Applying the Crow Search Algorithm for the Optimal Integration of PV Generation Units in DC Networks

Luis Fernando Grisales-Noreña (), Brandon Cortés-Caicedo, Gerardo Alcalá and Oscar Danilo Montoya ()
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Luis Fernando Grisales-Noreña: Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile
Brandon Cortés-Caicedo: Departamento de Mecatrónica y Electromecánica, Facultad de Ingeniería, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
Gerardo Alcalá: Centro de Investigación en Recursos Energéticos y Sustentables, Universidad Veracruzana, Coatzacoalcos, Veracruz 96535, Mexico
Oscar Danilo Montoya: Grupo de Compatibilidad e Interferencia Electromagnética (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia

Mathematics, 2023, vol. 11, issue 2, 1-18

Abstract: This paper presents an efficient master–slave methodology to solve the problem of integrating photovoltaic (PV) generators into DC grids for a planning period of 20 years. The problem is mathematically formulated as Mixed-Integer Nonlinear Programming (MINLP) with the objective of minimizing the total annual operating cost. The main stage, consisting of a discrete-continuous version of the Crow search algorithm (DCCSA), is in charge of determining the installation positions of the PV generators and their corresponding power ratings. On the other hand, at the slave level, the successive approximation power flow method is used to determine the objective function value. Numerical results on 33- and 69-bus test systems demonstrate the applicability, efficiency and robustness of the developed approach with respect to different methodologies previously discussed in the scientific literature, such as the vortex search algorithm, the generalized normal distribution optimizer and the particle swarm optimization algorithm. Numerical tests are performed in the MATLAB programming environment using proprietary scripts.

Keywords: DC networks; PV generators; crow search algorithm; discrete-continuous codification; master–slave optimization; successive approximation power flow method; electrical systems planning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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