Particle swarm optimization-based power and temperature control scheme for grid-connected DFIG-based dish-Stirling solar-thermal system

Variable-speed operation of a dish-Stirling (DS) concentrated solar-thermal power generating system can achieve higher energy conversion efficiency compared to the conventional fixed-speed operation system. However, tuning of the controllers for the existing control schemes is cumbersome due to the presence of a large number of control parameters. This paper proposes a new control system design approach for the doubly-fed induction generator (DFIG)-based DS system to achieve maximum power point tracking and constant receiver temperature regulation. Based on a developed thermo-electro-pneumatic model, a coordinated torque and mean pressure control scheme is proposed. Through steady-state analysis, the optimal torque is calculated using the measured insolation and it serves as the tracking reference for direct torque control of the DFIG. To minimize the tracking error due to temperature variation and the compressor loss of the hydrogen supply system, four optimal control parameters are determined using particle swarm optimization (PSO). Model-order reduction and the process of the pre-examination of system stability are incorporated into the PSO algorithm, and it effectively reduces the search effort for the best solution to achieve maximum power point tracking and maintain the temperature around the set-point. The results from computational simulations are presented to show the efficacy of the proposed scheme in supplying the grid system with smoothened maximum power generation as the solar irradiance varies