Abstract
In this paper, stochastic fractal search method (SFS) is employed for solving the optimal reactive power flow (ORPF) problem with a target of optimizing total active power losses (TPL), voltage deviation (VD), and voltage stability index (VSI). SFS is an effective metaheuristic algorithm consisting of diffusion process and two update processes. ORPF is a complex problem giving challenges to applied algorithms by taking into account many complex constraints such as operating voltage from generators and loads, active and reactive power generation of generators, limit of capacitors, apparent power limit from branches, and tap setting of transformers. For verifying the performance, solutions of IEEE 30 and 118-bus system with TPL, VD, and VSI objectives are found by the SFS method with different control parameter settings. Result comparisons indicate that SFS is more favorable than other methods about finding effective solutions and having faster speed. As a result, it is suggested that SFS should be used for ORPF problem, and modifications performed on SFS are encouraged for better results.
Highlights
In the power system, optimal reactive power flow (ORPF) is one of the best famous optimization problems and a very complex problem
We test the performance of the stochastic fractal search method (SFS) method for the ORPF problem with two systems having 30 buses and 118 buses under considering three objectives such as power loss, voltage deviation, and L-index. e method is executed on Matlab program language and a computer with the processor of Core i7, 2.4 GHz, and 4 GB of RAM
We implement the SFS method for optimizing total power losses, voltage deviation, and L-index of the IEEE 30-bus system by setting different values to control parameters such as population size, maximum iteration, and walk factor. e IEEE 30-bus system consists of 6 generators, 24 loads, and 41 branches, 9 VAR compensators, and 4 transformers [38]
Summary
Optimal reactive power flow (ORPF) is one of the best famous optimization problems and a very complex problem. In the ORPF problem, two variables need to be considered such as control variables and dependent variables. Control variables are voltage of generation buses, on load tap-changer setting of transformers and generated reactive power of capacitor banks, while dependent variables are voltage of load buses, apparent power flow of transmission lines, and reactive power of generators. The major objectives of such ORPF problem is to find control variable so that others have values falling into a permitted operating range [1, 2]. The ORPF problem concentrates on reducing three individual objectives such as power losses of transmission lines, voltage deviation, and voltage stability index. A power system economically and stably operates when these goals are fully achieved
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