Contents lists available at ScienceDirect Solar Energy journal homepage: www.elsevier.com/locate/solener Solar furnace temperature control with active cooling ☆ Bertinho A. Costa a, ⁎ , João M. Lemos a , Emmanuel Guillot b a INESC-ID/IST, University of Lisbon, Rua Alves Redol, 9, 1000-029, Portugal b CNRS-PROMES, 7 rue du Four Solaire, 66120 Font Romeu Odeillo, France ARTICLE INFO Keywords: Solar thermal energy Solar furnace Modelling Control Active cooling ABSTRACT The article describes a control architecture for solar furnaces where active cooling is employed to improve the tracking of a time-varying temperature reference. This capability is important during the decreasing phase of the temperature reference where heat loss must be increased. The results of two different control methodologies, exact linearization and model predictive control with integral action, are shown with active cooling that is done in coordination with the command of the shutter which adjusts the solar incident power. The controller parameters are computed from the temperature dynamics which is identified off-line from collected process data. This approach is used to avoid online adaptation mechanisms of the controller para- meters, that may cause stability problems during the controller startup, and may melt the testing material sample. The novelty of the present work is to present a control architecture that coordinates the operations of the shutter together with the application of active cooling. This methodology improves temperature reference tracking and increases the usability and the operation of solar furnaces. 1. Introduction Increased energy costs, past energy crises and energy conflicts, carbon-based energy pollution, and the expected fossil-fuels induced climate changes, have triggered the development of renewable energy technologies such as concentrating solar power systems (CSP). CSP include solar furnaces, photovoltaic (CPV), solar thermal (CST) which have a wide application, such as the “generation” of electrical energy and heat (Camacho et al., 2007a,b), the production of solar fuels, hy- drogen and syngas (Agrafiotis et al., 2014), desalinization, and material processing (Oliveira et al., 2015, 2016). The article addresses the control of solar furnaces for material processing and stress testing, where the temperature of the sample must follow a time-varying reference with precision. The proposed control architecture has a cascade structure where the outer controller is em- ployed to control the temperature of the sample, computes a reference for the incident flux on the sample, and supplies it to the inner con- troller. The inner controller adjusts the position of the shutter using the information that it receives from the temperature controller and com- pensates changes present in the solar irradiance. If needed, solar in- cident flux control experiments can be done using only the inner con- troller. Research on control of solar furnaces for material processing and stress testing, developed at the Plataforma Solar de Almeria (Berenguel et al., 1999), have addressed several topics, such as constrained temperature control and disturbance rejection (Beschi et al., 2012, 2013b), linearization with the Generalized Predictive Control (GPC) algorithm (Beschi et al., 2013a) and fractional robust PID control (Beschi et al., 2016). Motivated by the improvement of operation and automation of small size solar furnaces at PROMES, Odeillo, (France) to obtain re- peatable results that do not depend on the human operator that manually controls the experiment, several control strategies have been developed and tested, such as adaptive control (Costa and Lemos, 2009a,b; Costa et al., 2011), predictive adaptive temperature control (Costa and Lemos, 2012), and optimal control (Costa and Lemos, 2016). The work that is presented in this article is based on the previous works (Costa et al., 2016a,b) but has the novelty of considering active cooling to improve temperature reference tracking, in particular when the shutter is closed and the temperature of the sample is above the re- ference temperature. It is interesting to remark that, by including active cooling to operate when active heating is off and the temperature of the sample is above the temperature reference, a switched temperature dynamics is obtained. The details are described in Section 2. The article is organized as follows: in Section 2 a description of the http://dx.doi.org/10.1016/j.solener.2017.10.017 Received 16 June 2017; Received in revised form 28 September 2017; Accepted 4 October 2017 ☆ This work was partially supported by the European Union through project SFERA2, under FP7 (project number 312643) and by the FCT-Portugal under the contract UID/CEC/ 50021/2013. ⁎ Corresponding author. E-mail addresses: bac@inesc-id.pt (B.A. Costa), jlml@inesc-id.pt (J.M. Lemos), emmanuel.guillot@promes.cnrs.fr (E. Guillot). Solar Energy 159 (2018) 66–77 0038-092X/ © 2017 Elsevier Ltd. All rights reserved. MARK