Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi

• Main Author: Mahmud Affandi, Muhamad Saifullah
• Format: Article
• Language: English
• Published: UiTM Press 2014
• Subjects: Neural networks (Computer science)
• Online Access: https://ir.uitm.edu.my/id/eprint/62964/1/62964.pdf; https://ir.uitm.edu.my/id/eprint/62964/; https://jeesr.uitm.edu.my/v1/

Distributed Generator (DG) had created a challenge and an opportunity for developing various novel technologies in power generation. DG is installed to improve the voltage profile as well as to minimize losses. DG allocation is a crucial factor in distribution loss management. The optimum DG allocation provides a variety of benefits. This paper presents a computational intelligence technique for DG installation within contingency scenario. A contingency scenario study of DG deployment in the distribution network for reducing real power losses has been considered and evaluated. The Artificial Bee Colony (ABC) algorithm technique for solving the problem of optimal location and sizing of DG on distributed systems is presented. The objective is to minimize transmission power loss under the contingency scenario. This proposed technique will be compared with Evolutionary Programming (EP) algorithm, that usually designed to maximize or minimize the objective function, which is a measure of the quality of each candidate solution. Meanwhile, for ABC algorithm is inspired of the intelligent behavior of bees during the nectar search process. This operational coding was developed in MatLAB and conducted on the test system, that is IEEE 69-bus radial distribution system.