Enhancing Stability in a WPTEB System: Coordinated Controller Design Using an IAPO Algorithm

In this paper, the problem of coordinated optimization of controller parameters is investigated to enhance the stability of a general class of power systems. A wind-PV-thermal-electricity bundled (WPTEB) system is modeled, integrating traditional thermal power generation with clean energy sources, including wind power, photovoltaic (PV) power, and solid oxide fuel cells. To address the low-frequency oscillation problem in the WPTEB system, an improved arctic puffin optimization (IAPO) algorithm is proposed for the coordinated design of power system stabilizers, power oscillation damping controllers, and unified power flow controller parameters. Compared with existing methods, the proposed algorithm incorporates the good point set theory, convex lens imaging learning, and selection probability strategy, enhancing its optimization capability, global search performance, and avoidance of local optimal. Finally, the WPTEB system is validated through simulations and experiments on a four-machine two-zone system and a 53-machine 118-node system. The results demonstrate that the proposed method effectively leverages the controllers’ advantages, significantly improving system stability and robustness.