Mihai, Andreea (2014) Calibration of a Building Energy Model Using Measured Data for a Research Center. Masters thesis, Concordia University.
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Abstract
This thesis proposes an evidence-based bottom-up methodology to calibrate a building energy model starting at the zone level, and finishing with the whole building level. The calibration is based as much as possible on measurements taken from the existing Building Automation System (BAS). This study presents the calibration at the zone and air handling unit level.
First a literature review is presented, followed by the evidence-based bottom-up methodology. Next, the case study building is described, along with the extraction and analysis of the monitored data. Then the building model is created and calibrated at the zone level based on the supply air flow rate to each zone. The calibration at the air handling unit level is based on: i) the supply air flow rate leaving the air handling unit; ii) the supply air temperature and iii) the cooling coil load. The evaluation of the calibration quality is proposed to be performed in three stages: i) graphical representation; ii) statistical indices (RMSE, CV-RMSE, NMBE); and iii) paired difference statistical hypothesis testing.
A sensitivity analysis is performed and it is found that the energy model is not sensitive to changes in the building envelope parameters, but rather to variations in internal loads.
Two approaches for representing the schedules of internal loads are compared and the proposed approach, where the internal loads are derived from measured cooling load in each zone, is recommended.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering |
|---|---|
| Item Type: | Thesis (Masters) |
| Authors: | Mihai, Andreea |
| Institution: | Concordia University |
| Degree Name: | M.A. Sc. |
| Program: | Building Engineering |
| Date: | 31 January 2014 |
| Thesis Supervisor(s): | Zmeureanu, Radu |
| Keywords: | building energy performance simulation, calibration, measured data, statistical indices, paired hypothesis testing, bottom-up approach, evidence-based approach, sensitivity analysis, internal loads |
| ID Code: | 978322 |
| Deposited By: | ANDREEA MIHAI |
| Deposited On: | 09 Jun 2014 13:51 |
| Last Modified: | 18 Jan 2018 17:46 |
References:
Abushakra, B., Sreshthaputra, A., Haberl, J. and Claridge, D. (2001). Compilation of Diversity Factors and Schedules for Energy and Cooling Load Calculations-Final Report. submitted to ASHRAE under Research Project 1093-RP. Energy Systems Lab Report No. ESL-TR-01-04.ASHRAE (2001). Fundamentals Handbook. American Society of Heating, Refrigerating and Air Conditioning Engineers Inc, Atlanta, Georgia.
ASHRAE (2002). ASHRAE Guideline 14. Measurement of Energy and Demand Savings, American Society of Heating, Ventilating, and Air Conditioning Engineers Inc. , Atlanta, Georgia.
Baumann, O. (2004). Operation diagnostics-use of operation patterns to verify and optimize building and system operation. Proceedings of International Conference for Enhanced Building Operations (ICEBO), Paris, France.
Bazjanac, V. (2005). Model based cost and energy performance estimation during schematic design. Proceedings of 22nd Conference on Information Technology in Construction, Dresden, Germany.
Bertagnolio, S., Masy, G., Andre, P. and Lebrun, J. (2008). Building and HVAC System simulation with the help of an engineering equation solver. Proceedings of the 3rd National conference of the International Building Performance Simulation Association (IBPSA), USA, Berkeley, CA.
Bertagnolio, S., Randaxhe, F. and Lemort, V. (2012). Evidence-based calibration of a building energy simulation model: Application to an office building in Belgium. Proceedings of the 12th International Conference for Enhanced Building Operations, Manchester, UK.
Bordass, B., Leaman, A. and Ruyssevelt, P. (2001). Assessing building performance in use 5: conclusions and implications. Building Research & Information, vol 29, (2): 144-157.
Bronson, D. J., Hinchey, S. B., Haberl, J. S. and O'Neal, D. L. (1992). Procedure for calibrating the DOE-2 simulation program to non-weather-dependent measured loads. Proceedings of the ASHRAE Winter Meeting, Anaheim, CA, USA, .
Chou, S. K., Chang, W. L. and Wong, Y. W. (1993). Effects of multi-parameter changes on energy use of large buildings. International Journal of Energy Research, vol 17, (9): 885-903.
Claridge, D. E., Bensouda, N., Lee, S. U., Wei, G., Heinemeier, K. and Liu, M. (2003). Manual of procedures for calibrating simulations of building systems, submitted to the California Energy Comission Public Interest Energy Research Program
Clarke, J. A., Strachan, P. A. and Pernot, C. (1993). An approach to the calibration of building energy simulation models. ASHRAE Transactions, vol 99: 917-917.
Corson, G. (1992). Input-output sensitivity of building energy simulations. Proceedings of ASHRAE Winter Meeting, Anaheim, CA, USA
Department of Energy (DOE) (2006). eQuest, the QUick Energy Simulation Tool v 3.65. Retrieved from http://www.doe2.com/equest/, February 2014.
Department of Energy (DOE) (2013). EnergyPlus v 8.1, University of Illinois and Ernest Orlando Lawrence Berkley National Laboratory, USA. Retrieved from http://apps1.eere.energy.gov/buildings/energyplus/, October 2012.
Department of Energy (DOE). (2013). Weather file aquired from http://doe2.com/index_wth.html. Retrieved 11 November, 2013.
Diamond, S. C., Cappiello, C. C. and Hunn, B. D. (1986). DOE-2 Verification project. Phase I. Final report, Los Alamos National Lab., NM (USA).
Diamond, S. C., Hunn, B. D. and Cappiello, C. C. (1981). DOE-2 Verification Project. Phase I. Interim report, Los Alamos Scientific Lab., NM (USA).
Diamond, S. C., Hunn, B. D. and Cappiello, C. C. (1985). Computer modeling: the DOE-2 validation. ASHRAE journal, vol 27, (11): 25-32.
DOE (2008). M&V Guidelines: Measurement and Verification for Federal Energy Projects (FEMP). Federal Energy Management Program.
Eley, C., Goodrich, K., Arent, J., Higa, R. and Rauss, D. (2011). ML-11-029 Rethinking Percent Savings—The Problem with Percent Savings and zEPI: The New Scale for a Net-Zero Energy Future. ASHRAE Transactions, vol 117, (2): 787.
Guiterman, T. and Krarti, M. (2011). ML-11-C046 Analysis of Measurement and Verification Methods for Energy Retrofits Applied to Residential Buildings. ASHRAE Transactions, vol 117, (2): 382.
Haberl, J. S. and Abbas, M. (1998). Development of graphical indices for viewing building energy data: Part I. Journal of Solar Energy Engineering - Transactions of The ASME, vol 120, (3): 156-161.
Haberl, J. S. and Bou-Saada, T. E. (1998). Procedures for calibrating hourly simulation models to measured building energy and environmental data. Journal of Solar Energy Engineering, vol 120, (3): 193-204.
Heidell, J. A. and Taylor, Z. T. (1985). Comparison of empirically measured end-use metered data with DOE 2. 1 simulation. Proceedings of the International Building Performance Simulation Association (IBPSA) Conference, Seattle, WA, USA, Pacific Northwest Lab., Richland, WA (USA).
IPMVP-Committee (2002). International Performance Measurement & Verification Protocol: Concepts and Options for Determining Energy and Water Savings.
Kaplan, M., Caner, P. and Vincent, G. W. (1992). Guidelines for energy simulation of commercial buildings. Proceedings from the ACEEE 1992 Summer study on Energy Efficiency in buildings, Pacific Grove, California.
Kaplan, M. B., McFerran, J., Jansen, J. and Pratt, R. (1990). Reconciliation of a DOE2.1C model with monitored end-use data for a small office building. ASHRAE Transactions, vol 96, (1): 981-993.
Katipamula, S. and Haberl, J. S. (1991). Methodology to identify diurnal load shapes for non-weather dependent electric end-uses. Proceedings of the second ASME-JSES-JSME International Solar Energy Conference Reno, Nevada.
Kelsey, J. and Pearson, D. (2011). ML-11-C045 Updated Procedures for Commercial Building Energy Audits. ASHRAE Transactions, vol 117, (2): 374.
Lam, J. C. and Hui, S. (1996). Sensitivity analysis of energy performance of office buildings. Building and Environment, vol 31, (1): 27-39.
Liu, G. and Liu, M. (2011). A rapid calibration procedure and case study for simplified simulation models of commonly used HVAC systems. Building and Environment, vol 46, (2): 409-420.
Liu, S. and Henze, G. P. (2005). Calibration of building models for supervisory control of commercial buildings. Proceedings of the 9th International Building Performance Simulation Association (IBPSA) Conference, Montreal, Canada.
Love, J. A. and Kandil, A.-E. (2013). Signature analysis calibration of a school energy model using hourly data Journal of Building Performance Simulation, vol ahead-of-print: 1-20.
Lunneberg, T. A. (1999). Improving simulation accuracy through the use of short-term electrical end-use monitoring. Proceedings of the International Building Performance Simulation Association (IBPSA) Conference, Kyoto, Japan.
Mayer, T., Sebold, F., Fields, A., Ramirez, R., Souza, B. and Ciminelli, M. (2003). DrCEUS: Energy and demand usage from commercial on-site survey data. Proceedings of the International Energy program Evaluation Conference, Seattle, WA.
Millette, J., Sansregret, S. and Daoud, A. (2011). SIMEB: simplified interface to DOE2 and EnergyPlus - a user's perspective - case study of an existing building. Proceeding of the 12th International Building Performance Simulation Asssociation (IBPSA) Conference, Sydney, Australia.
Monfet, D., Zmeureanu, R., Charneux, R. and Lemire, N. (2009). Calibration of a Building Energy Model Using Measured Data. ASHRAE Transactions, vol 115, (1): 348-359.
Mottillo, M. (2001). Better Inputs for Better Outputs-Sensitivity Analysis of Energy Simulation by Building Type. ASHRAE Transactions, vol 107, (2): 722-732.
N.R.C. (1997). Model National Energy Code for Buildings. Natural Resources Canada, Ottawa, Ontario, Canada.
N.R.C. (2011). National Energy Code of Canada for Buildings. Natural Resources Canada, Ottawa, Ontario, Canada.
N.R.C. (2013). CAN-QUEST v 1.5, Ottawa, Ontario, Canada. Retrieved from.
Pan, Y., Huang, Z. and Wu, G. (2007). Calibrated building energy simulation and its application in a high-rise commercial building in Shanghai. Energy and Buildings, vol 39, (6): 651-657.
Pedrini, A., Westphal, F. S. and Lamberts, R. (2002). A methodology for building energy modelling and calibration in warm climates. Building and Environment, vol 37, (8): 903-912.
Perez-Lombard, L., Ortiz, J. and Pout, C. (2008). A review on buildings energy consumption information. Energy and buildings, vol 40, (3): 394-398.
Plourde, J. (2011). Making the Case For Energy Metering. ASHRAE Journal, vol 53, (4): 20.
Raftery, P., Keane, M. and Costa, A. (2009). Calibration of a detailed simulation model to energy monitoring system data: a methodology and case study. Proceedings of the 11th International Building Performance Simulation Association (IBPSA) Conference, Glasgow, Scotland, UK.
Raftery, P., Keane, M. and Costa, A. (2011). Calibrating whole building energy models: Detailed case study using hourly measured data. Energy and Buildings, vol 43, (12): 3666-3679.
Raftery, P., Keane, M. and O’Donnell, J. (2011). Calibrating whole building energy models: An evidence-based methodology. Energy and Buildings, vol 43, (9): 2356-2364.
Reddy, T. A. (2006). Literature review on calibration of building energy simulation programs: uses, problems, procedures, uncertainty, and tools. ASHRAE Transactions, vol 112, (2): 226-240.
Reddy, T. A. (2011). Applied data analysis and modeling for energy engineers and scientists. Springer, New York, USA.
Reddy, T. A., Maor, I. and Jian, S. (2006). Procedures for reconciling computer-calculated results with measured energy data. ASHRAE Research Project 1051-RP.
Reddy, T. A., Maor, I. and Panjapornpon, C. (2007). Calibrating detailed building energy simulation programs with measured data—part II: application to three case study office buildings (RP-1051). HVAC & R Research, vol 13, (2): 243-265.
Sonderegger, R., Avina, J., Kennedy, J. and Bailey, P. (2001). Deriving loadshapes from utility bills through scaled simulation. Kansas City, MI.
Sornay, J. (1985). Recent developments of building energy simulation tools in Europe. Proceedings of the International Building Performance Simulation Association (IBPSA) Conference, Seattle, WA.
Stein, J. (1997). Calibrated Simulation: An Improved Method for Analyzing Building Energy Use. Boulder, CO, September.
Troncoso, R. (1997). A hybrid monitoring-modeling procedure for analyzing the performance of large central chilling plants. Proceedings of International Building Performance Simulation Association (IBPSA) Conference, Prague, Czech Republic.
Waltz, J. P. (2000). Computerized building energy simulation handbook. CRC Press, Lilburn, Georgia.
Weather Analytics (2013). Weather file acquired from http://www.weatheranalytics.com. Retrieved 15 April, 2013.
Yoon, J.-H. and Lee, E.-J. (1999). Calibration procedure of energy performance simulation model for a commercial building. Proceedings from the International Building Performance Simulation Association (IBPSA) Conference, Kyoto, Japan.
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