Optimal power flow using gravitational search algorithm

By Serhat Duman, Ugur Güvenc, Yusuf Sönmez, N. Yorukeren. 2012

538 citations recorded by the source corpus.

In this paper, gravitational search algorithm (GSA) is proposed to find the optimal solution for optimal power flow (OPF) problem in a power system. The proposed approach is applied to determine the optimal settings of control variables of the OPF problem. The performance of the proposed approach examined and tested on the standard IEEE 30-bus and 57-bus test systems with different objective functions and is compared to other heuristic methods reported in the literature recently. Simulation results obtained from the proposed GSA approach indicate that GSA provides effective and robust high-quality solution for the OPF problem.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/f5d90c6a42f5e4d53d2316b66291726547f65f09

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. A. E. Chaib
2. M. A. Abido
3. H. Bouchekara
4. R. Mehasni

Citations in the corpus

• Optimal power flow with emission and non-smooth cost functions using backtracking search optimization algorithm (2016, background): “Some of the recent applications of metaheuristics to OPF problem are: Artificial Bee Colony (ABC) [5,6], Black Hole (BH) [7], Teaching Learning Based Optimization (TLBO) [8], League Championship Algorithm (LCA) [9], Differential Search Algorithm (DSA) [10], Krill Herd Algorithm (KHA) [11], Gravitati”