Centralized and distributed Model Predictive Control for the maximization of the thermal power of solar parabolic-trough plants

This paper proposes a new centralized Model Predictive Control (MPC) algorithm for the maximization of the thermal power obtained with a parabolic-trough collector field. The optimal operation of the plant is achieved by controlling a set of valves located at the beginning of each loop of collectors, which allow to outperform the response achieved with traditional control approaches for parabolic-trough plants. Unfortunately, the computational complexity of the proposed MPC controller hinders its application in real-time for medium and large parabolic-trough power plants. Consequently, this paper also proposes a logic-based distributed Model Predictive Control algorithm, which approaches the performance of the centralized MPC but entailing a much lower computational load. The proposed controllers are tested by simulation using a model of the collector field ACUREX (Almeria, Spain) along a 2-h synthetic DNI profile. The results obtained show that the proposed distributed algorithm is able to perform quite close to the centralized one. Moreover, the analysis of the numerical results (in terms of achieved power) shows that the use of valves at the beginning of each loop substantially improve the achieved thermal power, that the achieved performance using a local controller is significantly lower than using a global one, and that the maximization of the thermal power does not imply the maximization or minimization of the outlet temperature.