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International Conference on Principles and Practice of Constraint Programming

CP 2016: Principles and Practice of Constraint Programming pp 683–700Cite as

Online HVAC-Aware Occupancy Scheduling with Adaptive Temperature Control

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9892))

Abstract

Heating, ventilation and air-conditioning (HVAC) is the largest consumer of electricity in commercial buildings. Consumption is impacted by group activities (e.g. meetings, lectures) and can be reduced by scheduling these activities at times and locations that minimize HVAC utilization. However, this needs to preserve occupants’ thermal comfort and be responsive to dynamic information such as new activity requests and weather updates. This paper presents an online HVAC-aware occupancy scheduling approach which models and solves a joint HVAC control and occupancy scheduling problem. Our online algorithm greedily commits to the best schedule for the latest activity requests and notifies the occupants immediately, but revises the entire future HVAC control strategy each time it considers new requests and weather updates. In our experiments, the quality of the solution obtained by this approach is within 1 % of that of the clairvoyant solution. We incorporate adaptive comfort temperature control into our model, encouraging energy saving behaviors by allowing the occupants to indicate their thermal comfort flexibility. In our experiments, the integration of adaptive temperature control further generates up to 12 % of energy savings when a reasonable thermal comfort flexibility is provided.

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Notes

  1. 1.

    Both Lim et al. [21, 22] and our experiments use a more complex state vector which not only includes the zone temperatures \(T_{l,k}\) but also the temperature of the interior walls. For readability reasons, we abstract from these extra state variables in our exposition above.

References

  1. Aileen, E.: The potential energy savings through the use of adaptive comfort cooling setpoints in fully air conditioned australian office buildings, a simulation study. Equilibr. J. (2010)

    Google Scholar 

  2. Babonneau, F., Vial, J.P., Apparigliato, R.: Uncertainty and Environmental Decision Making. International Series in Operations Research and Management Science. Springer, Heidelberg (2009)

    Google Scholar 

  3. Ben-Tal, A., Nemirovski, A.: Robust convex optimization. Math. Oper. Res. 23(4), 769–805 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  4. Ben-Tal, A., Nemirovski, A.: Robust solutions to uncertain linear programs. OR Lett. 25, 1–13 (1999)

    MathSciNet  MATH  Google Scholar 

  5. Chai, B., Costa, A., Ahipasaoglu, S.D., Huang, S., Yuen, C., Yang, Z.: Minimizing commercial building cost in smart grid: an optimal meeting scheduling approach. In: 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm), pp. 764–769. IEEE (2014)

    Google Scholar 

  6. Chew, B., Kazi, S., Amiri, A.: Adaptive thermal comfort model for air-conditioned lecture halls in Malaysia. World Acad. Sci. Eng. Technol. Int. J. Civ. Environ. Struct. Constr. Archit. Eng. 9(2), 150–157 (2015)

    Google Scholar 

  7. De Dear, R.J., Brager, G.S., Reardon, J., Nicol, F., et al.: Developing an adaptive model of thermal comfort and preference/discussion. ASHRAE Trans. 104, 145 (1998)

    Google Scholar 

  8. Dupont, C., Giuliani, G., Hermenier, F., Schulze, T., Somov, A.: An energy aware framework for virtual machine placement in cloud federated data centres. In: 2012 Third International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet (e-Energy), pp. 1–10. IEEE (2012)

    Google Scholar 

  9. EIA: Us eia-department of energy, cbecs detailed tables (2003). http://www.eia.gov/consumption/commercial/

  10. El Ghaoui, L., Lebret, H.: Robust solutions to least-squares problems with uncertain data. SIAM J. Matrix Anal. Appl. 18, 1035–1064 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  11. Department of Energy: Buildings energy data book. In: Buildings Energy Data Book. Department of Energy, United States (2011). http://buildingsdatabook.eren.doe.gov/ChapterIntro1.aspx

  12. Gouda, M., Danaher, S., Underwood, C.: Low-order model for the simulation of a building and its heating system. Build. Serv. Eng. Res. Technol. 21(3), 199–208 (2000)

    Article  Google Scholar 

  13. Gouda, M., Danaher, S., Underwood, C.: Building thermal model reduction using nonlinear constrained optimization. Build. Environ. 37(12), 1255–1265 (2002)

    Article  Google Scholar 

  14. Goyal, S., Barooah, P.: A method for model-reduction of non-linear thermal dynamics of multi-zone buildings. Energy Build. 47, 332–340 (2012)

    Article  Google Scholar 

  15. Goyal, S., Ingley, H.A., Barooah, P.: Occupancy-based zone-climate control for energy-efficient buildings: complexity vs. performance. Appl. Energy 106, 209–221 (2013)

    Article  Google Scholar 

  16. Hijazi, H., Bonami, P., Ouorou, A.: Robust delay-constrained routing in telecommunications. Ann. Oper. Res. 206(1), 163–181 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  17. Ifrim, G., O’Sullivan, B., Simonis, H.: Properties of energy-price forecasts for scheduling. In: Milano, M. (ed.) CP 2012. LNCS, vol. 7514, pp. 957–972. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  18. Klein, L., Kwak, J.Y., Kavulya, G., Jazizadeh, F., Becerik-Gerber, B., Varakantham, P., Tambe, M.: Coordinating occupant behavior for building energy and comfort management using multi-agent systems. Autom. Constr. 22, 525–536 (2012)

    Article  Google Scholar 

  19. Kwak, J.y., Kar, D., Haskell, W., Varakantham, P., Tambe, M.: Building thinc: user incentivization and meeting rescheduling for energy savings. In: Proceedings of the 13th International Conference on Autonomous Agents and Multi-agent Systems, pp. 925–932 (2014)

    Google Scholar 

  20. Kwak, J.y., Varakantham, P., Maheswaran, R., Chang, Y.H., Tambe, M., Becerik-Gerber, B., Wood, W.: Tesla: An energy-saving agent that leverages schedule flexibility. In: Proceedings of the 12th International Conference on Autonomous Agents and Multi-agent Systems, pp. 965–972 (2013)

    Google Scholar 

  21. Lim, B.P., Van Den Briel, M., Thiébaux, S., Backhaus, S., Bent, R.: Hvac-aware occupancy scheduling. In: AAAI, pp. 4249–4250 (2015)

    Google Scholar 

  22. Lim, B.P., van den Briel, M., Thiébaux, S., Bent, R., Backhaus, S.: Large neighborhood search for energy aware meeting scheduling in smart buildings. In: Michel, L. (ed.) CPAIOR 2015. LNCS, vol. 9075, pp. 240–254. Springer, Heidelberg (2015)

    Google Scholar 

  23. Majumdar, A., Zhang, Z., Albonesi, D.: Characterizing the benefits and limitations of smart building meeting room scheduling. In: Proceedings of the 7th International Conference on Cyber-Physical Systems (2016)

    Google Scholar 

  24. Majumdar, A., Albonesi, D.H., Bose, P.: Energy-aware meeting scheduling algorithms for smart buildings. In: Proceedings of the 4th ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pp. 161–168. ACM (2012)

    Google Scholar 

  25. Ono, M., Graybill, W., Williams, B.C.: Risk-sensitive plan execution for connected sustainable home. In: Proceedings of the 4th ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pp. 45–52. ACM (2012)

    Google Scholar 

  26. Pan, D., Wang, D., Cao, J., Peng, Y., Peng, X.: Minimizing building electricity costs in a dynamic power market: algorithms and impact on energy conservation. In: 2013 IEEE 34th Real-Time Systems Symposium (RTSS), pp. 107–117. IEEE (2013)

    Google Scholar 

  27. Pan, D., Yuan, Y., Wang, D., Xu, X., Peng, Y., Peng, X., Wan, P.J.: Thermal inertia: towards an energy conservation room management system. In: Proceedings of the 31st IEEE International Conference on Computer Communications, pp. 2606–2610. IEEE (2012)

    Google Scholar 

  28. Pitt, S. (ed.): Baseline Energy Consumption and Greenhouse Gas Emissions in Commercial Buildings in Australia Part 1 Report. Department of Climate Change and Energy Efficiency, Australia (2012). http://www.industry.gov.au/Energy/EnergyEfficiency/Non-residentialBuildings/Documents/CBBS-Part-1.pdf

  29. Scott, P., Thiébaux, S., van den Briel, M., Van Hentenryck, P.: Residential demand response under uncertainty. In: Schulte, C. (ed.) CP 2013. LNCS, vol. 8124, pp. 645–660. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  30. Shaw, P.: Using constraint programming and local search methods to solve vehicle routing problems. In: Maher, M.J., Puget, J.-F. (eds.) CP 1998. LNCS, vol. 1520, pp. 417–431. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  31. Ward, J., Wall, J., White, S.: Automate and motivate: behaviour-reliant building technology solutions for reducing greenhouse gas emissions. Archit. Sci. Rev. 53(1), 87–94 (2010)

    Article  Google Scholar 

  32. Yang, R., Wang, L.: Development of multi-agent system for building energy and comfort management based on occupant behaviors. Energy Build. 56, 1–7 (2013)

    Article  Google Scholar 

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Acknowledgements

Thanks to Milind Tambe and Jun Kwak from USC for sharing the real data in [20] and helpful discussions. This work is supported by NICTA’s Optimization Research Group as part of the Future Energy Systems project. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program.

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Authors and Affiliations

  1. NICTA, The Australian National University, Canberra, Australia

    BoonPing Lim, Hassan Hijazi, Sylvie Thiébaux & Menkes van den Briel

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  1. BoonPing Lim
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  2. Hassan Hijazi
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  4. Menkes van den Briel
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Correspondence to BoonPing Lim .

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  1. University of Nice Sophia Antipolis , Sophia Antipolis, France

    Michel Rueher

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Lim, B., Hijazi, H., Thiébaux, S., van den Briel, M. (2016). Online HVAC-Aware Occupancy Scheduling with Adaptive Temperature Control. In: Rueher, M. (eds) Principles and Practice of Constraint Programming. CP 2016. Lecture Notes in Computer Science(), vol 9892. Springer, Cham. https://doi.org/10.1007/978-3-319-44953-1_43

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  • DOI: https://doi.org/10.1007/978-3-319-44953-1_43

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