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Articles

Chance constrained stochastic MPC for building climate control under combined parametric and additive uncertainty

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Pages 410-430 | Received 22 Jul 2021, Accepted 16 Mar 2022, Published online: 06 Apr 2022

References

  • Afram, A., and F. Janabi-Sharifi. 2014. “Theory and Applications of HVAC Control Systems – A Review of Model Predictive Control (MPC).” Building and Environment 72: 343–355.
  • Avci, M., M. Erkoc, A. Rahmani, and S. Asfour. 2013. “Model Predictive HVAC Load Control in Buildings Using Real-Time Electricity Pricing.” Energy and Buildings 60: 199–209.
  • Bacher, P., and H. Madsen. 2011. “Identifying Suitable Models for the Heat Dynamics of Buildings.” Energy and Buildings 43 (7): 1511–1522.
  • Baetens, R., and D. Saelens. 2016. “Modelling Uncertainty in District Energy Simulations by Stochastic Residential Occupant Behaviour.” Journal of Building Performance Simulation 9 (4): 431–447.
  • Bengea, S., V. Adetola, K. Kang, M. J. Liba, D. Vrabie, R. Bitmead, and S. Narayanan. 2011. “Parameter Estimation of a Building System Model and Impact of Estimation Error on Closed-Loop Performance.” In 50th IEEE Conference on Decision and Control and European Control Conference, 5137–5143. Orlando, FL: IEEE.
  • Bianchini, G., M. Casini, A. Vicino, and D. Zarrilli. 2016. “Demand-Response in Building Heating Systems: A Model Predictive Control Approach.” Applied Energy 168: 159–170.
  • Calafiore, G. C., and L. El Ghaoui. 2006. “On Distributionally Robust Chance-Constrained Linear Programs.” Journal of Optimization Theory and Applications 130 (1): 1–22.
  • De Jaeger, I. 2021. “On the Impact of Input Data Uncertainty on the Reliability of Urban Building Energy Models.” PhD diss., KU Leuven.
  • De Jaeger, I., J. Lago, and D. Saelens. 2018. “A Probabilistic Approach to Allocate Building Parameters within District Energy Simulations.” In Proceedings of the Urban Energy Simulation Conference, Glasgow, Scotland: University of Strathclyde.
  • De Jaeger, I., J. Lago, and D. Saelens. 2021. “A Probabilistic Building Characterization Method for District Energy Simulations.” Energy and Buildings 230: 110566.
  • Djunaedy, E., K. Van den Wymelenberg, B. Acker, and H. Thimmana. 2011. “Oversizing of HVAC System: Signatures and Penalties.” Energy and Buildings 43 (2-3): 468–475.
  • Drgoňa, J., J. Arroyo, I. C. Figueroa, D. Blum, K. Arendt, D. Kim, E. P. Ollé, et al. 2020. “All You Need to Know About Model Predictive Control for Buildings.” Annual Reviews in Control 50: 190–232.
  • Drgoňa, J., M. Kvasnica, M. Klaučo, and M. Fikar. 2013. “Explicit Stochastic MPC Approach to Building Temperature Control.” In 52nd IEEE Conference on Decision and Control, 6440–6445. Florence, Italy: IEEE.
  • Farina, M., L. Giulioni, and R. Scattolini. 2016. “Stochastic Linear Model Predictive Control with Chance Constraints–A Review.” Journal of Process Control 44: 53–67.
  • Farina, M., and R. Scattolini. 2016. “Model Predictive Control of Linear Systems with Multiplicative Unbounded Uncertainty and Chance Constraints.” Automatica 70: 258–265.
  • Gang, W., S. Wang, K. Shan, and D. Gao. 2015. “Impacts of Cooling Load Calculation Uncertainties on the Design Optimization of Building Cooling Systems.” Energy and Buildings 94: 1–9.
  • Gang, W., S. Wang, F. Xiao, and D.-C. Gao. 2015. “Robust Optimal Design of Building Cooling Systems Considering Cooling Load Uncertainty and Equipment Reliability.” Applied Energy 159: 265–275.
  • Geng, X., and L. Xie. 2019. “Data-Driven Decision Making in Power Systems with Probabilistic Guarantees: Theory and Applications of Chance-Constrained Optimization.” Annual Reviews in Control 47: 341–363.
  • Gouda, M., S. Danaher, and C. Underwood. 2000. “Low-Order Model for the Simulation of A Building and Its Heating System.” Building Services Engineering Research and Technology 21 (3): 199–208.
  • Goyal, S., H. A. Ingley, and P. Barooah. 2012. “Effect of Various Uncertainties on the Performance of Occupancy-Based Optimal Control of HVAC Zones.” In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 7565–7570. Maui, Hawaii: IEEE.
  • Guerra-Santin, O., and L. Itard. 2010. “Occupants' Behaviour: Determinants and Effects on Residential Heating Consumption.” Building Research & Information 38 (3): 318–338.
  • Gutschker, O. 2008. “Parameter Identification with the Software Package LORD.” Building and Environment 43 (2): 163–169. Outdoor Testing, Analysis and Modelling of Building Components.
  • Harb, H., N. Boyanov, L. Hernandez, R. Streblow, and D. Müller. 2016. “Development and Validation of Grey-Box Models for Forecasting the Thermal Response of Occupied Buildings.” Energy and Buildings 117: 199–207.
  • Hewing, L., K. P. Wabersich, and M. N. Zeilinger. 2020. “Recursively Feasible Stochastic Model Predictive Control Using Indirect Feedback.” Automatica 119: 109095.
  • Horn, R. A., and C. R. Johnson. 1991. Topics in Matrix Analysis. 37 vols. Cambridge: Cambridge University Presss. 3–9.
  • Huang, P., G. Huang, and Y. Wang. 2015. “HVAC System Design Under Peak Load Prediction Uncertainty Using Multiple-Criterion Decision Making Technique.” Energy and Buildings 91: 26–36.
  • Ioannou, A., and L. C. Itard. 2015. “Energy Performance and Comfort in Residential Buildings: Sensitivity for Building Parameters and Occupancy.” Energy and Buildings 92: 216–233.
  • Ioli, D., A. Falsone, and M. Prandini. 2016. “Energy Management of a Building Cooling System with Thermal Storage: A Randomized Solution with Feedforward Disturbance Compensation.” In 2016 American Control Conference (ACC), 2346–2351. Boston, MA: IEEE.
  • Jiménez, M. J., H. Madsen, and K. K. Andersen. 2008. “Identification of the Main Thermal Characteristics of Building Components Using Matlab.” Building and Environment 43 (2): 170–180.
  • Jorissen, F., W. Boydens, and L. Helsen. 2018. “Methodology for Integrated Optimal Control and Design of Buildings.” In Proceedings of the REHVA Annual Meeting Conference Low Carbon Technologies in HVAC. Brussels, Belgium: ATIC.
  • Killian, M., and M. Kozek. 2016. “Ten Questions Concerning Model Predictive Control for Energy Efficient Buildings.” Building and Environment 105: 403–412.
  • Klein Haneveld, W. K., M. H. van der Vlerk, and W. Romeijnders. 2020. Chance Constraints, 115–138. Cham: Springer International Publishing.
  • Korkas, C. D., S. Baldi, I. Michailidis, and E. B. Kosmatopoulos. 2016. “Occupancy-Based Demand Response and Thermal Comfort Optimization in Microgrids with Renewable Energy Sources and Energy Storage.” Applied Energy 163: 93–104.
  • Lambrichts, W. 2020. “Model Predictive Control of Residential Heating: Accounting for Uncertainties on Weather and Occupancy Behaviour.” Master's diss., KU Leuven.
  • Long, Y., S. Liu, L. Xie, and K. H. Johansson. 2014. “A Scenario-based Distributed Stochastic MPC for Building Temperature Regulation.” In 2014 IEEE International Conference on Automation Science and Engineering (CASE), 1091–1096. Taipei, Taiwan: IEEE.
  • Ma, Y., J. Matuško, and F. Borrelli. 2014. “Stochastic Model Predictive Control for Building HVAC Systems: Complexity and Conservatism.” IEEE Transactions on Control Systems Technology 23 (1): 101–116.
  • Ma, Y., S. Vichik, and F. Borrelli. 2012. “Fast Stochastic MPC with Optimal Risk Allocation Applied to Building Control Systems.” In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 7559–7564. Maui, Hawaii: IEEE.
  • Maasoumy, M., M. Razmara, M. Shahbakhti, and A. S. Vincentelli. 2014. “Handling Model Uncertainty in Model Predictive Control for Energy Efficient Buildings.” Energy and Buildings 77: 377–392.
  • Maasoumy, M., and A. Sangiovanni-Vincentelli. 2012. “Optimal Control of Building HVAC Systems in the Presence of Imperfect Predictions.” In Dynamic Systems and Control Conference, Vol. 45301, 257–266. Fort Lauderdale, FL: American Society of Mechanical Engineers.
  • Mady, A. E.-D., G. Provan, C. Ryan, and K. Brown. 2011. “Stochastic Model Predictive Controller for the Integration of Building Use and Temperature Regulation.” In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 25. San Francisco, CA: Association for the Advancement of Artificial Intelligence (AAAI).
  • Mavromatidis, G., K. Orehounig, and J. Carmeliet. 2018. “A Review of Uncertainty Characterisation Approaches for the Optimal Design of Distributed Energy Systems.” Renewable and Sustainable Energy Reviews 88: 258–277.
  • Mesbah, A. 2016. “Stochastic Model Predictive Control: An Overview and Perspectives for Future Research.” IEEE Control Systems Magazine 36 (6): 30–44.
  • Mirakhorli, A., and B. Dong. 2016. “Occupancy Behavior Based Model Predictive Control for Building Indoor Climate–A Critical Review.” Energy and Buildings 129: 499–513.
  • Nagpal, H., A. Staino, and B. Basu. 2020. “Robust Model Predictive Control of HVAC Systems with Uncertainty in Building Parameters Using Linear Matrix Inequalities.” Advances in Building Energy Research 14 (3): 338–354.
  • NBN. 2005. “NBN EN ISO 7730:2005 – Ergonomics of the Thermal Environment – Analytical Determination and Interpretation of Thermal Comfort using Calculation of the PMV and PPD Indices and Local Thermal Comfort Criteria.”
  • NBN. 2007. “NBN EN ISO 15251:2007 – Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics.”
  • NBN. 2017. “NBN EN 12831-1: Energy Performance of Buildings – Method for Calculation of the Design Heat Load – Part 1: Space Heating Load.”
  • Nemirovski, A., and A. Shapiro. 2007. “Convex Approximations of Chance Constrained Programs.” SIAM Journal on Optimization 17 (4): 969–996.
  • Oldewurtel, F. 2011. “Stochastic Model Predictive Control for Energy Efficient Building Climate Control.” PhD diss., ETH Zurich, Zürich, 2011. Diss., Eidgenössische Technische Hochschule ETH Züich, Nr. 19908.
  • Oldewurtel, F., D. Gyalistras, M. Gwerder, C. Jones, A. Parisio, V. Stauch, B. Lehmann, and M. Morari. 2010. “Increasing Energy Efficiency in Building Climate Control Using Weather Forecasts and Model Predictive Control.” In Clima-RHEVA World Congress. Antalya, Turkey.
  • Oldewurtel, F., C. N. Jones, and M. Morari. 2008. “A Tractable Approximation of Chance Constrained Stochastic MPC based on Affine Disturbance Feedback.” In 2008 47th IEEE Conference on Decision and Control, 4731–4736. Cancun, Mexico: IEEE.
  • Oldewurtel, F., C. N. Jones, A. Parisio, and M. Morari. 2013. “Stochastic Model Predictive Control for Building Climate Control.” IEEE Transactions on Control Systems Technology 22 (3): 1198–1205.
  • Oldewurtel, F., A. Parisio, C. N. Jones, D. Gyalistras, M. Gwerder, V. Stauch, B. Lehmann, and M. Morari. 2012. “Use of Model Predictive Control and Weather Forecasts for Energy Efficient Building Climate Control.” Energy and Buildings 45: 15–27.
  • Oldewurtel, F., A. Parisio, C. N. Jones, M. Morari, D. Gyalistras, M. Gwerder, V. Stauch, B. Lehmann, and K. Wirth. 2010. “Energy Efficient Building Climate Control Using Stochastic Model Predictive Control and Weather Predictions.” In Proceedings of the 2010 American Control Conference, 5100–5105. Baltimore, MD: IEEE.
  • Oldewurtel, F., A. Ulbig, A. Parisio, G. Andersson, and M. Morari. 2010. “Reducing Peak Electricity Demand in Building Climate Control Using Real-Time Pricing and Model Predictive Control.” In 49th IEEE Conference on Decision and Control (CDC), 1927–1932. Atlanta, GA: IEEE.
  • Parisio, A., M. Molinari, D. Varagnolo, and K. H. Johansson. 2013. “A Scenario-based Predictive Control Approach to Building HVAC Management Systems.” In 2013 IEEE International Conference on Automation Science and Engineering (CASE), 428–435. Madison, WI: IEEE.
  • Parisio, A., D. Varagnolo, M. Molinari, G. Pattarello, L. Fabietti, and K. H. Johansson. 2014. “Implementation of A Scenario-Based MPC for HVAC Systems: An Experimental Case Study.” IFAC Proceedings Volumes 47 (3): 599–605.
  • Parisio, A., D. Varagnolo, D. Risberg, G. Pattarello, M. Molinari, and K. H. Johansson. 2013. “Randomized Model Predictive Control for HVAC Systems.” In Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings, 1–8. Rome, Italy: Association for Computing Machinery (ACM).
  • Peeters, L., R. De Dear, J. Hensen, and W. D'haeseleer. 2009. “Thermal Comfort in Residential Buildings: Comfort Values and Scales for Building Energy Simulation.” Applied Energy 86 (5): 772–780.
  • Peng, S. 2019. “Chance Constrained Problem and Its Applications.” PhD diss., Université Paris Saclay (COmUE); Xi'an Jiaotong University.
  • Petersen, S., and K. W. Bundgaard. 2014. “The Effect of Weather Forecast Uncertainty on A Predictive Control Concept for Building Systems Operation.” Applied Energy 116: 311–321.
  • Prandini, M., S. Garatti, and J. Lygeros. 2012. “A Randomized Approach to Stochastic Model Predictive Control.” In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 7315–7320. Maui, Hawaii: IEEE.
  • Rasmussen, C. E., and C. K. I. Williams. “Gaussian Processes for Machine Learning.” Massachusetts Institute of Technology, 2006. Appendix A: Mathematical background.
  • Reynders, G. 2015. “Quantifying the Impact of Building Design on the Potential of Structural Storage for Active Demand Response in Residential Buildings.” PhD diss., KU Leuven.
  • Reynders, G., J. Diriken, and D. Saelens. 2014a. “Quality of Grey-Box Models and Identified Parameters As Function of the Accuracy of Input and Observation Signals.” Energy and Buildings 82: 263–274.
  • Reynders, G., J. Diriken, and D. Saelens. 2014b. “Bottom-up Modeling of the Belgian Residential Building Stock: Influence of Model Complexity.” In Proceedings of the 9th International Conference on System Simulation in Buildings, 1–19. Liège, Belgium: University of Liège.
  • Serale, G., M. Fiorentini, A. Capozzoli, D. Bernardini, and A. Bemporad. 2018. “Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities.” Energies 11 (3): 631.
  • Sun, Y., L. Gu, C. J. Wu, and G. Augenbroe. 2014. “Exploring HVAC System Sizing Under Uncertainty.” Energy and Buildings 81: 243–252.
  • Tanaskovic, M., D. Sturzenegger, R. Smith, and M. Morari. 2017. “Robust Adaptive Model Predictive Building Climate Control.” IFAC-PapersOnLine 50 (1): 1871–1876.
  • Thieblemont, H., F. Haghighat, R. Ooka, and A. Moreau. 2017. “Predictive Control Strategies Based on Weather Forecast in Buildings with Energy Storage System: A Review of the State-of-the Art.” Energy and Buildings 153: 485–500.
  • Tian, W., Y. Heo, P. De Wilde, Z. Li, D. Yan, C. S. Park, X. Feng, and G. Augenbroe. 2018. “A Review of Uncertainty Analysis in Building Energy Assessment.” Renewable and Sustainable Energy Reviews 93: 285–301.
  • Tindale, A. 1993. “Third-Order Lumped-Parameter Simulation Method.” Building Services Engineering Research and Technology 14 (3): 87–97.
  • Uytterhoeven, A., I. De Jaeger, K. Bruninx, D. Saelens, and L. Helsen. 2021. “Data-Driven Estimation of Parametric Uncertainty of Reduced Order RC Models for Building Climate Control (In Press).” In Proceedings of the International Building Performance Simulation Association. Bruges, Belgium: International Building Performance Association (IBPSA).
  • van der Heijde, B. 2019. “Optimal Integration of Thermal Energy Storage and Conversion in Fourth Generation Thermal Networks.” PhD diss., KU Leuven.
  • Yang, S., M. P. Wan, W. Chen, B. F. Ng, and D. Zhai. 2019. “An Adaptive Robust Model Predictive Control for Indoor Climate Optimization and Uncertainties Handling in Buildings.” Building and Environment 163: 106–326.
  • Zhang, X., S. Grammatico, G. Schildbach, P. Goulart, and J. Lygeros. 2014. “On the Sample Size of Randomized MPC for Chance-Constrained Systems with Application to Building Climate Control.” In 2014 European Control Conference (ECC), 478–483. Strasbourg, France: European Control Association (EUCA)
  • Zhang, J., and T. Ohtsuka. 2020. “Stochastic Model Predictive Control Using Simplified Affine Disturbance Feedback for Chance-Constrained Systems.” IEEE Control Systems Letters 5 (5): 1633–1638.
  • Zhang, X., G. Schildbach, D. Sturzenegger, and M. Morari. 2013. “Scenario-based MPC for Energy-Efficient Building Climate Control under Weather and Occupancy Uncertainty.” In 2013 European Control Conference (ECC), 1029–1034. Zurich, Switzerland: European Control Association (EUCA).

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