Optimal power flow solution in power systems using a novel Sine-Cosine algorithm
By A. Attia, R. A. Sehiemy, Hany M. Hasanien. International Journal of Electrical Power & Energy Systems, 2018
329 citations recorded by the source corpus.
Abstract This paper presents the application of a novel algorithm, which is based on a modified Sine-Cosine technique for solving the optimal power flow (OPF) problem. It is a highly coupled non-linear constrained optimization problem. The modified Sine-Cosine algorithm (MSCA) aims at reducing the computational time with a sufficient improvement in finding the optimal solution and feasibility. Levy flights are added to the original Sine-Cosine algorithm to enhance the ability to focus on optimal and avoids local optima. Decreasing search agents number based on the objective function speeds up the MSCA. The MSCA presents a simple and robust solution for the OPF problem under different objective functions. The MSCA is validated with solving the OPF problem for a number of benchmark test systems, namely the IEEE-30 bus and IEEE 118-bus systems under selected objective functions, which are based on operational and economic performance indices of the power system. The proposed MSCA is compared with other optimization methods to illustrate the effectiveness and potential of the SCA and MSCA algorithms.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/1f76c1cfb9860de4e9442bda7775d47cdc5d991e
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In Electrical and Electronic Engineering
Citations in the corpus
- An improved grey wolf optimizer for solving engineering problems (2021, methodology): “The metaheuristic algorithms are applied for solving complex problems in different applications such as optimal power flow (Attia et al., 2018; A.-A. A. Mohamed et al., 2017; Nuaekaew et al., 2017), chip design (Fard et al., 2014; Venkataraman et al., 2020), feature selection (Arora et al., 2019;…”