Adaptive incremental state space MPC for collector defocusing of a parabolic trough plant. (15th May 2019)

• Record Type: Journal Article
• Authors: Sánchez, A.J.; Gallego, A.J.; Escaño, J.M.; Camacho, E.F.
• Is Part Of: Solar energy. Volume 184(2019)
• Page Start: 105
• Page End: 114
• Publication Date: 2019-05-15
• Subjects: Solar energy -- Model predictive control -- Collector defocus -- Electric power limitation; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2019.03.094
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: Flow-rate control is limited in saturation and power limitations. Loops defocusing is needed to avoid oil degradation. High nonlinear dynamics and disturbances may affect linear controller performance. High frequency dynamics may be excited if abrupt defocus responses are required. An adaptive incremental MPC strategy is designed showing good performance. Abstract: Commercial solar plants produce energy around a nominal operating point in which the solar field outlet temperature is high and close to the thermal limit of the heat transfer fluid. The main control of the temperature is carried out by means of the fluid flow-rate that circulates through the solar field. Defocusing the collectors is normally used as a safety mechanism to avoid exceeding the thermal limit. However, in situations in which the flow is saturated, the control of defocusing the collectors becomes of vital importance and is the system in charge of controlling the solar field outlet temperature. The paper presents an Adaptive State Space Model Predictive Control strategy with an incremental formulation to control the fourth and third collector defocus angles for field outlet temperature set-point tracking at the nominal operation point, avoiding the Heat Transfer Fluid temperature from exceeding the manufacturer thermal limit (oil degradation). The state space description uses an Unscented Kalman Filter for estimating the non-measurable states. A 50 MW parabolic solar trough plant nonlinear model has been used to design and validate the strategy. Simulation results are presented showing the advantages of using the proposed strategy.