Objective: The objective of this paper is to propose a methodology for the optimal location and sizing of D-STATCOMs within a distribution electrical system, with the aim to reduce the annualized operating costs related to the annual power energy losses and the investment costs associated with the installation of the D-STATCOM.
Context: This paper presents a hybrid methodology based on a master-slave strategy and the genetic and particle swarm optimization algorithms for solving the problem of optimal location and sizing of Distribution Static Compensators (DSTATCOMs), for reactive compensation in electrical distribution systems.
Methodology: In this paper was used a mathematical formulation that represents the effect of the location and sizing of D-STATCOMs in electrical distribution systems; by proposing a master-slave methodology combining the genetic algorithm and the particle swarm optimization algorithms as a solution method. Furthermore, with the aim to validate the effectiveness and robustness of the proposed methodology in this work, three comparison methods, two test systems, and multiple technical considerations were used to represent the electrical distribution systems in a distributed energy resource environment.
Results: The results obtained show that the proposed methodology is the most effective solution method for solving the problem, by achieving the greatest reduction in relation to the investment and operating costs. This methodology will allow the grid operators to identify the location and size of the D-STATCOMs within the electrical energy distribution system, with the lowest investment and operating costs in relation to other works reported in specialized literature.
Conclusions: The obtained results demonstrate that GA/PSO achieved the best performance, with the DCVSA comparison method in second place, and the GAMS solvers in third place. It is important to notice that it was not possible to evaluate the GAMS solvers on the 69 bus test system, because this solver failed the mathematical formulation that represented this electrical system. Based on previous results, it can be concluded that the GA/PSO is the most suitable optimization method used for solving the problem of optimal integration of D-STATCOMs in Distribution electrical systems for the grid.
