A new thief and police algorithm and its application in simultaneous reconfiguration with optimal allocation of capacitor and distributed generation units

H.B. Tolabi, A. Lashkar Ara and R. Hosseini

Energy, 2020, vol. 203, issue C

Abstract: This work aims to present a new optimization approach named Thief and Police Algorithm (TPA) to solve discrete-continuous optimization problems. The TPA performance was assessed by solving a discrete-continuous optimization problem in distribution networks. The optimization problem in this study was simultaneous reconfiguration with optimal allocation of capacitor, photovoltaic (PV) and Wind Turbine (WT) units. The objectives were considered as minimization of power loss, minimization of operational cost and improvement of voltage stability of the network. The proposed technique was evaluated using the IEEE 33 bus distribution network with eight different scenarios. Their results were compared with each other on different scenarios and with other well-known algorithms such as Symbiotic Organisms Search (SOS), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The results reveals that the TPA outperforms its counterparts in solving the mentioned problem. Also, the performance of the TPA was assessed using the 30 CEC 2017 test functions and the results were compared to the other optimization methods which confirms high capability of the TPA to solve complex optimization problems.

Keywords: Optimization; Photovoltaic; Reconfiguration; Thief and police algorithm; Wind turbine (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220310185
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:203:y:2020:i:c:s0360544220310185

DOI: 10.1016/j.energy.2020.117911

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 ().