Open AccessMulti‐distributed generation planning using hybrid particle swarm optimisation‐ gravitational search algorithm including voltage rise issue
Author(s) -
Tan Wen Shan,
Hassan Mohammad Yusri,
Rahman Hasimah Abdul,
Abdullah Md Pauzi,
Hussin Faridah
Publication year - 2013
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2013.0050
Subject(s) - particle swarm optimization , distributed generation , mathematical optimization , algorithm , computer science , population , range (aeronautics) , renewable energy , gravitational search algorithm , grid , voltage , engineering , mathematics , electrical engineering , demography , geometry , aerospace engineering , sociology
Distributed generation (DG) has been becoming more well‐known in the power sector because of its ability in power loss reduction, low investment cost, increase reliability, and most significantly, to exploit renewable‐energy resources. In this study, a multi‐objective index‐based approach for optimally determining the placement and size of multi‐DG units in distribution systems, including the voltage rise phenomenon is proposed. The proposed approach considers a wide range of technical aspects such as the total real power losses in the system, the voltage profile, the mega volt ampere intake by the grid, the DG quantity and the greenhouse gases emission. A novel hybrid population‐based algorithm with the combination of particle swarm optimisation (PSO), and gravitational search algorithm (GSA) is introduced. To reveal the validity of the hybrid PSO‐GSA, an analysis is carried out on 69‐bus systems then compared with results obtained by pre‐combined methods. The outcomes verify that the proposed algorithm is efficient, robust, and capable of handling mixed integer nonlinear optimisation problem.