Abstract
The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.
Highlights
The electrical power system is a complex system consisting of subsystems, such as generation plants and transmission networks
A comparison of these results showed that the value of power losses obtained by the proposed IMPAPSO optimization algorithm was the best among the results obtained by the other algorithms, especially the BFOA
A comparison of these results showed that the value of power losses obtained by the proposed IMPAPSO optimization algorithm was the best among the Transformer Setting at Branch 11 1.099993675
Summary
The electrical power system is a complex system consisting of subsystems, such as generation plants and transmission networks. In [55], modifications were made to the social spider optimization (SSO) method on how the algorithm generates new solutions This was used for solving the ORPD problem with the IEEE 30- and 118-bus systems. It required huge number of iterations, especially with nonlinear optimization problems For solving this point, an improved version of the MPA was proposed, based on distribution and particle swarm optimization. An improved marine predators algorithm and particle swarm optimization (IMPAPSO) method was introduced in this study. This was a salient and new contribution of this research work.
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