Modeling and Control of Dish-Stirling Solar Thermal Integrated With PMDC Generator Optimized by Meta-Heuristic Approach

Abstract

This paper proposes an autonomous microgrid system for the first time with solar thermal dish-Stirling engine coupled with permanent magnet direct current generator and battery energy storage system along with uncontrolled variable loads. Both proportional-integral (PI) and proportional-integral-derivative (PID) controllers are considered separately for the bidirectional charge controller and buck-boost converter controller for the dish-Stirling system. The modern meta-heuristic algorithms including recent ones like particle swarm optimization, mine blast algorithm and grey wolf optimizer (GWO), have been adopted for tuning the gain parameters of the controllers used for the direct current common bus voltage stability and power sharing. The work considers variable insolation level for somehow mimicking the natural solar variation all the day. The simulation of the proposed model is carried out in MATLAB/Simulink and the results are obtained with two types of controllers for comparison. The results demonstrate the superior performance of the PID controllers optimized with GWO algorithm in terms of faster convergence rate, DC voltage profile, and maintenance of SOC of battery and energy efficiency as compared to the other two algorithms. It is also to be noted that the use of a permanent magnet DC generator coupled to the solar dish-Stirling engine improves the electric conversion efficiency and reduces cost effectively as compared to AC generators.