Author
Listed:
- Wanying Liu
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
DongFang Boiler (Group) Co., Ltd., Dongfang Electric Corporation, Chengdu 611730, China)
- Yang Zheng
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China)
- Zhi Zhang
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
China Yangtze Power Co., Ltd., Yichang 443002, China)
- Zifei Li
(School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China)
- Jianwei Li
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
China Yangtze Power Co., Ltd., Yichang 443002, China)
- Junqing Wang
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
China Yangtze Power Co., Ltd., Yichang 443002, China)
- Guang Li
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
China Yangtze Power Co., Ltd., Yichang 443002, China)
- Jia He
(Hubei Technology Innovation Center for Smart Hydropower, Wuhan 430000, China
China Yangtze Power Co., Ltd., Yichang 443002, China)
Abstract
This paper studies the collaborative inertia-frequency regulation strategies for the high renewable energy penetrated low inertia power system. Firstly, a systematic investigation is conducted to reveal the dominant dynamic characteristics and the possible challenges for such systems, and then proved the effectiveness of virtual inertia. Subsequently, a novel Laguerre-based model predictive control strategy is accordingly pro-posed, which ensures a better system states convergence ability and a reduced computational burden. The controller takes into account the system’s dual-mode feature to ensure timely response for both the inertia and the frequency support. Then, the regulation quality, operational burden and the cost are mathematically defined. The control trajectory is determined by the rolling optimization. The Gravity Searching Algorithm is utilized to determine the optimal control parameters. Finally, the proposed control strategy is validated through five case studies, demonstrating enhanced robustness, superior dynamic performance and cost-effective operation. This study provides new insights for the analysis and control strategies of the high RE penetrated low inertia systems.
Suggested Citation
Wanying Liu & Yang Zheng & Zhi Zhang & Zifei Li & Jianwei Li & Junqing Wang & Guang Li & Jia He, 2025.
"Dual-Mode Laguerre MPC and Its Application in Inertia-Frequency Regulation of Power Systems,"
Energies, MDPI, vol. 18(16), pages 1-21, August.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:16:p:4311-:d:1723849
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:16:p:4311-:d:1723849. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.