Open Journal Systems

Enhancing Non-intrusive Occupant Load Monitoring through Occupancy Matrix

Hamed Nabizadeh Rafsanjani


It has been universally accepted that energy consumption in commercial buildings is highly related to occupant behaviors. Improving occupants’ energy-use behaviors is regarded as the most cost-effective approach to enhance overall energy saving in commercial built environments. However, effective behavior intervention pursuits rely on the availability of occupant-specific energy-use information, which is extremely expensive to capture with existing technologies. In this context, the author’s previous studies proposed the non-intrusive occupant load monitoring (NIOLM) approach that captures individual occupants’ energy-consuming information at their entry and departure events in an economically feasible manner. The NIOLM assigns energy-load variations (ev) of a building to individual occupants and relies on two variables: Time delay intervals and magnitudes of ev. This paper extends the existing NIOLM concept with the inclusion of a new variable, the occupancy matrix which manifests the information of present occupants at the moment of ev. An experiment has been conducted in an office space to validate the feasibility and accuracy of the proposed approach. Outcomes of this research could be a great help for studies on occupant energy-use behaviors intervention and simulation.



Occupant energy-use behavior; Non-intrusive load monitoring; Load disaggregation, Wi-Fi networks, Commercial buildings.

Full Text:



U.S. Energy Information Administration, Annual Energy Review; 2014.

International Energy Agency, Key World Energy Statistics; 2014.

Chen J, Ahn C. Assessing Occupants’ Energy Load Variation through Existing Wireless Network Infrastructure in Commercial and Educational Buildings. Energy Build 2014;82:540-9.

Rafsanjani HN. Factors Influencing the Energy Consumption of Residential Buildings: A Review. Construction Research Congress 2016, American Society of Civil Engineers; 2016. p. 1133-42. Available from: abs/10.1061/9780784479827.114. [Last accessed on 2016 May 25].

Rafsanjani HN, Ahn CR, Alahmad M. A Review of Approaches for Sensing, Understanding, and Improving Occupancy-related Energy-use Behaviors in Commercial Buildings. Energies 2015;8:10996-1029.

Ghahramani A, Jazizadeh F, Becerik-Gerber B. A Knowledge Based Approach for Selecting Energy-aware and Comfort-driven HVAC Temperature Set Points. Energy Build 2014;85:536-48.

Ghahramani A, Zhang K, Dutta K, Yang Z, Becerik-Gerber B. Energy Savings from Temperature Setpoints and Deadband: Quantifying the Influence of Building and System Properties on Savings. Appl Energy 2016;165:930-42.

Rafsanjani HN, Ahn C, Eskridge K. Understanding the Recurring Patterns of Occupants’ Energy-use Behaviors at Entry and Departure Events in Office Buildings. Build Environ 2018;136:77-87.

Ghahramani A, Castro G, Karvigh SA, Becerik-Gerber B. Towards Unsupervised Learning of Thermal Comfort using Infrared Thermography. Appl Energy 2018;211:41-9.

Khosrowpour A, Taylor JE. One Size does not Fit All: Eco-feedback Programs Require Tailored Feedback. Sustainable Human– building Ecosystem, American Society of Civil Engineers; 2015. p. 36-43. Available from: abs/10.1061/9780784479681.004. [Last accessed on 2016 Nov 21].

McKenney K, Guernsey M, Ponoum R, Rosenfeld J. Commercial Miscellaneous Electric Loads: Energy Consumption Characterization and Savings Potential in 2008 by Building Type, Final Report by TIAX LLC; 2010.

Rafsanjani HN, Ahn C, Alahmad M. Development of Non-intrusive Occupant Load Monitoring (NIOLM) in Commercial Buildings: Assessing Occupants’ Energy-use Behavior at Entry and Departure Events. First International Symposium Sustainable Human-building Ecosystem ISSHBE. Pittsburgh, PA: American Society of Civil Engineers; 2015. p. 44-53.

Rafsanjani HN, Ahn C, Chen J. Importance of Time Delay Interval and Energy Load Variation for Non-intrusively Finding Occupants’ Energy-use Information in Commercial Buildings. Seoul, Korea: International Conference Sustainable Building Asia; 2016.

Rafsanjani HN, Ahn C. Linking Building Energy-Load Variations with Occupants’ Energy-Use Behaviors in Commercial Buildings: Non-Intrusive Occupant Load Monitoring (NIOLM). Procedia Eng 2016;145:532-9.

Rafsanjani HN, Ahn CR, Chen J. Linking Building Energy Consumption with Occupants’ Energy-consuming Behaviors in Commercial Buildings: Non-intrusive Occupant Load Monitoring (NIOLM). Energy Build 2018;172:317-27.

Rafsanjani HN. Feature Identification for Non-intrusively Extracting Occupant Energy-use Information in Office Buildings. J Archit Environ Struct Eng Res 2018;1:16-24.

Zoha A, Gluhak A, Imran MA, Rajasegarar S. Non-intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey. Sensors 2012;12:16838-66.

Gulbinas R, Taylor JE. Effects of Real-time Eco-feedback and Organizational Network Dynamics on Energy Efficient Behavior in Commercial Buildings. Energy Build 2014;84:493-500.

Zeifman M, Roth K. Nonintrusive Appliance Load Monitoring: Review and Outlook. IEEE Trans Consum Electron 2011;57:76-84.

Hart GW. Nonintrusive Appliance Load Monitoring. Proc IEEE 1992;80:1870-91.

Norford LK, Leeb SB. Non-intrusive Electrical Load Monitoring in Commercial Buildings Based on Steady-state and Transient Load-detection Algorithms. Energy Build 1996;24:51-64.

Batra N, Parson O, Berges M, Singh A, Rogers A. A Comparison of Non-intrusive Load Monitoring Methods for Commercial and Residential Buildings. New York: Cornell University; 2014.

Khosrowpour A, Gulbinas R, Taylor JE. Occupant Workstation Level Energy-use Prediction in Commercial Buildings: Developing and Assessing a New Method to Enable Targeted Energy Efficiency Programs. Energy Build 2016;127:1133-45.

Gulbinas R, Khosrowpour A, Taylor J. Segmentation and Classification of Commercial Building Occupants by Energy-use Efficiency and Predictability. IEEE Trans Smart Grid 2015;6:1.

Measurement Science Roadmap for Net-zero Energy Buildings Workshop Summary Report; 2010.

Allcott H. Social Norms and Energy Conservation. J Public Econ 2011;95:1082-95.

The Effectiveness of Energy Feedback for Conservation and Peak Demand: A Literature Review, (n.d.). Available from: http:// [Last accessed on 2016 Oct 19].

Carrico AR, Riemer M. Motivating Energy Conservation in the Workplace: An Evaluation of the Use of Group-level Feedback and Peer Education. J Environ Psychol 2011;31:1-13.

Allcott H, Rogers T. How Long do Treatment Effects Last? Persistence and Durability of a Descriptive Norms Intervention’s Effect on Energy Conservation. HKS Faculty Research Working Papers; 2012.

Peschiera G, Taylor JE, Siegel JA. Response–relapse Patterns of Building Occupant Electricity Consumption following Exposure to Personal, Contextualized and Occupant Peer Network Utilization Data. Energy Build 2010;42:1329-36.

Jain RK, Taylor JE, Peschiera G. Assessing Eco-feedback Interface Usage and Design to Drive Energy Efficiency in Buildings. Energy Build 2012;48:8-17.

Bekker MJ, Cumming TD, Osborne NK, Bruining AM, McClean JI, Leland LS, et al. Encouraging Electricity Savings in a University Residential Hall through a Combination of Feedback, Visual Prompts, and Incentives. J Appl Behav Anal 2010;43:327-31.

Coleman MJ, Irvine KN, Lemon M, Shao L. Promoting Behaviour Change through Personalized Energy Feedback in Offices. Build Res Inf 2013;41:637-51.

Murtagh N, Nati M, Headley WR, Gatersleben B, Gluhak A, Imran MA, et al. Individual Energy Use and Feedback in an Office Setting: A Field Trial. Energy Policy 2013;62:717-28.

Gulbinas R, Jain RK, Taylor JE. BizWatts: A Modular Socio-technical Energy Management System for Empowering Commercial Building Occupants to Conserve Energy. Appl Energy 2014;136:1076-84.

Yun R, Lasternas B, Aziz A, Loftness V, Scupelli P, Rowe A, et al. Toward the Design of a Dashboard to Promote Environmentally Sustainable Behavior among Office Workers. In: Berkovsky S, Freyne J, editors. Persuasive Technology. Berlin Heidelberg: Springer; 2013. p. 246-52.

Staats H, van Leeuwen E, Wit A. A longitudinal study of informational interventions to save energy in an office building. J Appl Behav Anal 2000;33:101-4.

(14 Abstract Views, 12 PDF Downloads)


  • There are currently no refbacks.

Copyright (c) 2019 Hamed Nabizadeh Rafsanjani

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.