A Method for Load Classification and Energy Scheduling Optimization to Improve Load Reliability

Yinze Ren, Hongbin Wu, Hejun Yang, Shihai Yang and Zhixin Li
Additional contact information
Yinze Ren: School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
Hongbin Wu: School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
Hejun Yang: School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
Shihai Yang: State Grid Jiangsu Electric Power Co. Ltd., Nanjing 210024, China
Zhixin Li: State Grid Jiangsu Electric Power Co. Ltd., Nanjing 210024, China

Energies, 2018, vol. 11, issue 6, 1-19

Abstract: With the large amount of distributed generation in use, the structure of the distribution system is increasingly complex. Therefore, it is necessary to establish a method to improve load reliability. Based on the reliability model of distributed generation, this paper investigates the time sequential simulation of a wind/solar/storage combined power supply system under off-grid operation. After classifying the load by power supply region, the load weight coefficient is established, which modifies the reliability index of the load point and system. The modified expected energy not supplied (EENS) is adopted as the objective function, and the particle swarm optimization algorithm is used to solving the optimal energy scheduling for improving the load reliability. Finally, the load reliability is calculated with a hybrid method. Using the IEEE-RBTS Bus 6 system as an example, the correctness and validity of the proposed method are verified as an effective way to improve load reliability.

Keywords: load classification; energy scheduling; load reliability; PSO algorithm (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/6/1558/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/6/1558/ (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:11:y:2018:i:6:p:1558-:d:152452

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 ().