OPTIMAL CONTROL APPLICATIONS AND METHODS Optim. Control Appl. Meth. (2014) Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/oca.2116 A room simulation tool for thermal comfort control in a bioclimatic building: A real example of use with an optimal controller M. Castilla 1 , J. Bonilla 2, * ,† , J. D. Álvarez 3 and F. Rodríguez 1 1 Automatic Control, Robotics and Mechatronics Research Group, University of Almería, Agrifood Campus of International Excellence, (ceiA3), CIESOL, Joint Center University of Almería - CIEMAT, Almería, Spain 2 Plataforma Solar de Almería (PSA), Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), 04200 Tabernas, Almería, Spain 3 Department of Automation and System Engineering, University of Seville, 41092 Seville, Spain SUMMARY A key objective in the European Union climate and energy package for 2020 is the reduction of energy consumption. Buildings are responsible for more that one third of global energy consumption, where heating, ventilation, and air conditioning systems account for more than half of it. In extreme climates, the existing passive measures of bioclimatic buildings are not enough at time to maintain a suitable users’ thermal comfort. However, this thermal comfort must be reached reducing the energy spent by the heating, ventilation, and air conditioning system of the building. Control systems, and more specifically model pre- dictive control, are a suitable way to find a trade-off between users’ thermal comfort and energy saving. Simulation tools are essential for the efficient and automated testing and validation of these control strategies. This paper presents a simulation tool of an office room from a bioclimatic building, namely, the CDdI- CIESOL-ARFRISOL building, to test advanced control strategies against a simulation model, to evaluate them, in terms of users comfort and energy consumption, and to validate them, considering the real room itself. Details about the simulation tool are given, together with the evaluation of its goodness through a real test using a nonlinear model predictive control in an office room of that building. Copyright © 2014 John Wiley & Sons, Ltd. Received 15 October 2013; Revised 29 January 2014; Accepted 12 February 2014 KEY WORDS: simulation tool; thermal comfort; energy efficiency; HVAC system; nonlinear model predictive control 1. INTRODUCTION The reduction of energy consumption and CO 2 emissions are the key objectives in the European Union climate and energy package for 2020 [1]. Recent studies show that buildings are responsible for 40% and 35% of world energy consumption and CO 2 emissions [2], where heating, ventila- tion, and air conditioning (HVAC) systems account for more than half of energy consumption [3]. Certainly, improvements in the construction and use of buildings could considerably contribute to meet the European Union goals, and this is why they are widely studied and analyzed by industry and academia [4]. Improvements in the construction and use of buildings can be achieved by means of bioclimatic architecture. However, the use of passive bioclimatic strategies by themselves may be insufficient under certain circumstances, being necessary the use of additional active strategies, such as (HVAC) systems coupled with renewable energies to reduce the energy consumption. These strategies are put *Correspondence to: J. Bonilla, Plataforma Solar de Almería (PSA), Centro de Investigaciones Energéticas, Medioam- bientales y Tecnológicas (CIEMAT), 04200 Tabernas, Almería, Spain. † E-mail: javier.bonilla@psa.es Copyright © 2014 John Wiley & Sons, Ltd.