Coordinated Planning of Power Systems under Uncertain Characteristics Based on the Multilinear Monte Carlo Method

Lang Zhao (), Yuan Zeng, Yizheng Li, Dong Peng and Yao Wang
Additional contact information
Lang Zhao: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Yuan Zeng: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Yizheng Li: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 100005, China
Dong Peng: State Grid Economic and Technological Research Institute Co., Ltd., Beijing 100005, China
Yao Wang: Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030001, China

Energies, 2023, vol. 16, issue 23, 1-15

Abstract: The randomness of the power supply side and the load side of comprehensive energy systems is increasingly prominent. It is very difficult to meet demand through traditional planning methods. To solve this problem, this paper explores the coordinated planning of a power system under uncertain characteristics using the multilinear Monte Carlo method. The uncertain characteristic model and probability density function of the system’s power supply side and load side are established. Taking the optimal operating cost and the maximum wind power consumption as the system planning objectives, a system coordination planning scheme is established, and it is solved by multilinear Monte Carlo simulation. The superiority of this method is verified by taking the modified IEEE 39-bus test system as an example. This method can provide a reference for system planning.

Keywords: coordinated planning; Monte Carlo; power system; uncertainty (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: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/23/7761/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/23/7761/ (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:16:y:2023:i:23:p:7761-:d:1287317

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 ().