Real-Time Aiming Strategy Optimization of Heliostat Field of Solar Power Tower via a Modified PSO Algorithm(SPSO)

This paper proposes an efficient and intelligent real-time optimization algorithm based on meta-heuristics, named SPSO, to manage the operation of SPT under various meteorological conditions, such as cloud shadow changes. In order to reduce the complexity of the real-time optimization metaheuristic algorithm, the population individuals of the metaheuristic algorithm are modeled as intelligent agents of heliostats. A population inheritance mechanism is proposed to improve the classical PSO algorithm and minimize redundant calculations, which extracts the similarity of the heliostat field running continuously. The proposed method is tested in a simulation environment that includes heliostat fields, cylindrical receivers, and cloud movement models. The results show that the proposed SPSO has higher convergence efficiency, better robustness, and shorter optimization time under dynamic cloud shadow conditions. Finally, the convergence of SPSO is demonstrated.