

Refrigeration Compressor √ √

Chiller √ √

Multi-Chiller √ √

Pump √ √

Hydronic Network (1) √ √

Heater Circuit (2) √ √

Heating Generator √ √

Boiler √ √

Multi-Boiler √ √

Electricity Meter √

Gas Meter √

Water Meter √

Building Climate Conditions √ (1) Hydronic network: Chilled water, hot water or temperate water (2) Heater circuit : Oil heater, gas heater or electrical element

Figure 5: The structure of various devices within a system

Central Chiller plants & Cooling Equipments

• Cooler circuit

• Cooling generator

• Chiller• Cooling

tower• Multi

chillerEX: 1 Chiller, 2 independant Refrigerant circuits, 1 cooling tower

Central Heating plants & Heating Equipments

• Heater circuit

• Heating generator

• Boiler • Multiboiler



5 DABO Reports DABO produces four types of report to assist the user in assessing the performance of the building, its systems and devices. These reports primarily display the data in a graphical format and have been designed to allow the most efficient review and use of the information.

Fault Detection and Diagnosis Reports

These reports display data generated by the various fault detection functions (these are defined as «services» in the software). Data are shown in a colour-coded table.

Commissioning Reports (COMM Reports)

These reports display data generated by the various commissioning functions or «services» or data from the building. Data are also shown in a colour-coded table. These reports can be customised by the user for additional statistical analysis.

Points Reporter

These reports display data from building points selected by the user. Data can be shown as a line chart or a table. These reports can be requested from the FDD report, from the commissioning report, or from the "Tools" menu.

Fault Management Reports

This type of report displays, by device type, confirmation of a fault repair.

5.1 Fault Detection and Diagnosis Reports (FDD Reports)

Figure 8 shows the DABO FDD Report (no. 1) together with the list of symptoms detected for a single cell (no. 2), and for a single symptom, the related individual graph (no. 3).

The FDD report displays the number of detected symptoms of a failure by date and hour-by-hour for all air handling, air terminal device of control zone in a building. It shows also the operation mode and provides access to detailed reports (available by clicking on the + button).

Figure 8. Example of Fault Detection and Diagnosis Reports

5.2 Point Reporter (Graph and Data) The Points Reporter displays raw data and the results of simple computations in graphic or table format for the relevant data collected or computed during the 4 hours before and 4 hours after a symptom was detected. The data displayed are sorted by date and time. Using the “Save Data” option, raw data can be extracted to a separate file for use in other applications (for example: Microsoft Excel). Figure 9, on the following page is an illustration of a point reporter report.



Figure 9. Illustration of a Point Reporter Report

5.3 Commissioning Reports (COMM Reports) The Commissioning Reports display performance values of devices on an hourly basis or summarised for an entire day, week, or month. Users can adapt the report by filtering devices by system device, system name, floor, orientation, family, and type. This allows users to observe time-based device performance variations.

This type of report is used, for example, to manually detect non-optimum set points, to identify devices with insufficient capacity, to identify systems with non-optimum sequences, to report equipment performance levels, or to report comfort performance. The COMM Reports are available for all DABO devices.

Figure 10 displays performance indices for the supply temperature (PI_T) and supply temperature set point (PI_TSP) as well as the average (AVG_CZ_PI_C) and maximum (MAX_CZ_PI_C) zone connected cooling loads for two air-handling units. This report is used to

detect if a temperature reset control strategy, which adjusts the supply air temperature set point as a function of the actual cooling load, performs well.

Note that the performance index for the supply temperature (PI_T) of the two air-handling units varies over the course of the day, indicating that a temperature reset strategy is being used.

For the M2 Laboratories unit, PI_T displays the same variation and has approximately the same magnitude as the average zone cooling load (AVG_CZ_PI_C). This is the expected behavior when the reset strategy is functioning correctly.

On M3, the strategy is probably not aggressive enough since while the cooling load is quite low (~7%), the supply air temperature index is near the middle of its range (~38%). This indicates that the supply air temperature may be too low for the given load and could generate a reheat load.

Figure 10. Typical Commissioning Report for 3 Air Handling Units

Figure 11 shows a daily VAV box performance report. Performance indices identified by the letter ‘a’ consist of the VAV box basic monitored control points (supply air flow ≈ 43 l/s, supply airflow set point ≈ 45 l/s, ATD supply air temperature ≈ 18°C and heating coil valve command ≈ 0%). Those identified by the letter ‘b’ are performance indices for the air terminal device airflow ≈ 30%, airflow set point ≈ - 1%, cooling load ≈ 16%, damper ≈ 43.8% and heating load = 0% , while those identified by the letter ‘c’ display information from the zone and AHU (AHU supply air temperature ≈ 20°C, supply fan command ‘1= on’ and zone air temperature = 23°C.

Data are shown in grey to indicate that the AHU that supplies air to the zone is not operating during these hours. The data indicate that the VAV-reheat box is supplying 30% of its design airflow, the damper position is approximately 43% open, the reheat coil valve is closed, the cooling load is close to 17%, and the heating load is at 0%. The data also indicate the ATD supply air temperature is slightly higher than the AHU supply air temperature. This could be due to a small heating valve leak, or could indicate the need to calibrate one or both of the sensors. It could also be due to normal heat gain as the air travels through the air distribution system.



Figure 11: Typical report for Air Terminal Devices – Commissioning Report

Figure 12 shows the heating network performance report for one day. The performance indices are the average connected heating load (AVG_PI_H ≈ 22%), maximum heating load (MAX_PI_H = 100%), supply water pressure N_SIP ≈ 157 pa, supply water pressure set point N_SISP ≈ 140 pa, supply water temperature N_SIT ≈ 76°C, supply water temperature set point N_SITSP ≈ 53°C, and the temperature control valve N_V = 100% bypass.

In this case the heating hydronic network operates at around 6% of its full capacity (PI_DEV ≈ 6%), temperature and pressure indices are over their design normal range of operation (PI_T and PI_P are over 100%), and the temperature and pressure are significantly higher than their respective set points, making the temperature and pressure set point indices very positive (PI_TSP and PI_PSP = 12 and 48%).

Recall that the set point indices are normally approximately equal to zero when the temperature or pressure is maintained at its set point value. Since the valve command is 100% in bypass and there is a heating load on the circuit, this report indicates that the valve and actuator should be inspected to ensure there is no leakage and/or problem with the actuator linkage.

Figure 12. NetNode Commissioning Report

5.4 Fault Management Report This report is used to manage information concerning confirmed faults in the building’s operation. In this report the user can review data for a specific device or for all devices of the same type.

The following information is reviewed in a full report (a partial report is provided in Figure 13):

• System name, • Failure number, • Failure description, • Failure start time, • Confirmation date, • Failure priority, • Primary benefit, • Secondary benefit, • Impact on energy savings, • Cost, • Responsible Operator, • Confirmed failure, • Operator's comments,



• Confirmation of repaired failure.

Figure 13. Typical Fault Management Report for an Air Handling Unit

6 Summary

Monitoring the energy performance of buildings is a growing priority for building owners and operators. This is not easy due to the enormous amounts of data collected by BEMS, and the extensive analysis required to evaluate the data. A comprehensive on-going commissioning process will help ensure that buildings operate at their optimized energy performance levels, while maintaining comfort conditions for occupants. DABO performs data analysis tasks required to implement an on-going commissioning process and provides reports that allow the

building operator and/or energy manager to quickly assess the overall performance of the building.

DABO is a tool in constant evolution. Current research efforts are concerned with the development of an energy predictor, new fault detection and diagnosis modules for heating and cooling networks, and new analyses of BEMS data to enhance the commissioning process.

Demonstration projects are currently in the investigation and implementation stages; however early results show that DABO helps circumvent commissioning barriers by automating some parts of the process, which has reduced the cost of commissioning. Developing a detailed systematic automated approach has improved the quality assurance process and the overall performance of the buildings. Furthermore, automating this essentially manual process has allowed its application on an on-going basis. Details from the demonstration projects results will be provided in future publications that are anticipated in the next 2 years.

7 Acknowledgements This work has been funded by the Panel on Energy Research and Development (PERD), a Canadian government program.

8 References

Choinière D. 2001. Un agent de détection et diagnostic de fautes pour les bâtiments. Congrès de l’Association québécoise pour la maîtrise de l’énergie. Quebec City, Quebec, Canada.

IEA. 2001a. International Energy Agency. Annex 40: Commissioning of Buildings and HVAC Systems for Improved Energy Performance. http://www.commissioning-hvac.org.

IEA. 2001b. International Energy Agency. Annex 34: Computer-Aided Evaluation of HVAC System Performance. Final Report. Editors Arthur Dexter and Jouko Pakanen. International Energy Agency.

D.Choiniere, and MCorsi. 2003. A BEMS assisted commissioning tool to improve the energy performance of HVAC systems. Proceedings of ICEBO 2003. Berkely, CA.

Jean Gilles. 2004. A climate change solution; “Intelligent Building Operating Technologies”. http://cetc-varennes.nrcan.gc.ca

dabotm: a bems assisted on-going commissioning tool · data analysis using artificial intelligence...

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