Optimal allocation of distributed generation and remote control switches for reliability enhancement of a radial distribution system using oppositional differential search algorithm. Issue 8 (26th August 2015)

• Record Type: Journal Article
• Authors: Ray, Saheli; Bhattacharya, Aniruddha; Bhattacharjee, Subhadeep
• Is Part Of: Journal of engineering. Volume 2015:Issue 8(2015)
• Page Start: 261
• Page End: 275
• Publication Date: 2015-08-26
• Subjects: distributed power generation -- power distribution reliability -- search problems -- power markets -- optimisation -- power generation reliability -- computational complexity; distributed generation optimal allocation -- remote control switch -- oppositional differential search algorithm -- radial power distribution system reliability enhancement -- electricity market -- ODS algorithm -- multiobjective function -- opposition‐based DS algorithm -- opposition‐based learning -- superorganism initialisation -- computational efhciency; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2015.0097
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : Reliability enhancement of power distribution system has attained much significance in the present competitive electricity market. Accordingly, methodologies to assess and improve distribution system reliability are also gaining much importance. This study proposes oppositional differential search (ODS) algorithm to solve reliability optimisation problem of radial distribution system. The objective of this study is to obtain the optimum number, size and location of distributed generation as well as optimal number and location of remote control switch simultaneously in radial distribution system in order to improve system reliability at a compromised cost. A multi‐objective function has been formulated here. Differential search (DS) algorithm imitates the seasonal migration behaviour of an organism in search of efficiency of food areas. Opposition‐based DS (ODS) algorithm has been used here to improve the quality of solution in minimum time. The proposed opposition‐based DS (ODS) algorithm utilises opposition‐based learning for Superorganism initialisation and also for iteration wise update operation. Simulation results obtained by ODS algorithm have been compared with that of DS algorithm and differential evolutionary algorithm. Simulation results reveal that ODS algorithm provides considerably superior performance, in terms of quality of solution obtained and computational efficiency.