Optimal Control Virtual Inertia of Optical Storage Microgrid Based on Improved Sailfish Algorithm

Abstract

The optical storage microgrid system composed of power electronic converters is a small inertia system. Load switching and power supply intermittent will affect the stability of the direct current (DC) bus voltage. Aiming at this problem, a virtual inertia optimal control strategy applied to optical storage microgrid is proposed. Firstly, a small signal model of the system is established to theoretically analyze the influence of virtual inertia and damping coefficient on DC bus voltage and to obtain the constraint range of virtual inertia and damping coefficient; Secondly, aiming at the defect that the Sailfish optimization algorithm is easy to premature maturity, a Sailfish optimization algorithm based on the leak-proof net and the cross-mutation propagation mechanism is proposed; Finally, the virtual inertia and damping coefficient of the system are optimized by the improved Sailfish algorithm to obtain the best control parameters. The simulation results in Matlab/Simulink show that the virtual inertia control optimized by the improved Sailfish algorithm improves the system inertia as well as the dynamic response and robustness of the DC bus voltage.

Harris Hawks Algorithm Incorporating Tuna Swarm Algorithm and Differential Variance Strategy

“…Swarm intelligence optimization algorithm is a metaheuristic algorithm that has now been widely used Article ID 1007-1202(2023)06-0461-13 DOI https://doi.org/10.1051/wujns/2023286461 in image processing [1] , control optimization [2,3] , electric power [4,5] , and so on. The mainstream swarm intelligence optimization algorithms are Particle Swarm Optimization (PSO) [6] , Grey Wolf Optimizer (GWO) [7] , Whale Optimization Algorithm (WOA) [8] , Butterfly Optimization Algorithm (BOA) [9] , Bacterial Foraging Optimization (BFA) [10] , Harris Hawks Optimization (HHO) [11] , Sparrow Search Algorithm (SSA) [12] , etc.…”

A Virtual Inertia Method for Stability Control of DC Distribution Systems with Parallel Converters

“…At the same time, the control method reduced the absolute value of voltage deviation and optimized the dynamic characteristics of the system. An intelligent method was used to solve the voltage quality problem caused by low inertia of the DC microgrid in [8]. In addition, an intelligent optimization control strategy based on virtual inertia and damping coefficient was proposed to enhance the stability of the DC distribution system.…”