Multi-objective stochastic Distribution Feeder Reconfiguration from the reliability point of view

Abdollah Kavousi-Fard and Taher Niknam

Energy, 2014, vol. 64, issue C, 342-354

Abstract: The main purpose of this paper is to assess the DFR (Distribution Feeder Reconfiguration) strategy as a costless technique to enhance the reliability of the distribution systems. The objective functions to be investigated are: SAIFI (System Average Interruption Frequency Index), AENS (Average Energy Not Supplied), total active power losses and the total network cost. In order to observe the effect of renewable energy sources on the reliability of the power system, wind power source as a popular type of renewable energy source is also considered in the system. In addition, to make the analysis more reliable, the uncertainty of the forecast error of active and reactive loads, wind speed variations as well as the failure rate and repair rate parameters are modeled though the probabilistic load flow. Since the problem investigated is a type of discrete, nonlinear and non-convex optimization problem, a novel self adaptive modified optimization algorithm based on the BA (bat algorithm) is proposed too. The proposed self adaptive modification method makes use of three sub-modifications to give each bat (solution) a choice of preferences during the optimization process. The efficiency and feasibility of the proposed method are studied through a standard IEEE (Institute of Electrical and Electronics Engineers) test system.

Keywords: Reliability; Uncertainty; Multi-objective Distribution Feeder Reconfiguration; Point Estimate Method (PEM); Self Adaptive Modified Bat Algorithm (SAMBA) (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544213007494
Full text for ScienceDirect subscribers only

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:eee:energy:v:64:y:2014:i:c:p:342-354

DOI: 10.1016/j.energy.2013.08.060

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().