Dynamics Power Quality Cost Assessment Based on a Gradient Descent Method

Jingyi Zhang, Tongtian Sheng, Pan Gu, Miao Yu, Jiaxin Yan (), Jianqun Sun and Shanhe Liu
Additional contact information
Jingyi Zhang: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China
Tongtian Sheng: State Grid Corporation of China, Beijing 100031, China
Pan Gu: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China
Miao Yu: School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Jiaxin Yan: School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Jianqun Sun: School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Shanhe Liu: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China

Energies, 2024, vol. 17, issue 9, 1-14

Abstract: The escalating demand for power load is increasingly prone to triggering power quality (PQ) issues, leading to severe economic losses. Aiming at reducing the economic losses, this paper focuses on the coordinated relationship between PQ and economic costs. Firstly, a multilayer multiple linear stepwise regression method is employed to screen PQ indicators, identifying harmonic and voltage deviation as the primary influencing factors of PQ. Secondly, a gradient descent optimization algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO) is proposed, enabling rapid computation of the minimum PQ cost. Finally, through validations of two case studies, the results confirm that the proposed method can rapidly calculate the minimum PQ cost based on real-time load demands, enabling the dynamic adjustment of PQ cost to meet the evolving needs of power system development.

Keywords: PQ cost; dynamic PQ index; LASSO; gradient descent; data driven (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (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/1996-1073/17/9/2104/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/9/2104/ (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:jeners:v:17:y:2024:i:9:p:2104-:d:1384959

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

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