Compensación de potencia reactiva en redes de distribución de media tensión con condensadores conmutados por tiristores considerando perfiles de demanda variable mediante el algoritmo de búsqueda del águila calva

Abstract

This research document addresses the challenge of reactive power compensation in electrical distribution networks from a metaheuristic optimization perspective. A discrete-continuous version of the bald eagle search (BES) algorithm is used to optimize the placement and sizing of thyristor switched capacitors (TSCs). The proposed approach employs a discrete-continuous encoding of the solution vector, where the discrete part determines the nodes for the installation of the TSCs, while the continuous part defines their appropriate sizes. A key advantage of this encoding is that the mixed-integer nonlinear programming (MINLP) model, which represents the optimal placement and sizing problem of the TSCs, only requires a classical power flow method to evaluate the objective function. This simplifies its implementation in any available programming language. The objective function seeks to minimize the total costs of power losses in the network and the annualized investment costs in TSCs. In addition, to account for daily load variations, active and reactive power demand curves are incorporated into the optimization model. The numerical results obtained on two test radial feeders, with 33 and 69 buses, demonstrate that the proposed BES can solve the MINLP model with excellent results, comparable or even better than the MINLP solvers available in GAMS software. All tests were carried out in the MATLAB software programming environment, taking advantage of its potential and flexibility. This approach offers an effective and efficient solution to address the problem of reactive power compensation in electrical distribution networks.