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Multi-objective Capacitor Allocations in Distribution Networks using Artificial Bee Colony Algorithm
El-Fergany, Attia,Abdelaziz, A.Y. The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.
Multi-objective Capacitor Allocations in Distribution Networks using Artificial Bee Colony Algorithm
Attia El-Fergany,A. Y. Abdelaziz 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.
Mohamed F. Kotb,Attia A. El‑Fergany 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.1
In this article, an efcient moth swarm-based optimal power fow (OPF) methodology is addressed. Three objectives are considered such as minimizations of (i) total fuel cost of production units including efects of valve ripples, (ii) emission rate, and (iii) network real power loss. Set of operating constraints are adapted considering production units’ prohibited zones to emulate real analysis along with security aspects. The moth swarm optimizer (MSO) is employed to generate the best values of the specifed design continuous and discrete control variables. Two test cases viz. IEEE 30-bus and 57-bus networks are demonstrated under various scenarios. The simulations are performed under MATLAB environment. Numerical simulations, subsequent discussions and appropriate comparisons to other methods indicate the viability of the proposed MSO-OPF tool. At last, the compulsory performance measures are made to confrm the observed performance of the MSO algorithm in solving OPF problem.