A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks

Ke-yan Liu, Wanxing Sheng, Yongmei Liu and Xiaoli Meng
Additional contact information
Ke-yan Liu: Power Distribution Department, China Electric Power Research Institute, Beijing 100192, China
Wanxing Sheng: Power Distribution Department, China Electric Power Research Institute, Beijing 100192, China
Yongmei Liu: Power Distribution Department, China Electric Power Research Institute, Beijing 100192, China
Xiaoli Meng: Power Distribution Department, China Electric Power Research Institute, Beijing 100192, China

Energies, 2017, vol. 10, issue 5, 1-17

Abstract: This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG) allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO). Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA). In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible.

Keywords: distribution network reconfiguration; interval analysis; reliability; data 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: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/5/618/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/5/618/ (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:10:y:2017:i:5:p:618-:d:97386

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 ().