Next Article in Journal
Propagation of Elastic Waves in a One-Dimensional High Aspect Ratio Nanoridge Phononic Crystal
Previous Article in Journal
Numerical Analysis of Q-Switched Erbium Ion Doped Fluoride Glass Fiber Laser Operation Including Spontaneous Emission
Previous Article in Special Issue
CSO Based Solution for Load Kickback Effect in Deregulated Power Systems
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Appl. Sci. 2018, 8(5), 804; https://doi.org/10.3390/app8050804

An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization

1
Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Malacca 76100, Malaysia
2
Department of Energy Engineering, An-Najah National University, Nablus 97300, Palestine
*
Author to whom correspondence should be addressed.
Received: 22 April 2018 / Revised: 9 May 2018 / Accepted: 14 May 2018 / Published: 16 May 2018
(This article belongs to the Special Issue Distribution Power Systems)
View Full-Text   |   Download PDF [1737 KB, uploaded 21 May 2018]   |  

Abstract

The presence of optimized distributed generation (DG) with suitable distribution network reconfiguration (DNR) in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO) is proposed in this research. The objective function is formulated to minimize the total power losses (TPL) and to improve the voltage stability index (VSI). The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO) and iteration particle swarm optimization (IPSO). Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms. View Full-Text
Keywords: distribution network reconfiguration; distributed generation; improved evolutionary particle swarm optimization; voltage stability index distribution network reconfiguration; distributed generation; improved evolutionary particle swarm optimization; voltage stability index
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Napis, N.F.; Abd. Kadir, A.F.; Khatib, T.; Hassan, E.E.; Sulaima, M.F. An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization. Appl. Sci. 2018, 8, 804.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top