Stochastic configuring networks based adaptive sliding mode control strategy to improving stability of SG-VSG paralleled microgrid

• Published in: International journal of electrical power & energy systems Vol. 161; p. 110193
• Main Authors: Li, Hongyue, Zhang, Xiao, Wang, Weiwei, Yu, Hongliang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-10-2024; Elsevier
• Subjects: Adaptive reaching law, Stochastic configuring networks; Microgrid; Sliding mode control; Virtual synchronous generator; Virtual synchronous generator; Microgrid; Adaptive reaching law, Stochastic configuring networks; Sliding mode control
• ISSN: 0142-0615
• DOI: 10.1016/j.ijepes.2024.110193

•Derive an equivalent swing equation of SG-VSG paralleled microgrid.•Propose an improved adaptive SCNs-SMC strategy.•The system stability under the proposed control strategy is proved via Lyapunov theory.•Comparative experiments have verified the progressiveness and effectiveness of the proposed control strategy.
This article proposes an adaptive sliding mode control (SMC) strategy based on stochastic configuring networks (SCNs) to improve the stability of synchronous generator (SG) and virtual synchronous generator (VSG) paralleled microgrid and enhance the dynamic performance. First, derives an equivalent swing equation what coupling of inherent inertia/damping of SG and virtual inertia/damping of VSG, the parameters design problem is established to a stabilization problem of second-order uncertain nonlinear system with bounded uncertainties. Second, an adaptive sliding mode control based on variable-speed reaching law is designed to maintain the second-order nonlinear system stable, and the switch function of adaptive reaching law is improved to reduce system chattering. Then, the stochastic configuring networks is introduced to approximate the nonlinear term, and the approximation ability of SCNs is improved by designing the configuration range of input parameters of hidden layer nodes. The stability of proposed control strategy is proved by Lyapunov theory. Finally, the feasibility and effectiveness of the proposed control strategy are verified by the designed simulations and experiments.