Journal of System Simulation
Abstract
Abstract: To address the new challenges of economic control and real-time requirements in wind energy conversion systems (WECS), this study proposes a nonlinear economic model predictive control (NEMPC) strategy. This strategy aims to maximize power generation and while reducing fatigue loads on critical structures, such as towers and gearboxes. Additionally, a moving horizon estimator (MHE) has been designed to provide an effective initialization for optimization. By exploiting the similarity of nonlinear programs between adjacent sampling moments, the algorithm achieves real-time iterative (RTI) solutions. Using a 5 MW wind turbine as the research object, the proposed strategy is implemented in the ACADOS framework for real-time optimization. Simulation results demonstrate that the strategy effectively improves the economic performance of the system while ensuring real-time control.
Recommended Citation
Wang, Wenwen; Liu, Xiangjie; and Kong, Xiaobing
(2025)
"Real-time Nonlinear Economic Model Predictive Control of Wind Energy Conversion System,"
Journal of System Simulation: Vol. 37:
Iss.
3, Article 11.
DOI: 10.16182/j.issn1004731x.joss.23-1396
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss3/11
First Page
679
Last Page
690
CLC
TP273
Recommended Citation
Wang Wenwen, Liu Xiangjie, Kong Xiaobing. Real-time Nonlinear Economic Model Predictive Control of Wind Energy Conversion System[J]. Journal of System Simulation, 2025, 37(3): 679-690.
DOI
10.16182/j.issn1004731x.joss.23-1396
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