Robust Load Frequency Control of Interconnected Power Systems with Back Propagation Neural Network-Proportional-Integral-Derivative-Controlled Wind Power Integration

Fang Ye and Zhijian Hu ()
Additional contact information
Fang Ye: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110020, China
Zhijian Hu: LAAS-CNRS, Université de Toulouse, 31077 Toulouse, France

Sustainability, 2024, vol. 16, issue 18, 1-17

Abstract: As the global demand for energy sustainability increases, the scale of wind power integration steadily increases, so the system frequency suffers significant challenges due to the huge fluctuations of the wind power output. To address this issue, this paper proposes a Back Propagation Neural Network-Proportional-Integral-Derivative (BPNN-PID) controller to track the output power of the wind power generation system, which can well alleviate the volatility of the wind power output, resulting in the slighter imbalance with the rated wind power output. Furthermore, at the multi-area power system level, to mitigate the impact of the imbalanced wind power injected into the main grid, the H ∞ robust controller was designed to ensure the frequency deviation within the admissible range. Finally, a four-area interconnected power system was employed as the test system, and the results validated the feasibility and effectiveness of both the proposed BPNN-PID controller and the robust controller.

Keywords: load frequency control; wind power generation; BPNN-PID; multi-area power system; robust controller (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/18/8062/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/18/8062/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:18:p:8062-:d:1478611

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().