Application of the SSA for Optimal Reactive Power Compensation in Radial and Meshed Distribution Using D-STATCOMs

• Published in: Algorithms Vol. 15; no. 10; p. 345
• Main Authors: Mora-Burbano, Javier Andrés, Fonseca-Díaz, Cristian David, Montoya, Oscar Danilo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-10-2022
• Subjects: Algorithms; annual operating costs minimization; Compensation; Compensators; daily load curves; Decision making; distribution static compensators; Energy costs; Exact solutions; Genetic algorithms; Integer programming; Mathematical models; Mathematical programming; Methods; Mixed integer; Nonlinear programming; Operating costs; Optimization; Optimization algorithms; Optimization techniques; Power flow; Programming environments; radial and meshed distribution networks; Reactive power; salp swarm optimization algorithm
• ISSN: 1999-4893; 1999-4893
• DOI: 10.3390/a15100345

This paper deals with the problem regarding the optimal placement and sizing of distribution static compensators (D-STATCOMs) in radial and meshed distribution networks. These grids consider industrial, residential, and commercial loads within a daily operation scenario. The optimal reactive power flow compensation problem is formulated through a mixed-integer nonlinear programming (MINLP) model. The objective function is associated with the minimization of the expected energy losses costs for a year of operation by considering the investment costs of D-STATCOMs. To solve the MINLP model, the application of a master–slave optimization approach is proposed, which combines the salp swarm algorithm (SSA) in the master stage and the matricial backward/forward power flow method in the slave stage. The master stage is entrusted with defining the optimal nodal location and sizes of the D-STATCOMs, while the slave stage deals with the power flow solution to determine the expected annual energy losses costs for each combination of nodes and sizes for the D-STATCOMs as provided by the SSA. To validate the effectiveness of the proposed master–slave optimizer, the IEEE 33-bus grid was selected as a test feeder. Numerical comparisons were made against the exact solution of the MINLP model with different solvers in the general algebraic modeling system (GAMS) software. All the simulations of the master–slave approach were implemented in the MATLAB programming environment (version 2021b). Numerical results showed that the SSA can provide multiple possible solutions for the studied problem, with small variations in the final objective function, which makes the proposed approach an efficient tool for decision-making in distribution companies.