Skip to main content

Optimal Control of Thermal Solar Energy Systems

Periodic Reporting for period 2 - OCONTSOLAR (Optimal Control of Thermal Solar Energy Systems)

Reporting period: 2020-03-01 to 2021-08-31

The problem to be addressed is to develop new control methods to use mobile sensors mounted on drones and unmanned ground vehicles (UGV) as an integral part of the control systems allowing the control of systems geographically disperse. Solar power plants will be used as a case study, with the aim of optimizing their operation using spatial irradiance estimations and predictions

The project aims at developing control techniques to improve the performance of solar energy systems but the technique being developed can also be applied to process such as traffic in highways, agriculture or flood control. Processes which are important for society.

The overall objectives of the project are:
1. Methods to control mobile sensor fleets and integrate them as an essential part of the overall control systems.
2. Spatially distributed solar irradiance estimation methods using a variable fleet of sensors mounted on drones and UGVs.
3. New model predictive control (MPC) algorithms that use mobile solar sensor estimations and predictions to yield safer and more efficient operation of the plants allowing the effective integration of solar energy in systems delivering energy to grids or other systems while satisfying production commitments.
1. Design and procurement of a fleet of drones and UAVs and solar sensors. The fleet is composed of 3 drones incorporating solar sensors and 6 UGV.
2. Development of a VTOL prototype incorporating a solar irradiance sensor.
3. Development of control algorithms for the estimation and short term forecasting of solar irradiance based on the information given by fleet of mobile sensors.
4. Development of MPC coalitional control methods which allows the control of large scale solar plants.
5. Development of new MPC algorithms to control solar power plants using the loop valves as manipulated variables.
6. Development of MPC controllers for defocusing the solar collectors which improves the previous controllers. These controllers have been tested in real plants.
7. The project results have been disseminated in 27 journal papers, 15 conference papers, 4 chapters in books and 5 keynotes and plenary lectures in conferences.
New methods for integrating information coming from sensors mounted on a fleet of vehicles into control systems are expected.

New algorithm for the spatial estimation and short term forecasting of solar irradiance are being developed. The estimation and short term forecasting of solar irradiance is expected to improve the control of solar power plants.

Algorithm for optimizing thermal solar plants by controlling the loop valves that take into account the short term forcast of the sorar irradiance are being developed. Simulation studies have shown that an increase in production of up to 10% can be obtained by using optimal control algorithms which manipulates the loop valves optimally.

New coalitional control algorithm for large solar plant. These algorithms allow the application of MPC to large plants.

Defocusing control algorithms for thermal solar plants. When the received solar power is higher than the power that can be generated and stores, the collectors have to be defocused. Defocusing algorithms used in commercial plants produce high oscillations and deterioration of actuators.. The research group has developed algorithm based on MPC which reduces considerably the oscillations and actuators wear.