Supervisory predictive control of a hybrid solar panels, microturbine and battery power generation plant

The main objective of this work is to design a supervisory predictive controller which optimizes the power flow of a renewable hybrid system (solar panels, microturbine and battery. Short time predictions of the solar power and the power reference will be embedded in the supervisor. Unlike expertise-based algorithms, the design of a generic and flexible strategy based on dynamic models is proposed. The performance index integrates the environmental impact, the cost of fuel, battery cycling and the energy delivery. Simulations and a real-time application in a Hardware-in-the-Loop plant are carried out to illustrate the applicability and effectiveness of the proposed supervisory predictive control design.