Research on adaptive optimal control algorithm for nonlinear dynamic characteristics of new energy power system
Authors
Guozhen Jiang, Cheng Jin, Chaoyong Qu
Abstract
An adaptive optimal control algorithm based on the Port-Controlled Hamiltonian with Dissipation (PCHD) model is proposed to address reduced inertia and complex nonlinear dynamics in power systems with high renewable penetration. It uses forgetting-factor recursive least squares (RLS) for online identification of time-varying parameters to build an accurate nonlinear model. A bottom-layer Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) ensures stabilization, while an upper-layer nonlinear model predictive control (NMPC) performs multi-objective rolling optimization, dynamically adjusting the equilibrium point and damping parameters to enhance system stability and economic performance. MATLAB/Simulink simulation results show that, compared with traditional PI control and IDA-PBC with fixed parameters, the proposed algorithm can reduce the maximum frequency deviation to −0.45 Hz, shorten the frequency recovery time to 4.2s, and reduce the ITAE index by 77%, while achieving the optimal power generation cost, which verifies its adaptability and robustness in transient stability control.
Citation
- Journal: IET Conference Proceedings
- Year: 2026
- Volume: 2025
- Issue: 47
- Pages: 1284–1290
- Publisher: Institution of Engineering and Technology (IET)
- DOI: 10.1049/icp.2026.0406
BibTeX
@article{Jiang_2026,
title={{Research on adaptive optimal control algorithm for nonlinear dynamic characteristics of new energy power system}},
volume={2025},
ISSN={2732-4494},
DOI={10.1049/icp.2026.0406},
number={47},
journal={IET Conference Proceedings},
publisher={Institution of Engineering and Technology (IET)},
author={Jiang, Guozhen and Jin, Cheng and Qu, Chaoyong},
year={2026},
pages={1284--1290}
}