EconPapers    
Economics at your fingertips  
 

A dynamics-constrained method for distributed frequency regulation in low-inertia power systems

Zhihao Li, Lun Yang and Yinliang Xu

Applied Energy, 2023, vol. 344, issue C, No S0306261923006207

Abstract: An increasing number of power electronics-interfaced renewable energy sources are integrated into the power grids. Such power systems suffer from poor frequency dynamic behaviors due to the decreasing rotational inertia and governor damping, thus are vulnerable to disturbances. A widely investigated approach to improve the frequency dynamics of the system is to imitate the synchronous generator responses by power converter control. In this paper, a dynamics-constrained frequency control method is proposed to bridge the gap between frequency dynamics optimization and secondary frequency control in low-inertia power systems. An intraday optimization model is formulated for the optimal tuning of the converter control parameters with guaranteed frequency security, and a distributed model predictive controller is developed for recovering the frequency economically. Case studies demonstrate the practicability of the proposed dynamic constrained frequency regulation approach and further comparison illustrates the computational efficiency and scalability of the proposed distributed algorithm.

Keywords: Low-inertia systems; Frequency regulation; Virtual synchronous machine; Distributed model predictive control; Dynamics-constrained (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261923006207
Full text for ScienceDirect subscribers only

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:eee:appene:v:344:y:2023:i:c:s0306261923006207

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2023.121256

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:344:y:2023:i:c:s0306261923006207