ScienceDirect IFAC-PapersOnLine 48-23 (2015) 278–285 Available online at www.sciencedirect.com 2405-8963 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Peer review under responsibility of International Federation of Automatic Control. 10.1016/j.ifacol.2015.11.296 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Keywords: Solar energy, Parabolic trough, Model Predictive Control, Optimization, Nonlinear. 1. INTRODUCTION The interest in renewable energy sources such as solar energy, experienced a great impulse after the Big Oil Crisis in the 70s. Driven mainly by economic factors, this interest decreased when oil prices fell. Nowadays, there is a renewed interest in renewable energies spurred by the need of reducing the environmental impact produced by the use of fossil energy systems (Goswami et al. (2000); Camacho and Berenguel (2012)). Solar energy is, by far, the most abundant source of renewable energy (Camacho and Gallego (2013a)). The use of solar energy has rapidly increased since the 80s. Many solar electricity production, furnaces, heating and solar cooling systems have been developed in the last decade (Camacho et al. (2012a)). The main technologies for converting solar energy into electricity are photovoltaic (PV) and concentrated solar thermal (CST). Parabolic trough, solar towers, Fresnel collector and solar dishes are the most used technologies for concentrating solar energy. One of the first trough solar operative plants was at the Plataforma Solar de Almer´ ıa (PSA), in southern Spain. This trough plant consisted of a field of solar col- lectors (ACUREX), a heat storage system and an electrical conversion unit (0.5 MW Stal-Laval turbine). This plant has been operating since 1980, and many control strate- gies for solar systems have been tested there (Camacho et al. (1992);Silva et al. (1997);Igreja et al. (2005);Ca- macho et al. (2007c);Camacho et al. (2007b);Limon et al. (2008b)). The 9 SEGS trough plants (354 MW) which commissioned between 1985 and 1990 in California, are considered to be the first commercial plants. Most of the commercial solar plants have been built and commissioned in the last decade. As examples we can mention the three 50 ⋆ Sponsor and financial support acknowledgment goes here. Paper titles should be written in uppercase and lowercase letters, not all uppercase. MW parabolic trough plants Andasol 1, 2 and 3 (Solar Millennium AG (2011)) in Guadix (Spain), the solar tower plants of Abengoa PS10 and PS20, Gemasolar solar tower built by Torresol Energy, the three 50 MW Solnova and the two 50 MW Helioenery parabolic trough plants of Abengoa in Spain, and the SOLANA and Mojave Solar parabolic trough plant in Arizona, of 280 MW power production each (Abengoa-Solar (2009) and Camacho and Gallego (2013a)). There are two main drawbacks to solar energy systems: a) the resulting energy costs are not yet competitive and b) solar energy is not always available when needed. Considerable research efforts are being devoted to tech- niques which may help to overcome these drawbacks; con- trol is one of those techniques (Camacho and Berenguel (2012)). This paper presents a review of the applications of Model Predictive control (MPC) strategies applied to solar trough plants. The paper describes the results obtained in real test with a recent MPC strategy which uses a nonlinear model to compute the future evolution of the plant response. The paper is organized as follows: Section 2 describes the main aspects and control objectives in the control of solar trough plants. Section 3 presents the mathematical model of the ACUREX solar field used for simulation purposes. Section 4 carries out a review of MPC (linear and nonlinear) control strategies applied to solar trough plants. Section 5 presents an example of how MPC control strategies can be used for optimizing the electrical pro- duction in solar trough plants. Finally, some concluding remarks are given. 2. CONTROL OBJECTIVES IN SOLAR TROUGH PLANTS This section describes the main aspects encountered when controlling thermal solar plants. The main controls of solar plants can be classified into Sun tracking and control of * Departamento de Ingenier´ ıa de Sistemas y Autom´atica. Escuela Superior de Ingenieros, 41092 Sevilla(e-mail: efcamacho@us.es). ** Departamento de Ingenier´ ıa de Sistemas y Autom´atica. Escuela Superior de Ingenieros, 41092 Sevilla(e-mail: antgallen@gmail.com) Abstract: The importance of the use of renewable energy sources has experienced a great impulse since the beginning of the 80s. In particular, solar energy is the most abundant source of renewable energy. Control strategies can be useful to improving the solar plants efficiency. In this work, a review of the applications of Model Predictive control (MPC) strategies applied to solar trough plants is presented. An application of a nonlinear Model Predictive Control for optimizing the electrical production is also described. Model Predictive Control In Solar Trough Plants: A Review Eduardo F. Camacho * Antonio J. Gallego **