Abstract
In this chapter, new trends for comfort control in buildings are presented. First, a brief review of recent approaches in comfort control is made. Second, some of these new trends which have been tested in the CDdI-CIESOL-ARFRISOL building are explained and discussed. Moreover, a section which includes some suggestions aimed at buildings’ technicians about comfort control, which are based on the knowledge presented along this book, are included.
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Agüero J, Rodríguez F, Castilla M, Pereira M (2013a) Productiveness and real time prices in energy management for HVAC systems. In: Proceedings of the 39th annual conference of the IEEE industrial electronics society, Vienna, Austria
Agüero J, Rodríguez F, Giménez A (2013b) Energy management based on productiveness concept. Renew Sustain Energy Rev 22:92–100
Álvarez JD, Costa-Castelló R, Castilla M, Camacho EF (2013) Repetitive control to counteract the effect of people on thermal comfort control. In: Proceedings of European Control Conference, ECC’13, Zürich, Switzerland
Camponogara E, Jia D, Krogh BH, Talukdar SN (2002) Distributed model predictive control. IEEE Control Syst Mag 22(1):44–52
Conejo AJ, Morales JM, Baringo L (2010) Real-time demand response model. IEEE Trans Smart Grid 1(3):236–242
IEA (2008) Worldwide trends in energy use and efficiency. Key insights from IEA indicator analysis. International energy agency. http://www.iea.org/publications/freepublications/publication/Indicators_2008-1.pdf. Accessed 18 Apr 2013
Jorge H, Antunes CH, Martins AG (2000) A multiple objective decision support model for the selection of remote load control strategies. IEEE Trans Power Syst 15(2):865–872
Koehler S, Borrelli F (2013) Building temperature distributed control via explicit MPC and Trim and Respond methods. In: Proceedings of the European Control Conference, ECC’13. Zürich, Switzerland, pp 4334–4339
Kolokotsa D, Tsiavos D, Stavrakakis GS, Kalaitzakis K, Antonidakis E (2001) Advanced fuzzy logic controllers design and evaluation for buildings’ occupant thermal-visual comfort and indoor air quality satisfaction. Energy Build 33:531–543
Lehmann B, Gyalistras D, Gwerder M, Wirth K, Carl S (2012) Intermediate complexity model for model predictive control of integrated room automation. Energy Build 58:250–262
Lujano-Rojas JM, Monteiro C, Dufo-López R, Bernal-Agustín JL (2012) Optimum residential load management strategy for real time pricing (RTP) demand response programs. Energy Policy 45:671–679
Ma Y, Anderson G, Borrelli F (2011) A distributed predictive control approach to building temperature regulation. In: American Control Conference (ACC11). California, USA, San Francisco, pp 2089–2094
Miki M, Yoshida K, Hirano Y, Ikegami H (2013) Estimation of illuminance sensor positions and improvement of energy efficiency in the distributed control lighting system. In: IEEE 8th international Symposium on Applied Computational Intelligence and informatics (SACI), Timisoara, Romania, pp 137–142
Moroşan PD, Bourdais R, Dumur D, Buisson J (2010a) Building temperature regulation using a distributed model predictive control. Energy Build 42:1445–1452
Moroşan PD, Bourdais R, Dumur D, Buisson J (2010b) A dynamic horizon distributed predictive control approach for temperature regulation in multi-zone buildings. In: Proceedings 18th Mediterranean Conference on Control and Automation, MED’10. Marrakech, Morocco, pp 622–627
Moroşan PD, Bourdais R, Dumur D, Buisson J (2011a) Distributed MPC for multizone temperature regulation with coupled constraints. In: Proceedings of the 18th IFAC World Congress, Milan, Italy
Moroşan PD, Bourdais R, Dumur D, Buisson J (2011b) A distributed MPC strategy based on benders decomposition applied to multi-source multi-zone temperature regulation. J Process Control 21(5):729–737
Oldewurtel F, Parisio A, Jones CN, Morari M, Gyalistras D, Gwerder M, Stauch V, Lehmann B, Wirth K (2010a) Energy efficient buildings climate control using stochastic model predictive control and weather predictions. In: Proceedings of the American Control Conference (ACC10), Baltimore, Maryland, USA
Oldewurtel F, Ulbig A, Parisio A, Andersson G, Morari M (2010b) 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), Atlanta, USA, pp 1927–1932
Oldewurtel F, Ulbig A, Morari M, Andersson G (2011) Building control and storage management with dynamic tariffs for shaping demand response. In: 2nd IEEE PES International conference and exhibition on Innovative Smart Grid Technologies (ISGT Europe), pp 1–8
Oldewurtel F, Parisio A, Jones CN, Gyalistras D, Gwerder M, Stauch V, Lehmann B, Morari M (2012) Use of model predictive control and weather forecasts for energy efficient building climate control. Energy Build 45:15–27
Scherer HF, Pasamontes M, Guzmán JL, Álvarez JD, Camponogara E, Normey-Rico JE (2014) Efficient building energy management using distributed model predictive control. J Process Control 24:740–749
Vinther K, Chandan V, Alleyne AG (2013) Learning/Repetitive Control for building systems with nearly periodic disturbances. In: Proceedings of the European Control Conference, ECC’13, Zürich, Switzerland
Vrettos E, Lai K, Oldewurtel F, Andersson G (2013) Predictive control of buildings for demand response with dynamic day-ahead and real-time prices. In: Proceedings of the European Control Conference, ECC’13, Zürich, Switzerland
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Castilla, M.d.M., Álvarez, J.D., Rodríguez Diaz, F., Berenguel, M. (2014). New Trends. In: Comfort Control in Buildings. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-6347-3_6
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DOI: https://doi.org/10.1007/978-1-4471-6347-3_6
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