Use of Image-Based Direct Normal Irradiance Forecasts in the Model Predictive Control of a Solar-Thermal Reactor

Abstract

A model predictive control (MPC) system for a solar-thermal reactor was developed and applied to the solar-thermal steam-gasification of carbon. The controller aims at rejecting the disturbances in solar irradiance, caused by the presence of clouds. Changes in solar irradiance are anticipated using direct normal irradiance (DNI) forecasts generated using images acquired through a Total Sky Imager (TSI). The DNI predictor provides an estimation of the disturbances for the control algorithm, for a time horizon of 1 min. The proposed predictor utilizes information obtained through the analysis of sky images, in combination with current atmospheric measurements, to produce the DNI forecast. The predictions of the disturbances are used, in combination with a dynamic model of the process, to determine the required control moves at every time step. The performance of the proposed DNI predictor-controller scheme was compared to the performance of an equivalent MPC that does not use DNI forecasts in the calculation of the control signals. In addition, the performance of a controller fed with perfect DNI predictions was also evaluated.