Research on Splitting Optimization Considering the Planning of Wind Power Integration

Fei Tang, Weiqiang Liang, Chenxu Wang, Xin Gao, Benxi Hu and Fanghua Qin
Additional contact information
Fei Tang: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Weiqiang Liang: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Chenxu Wang: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Xin Gao: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Benxi Hu: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Fanghua Qin: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

Sustainability, 2020, vol. 12, issue 18, 1-17

Abstract: With the continuous expansion of wind power integration scale, the stability of the power system has been greatly affected, especially the changes of the traditional grid structure, which makes the system splitting face major challenges. In the context of the widespread use of wind energy, a bi-level planning method considering optimal location-allocation of wind power to reduce the difficulty of splitting was proposed. Based on the slow coherence theory, a correlation model that reflects the coherence degree of system buses was constructed. Furthermore, an improved intelligent optimization algorithm was proposed to solve the optimal location-allocation of wind power. The proposed method was conducted in the Institute of Electrical and Electronics Engineering (IEEE) 39-bus system to centralize the splitting scope. It is verified that the proposed method can reduce the system’s possible oscillation modes to realize that less instability occurs under small disturbances, and restrict the range of splitting sections under large disturbances, which ensures the effectiveness of splitting devices to maintain the stable operation of the power grid.

Keywords: wind power; splitting control; slow coherence theory; intelligent optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/18/7726/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/18/7726/ (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:12:y:2020:i:18:p:7726-:d:415548

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 ().