Energy Management System for the Optimal Operation of PV Generators in Distribution Systems Using the Antlion Optimizer: A Colombian Urban and Rural Case Study

Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya (), Miguel Angel Rodriguez-Cabal and Javier Alveiro Rosero ()
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Brandon Cortés-Caicedo: Departamento de Mecatrónica y Electromecánica, Facultad de Ingeniería, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
Luis Fernando Grisales-Noreña: Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Campus Curicó 3340000, Chile
Oscar Danilo Montoya: Grupo de Compatibilidad e Interferencia Electromagnética (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia
Miguel Angel Rodriguez-Cabal: Departamento de Mecatrónica y Electromecánica, Facultad de Ingeniería, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
Javier Alveiro Rosero: Grupo de Investigación Electrical Machines & Drives (EM&D), Departamento de Ingeniería Eléctrica y Electrónica, Facultad de Ingeniería, Universidad Nacional de Colombia, Bogotá 111321, Colombia

Sustainability, 2022, vol. 14, issue 23, 1-35

Abstract: This paper presents an Energy Management System (EMS) for solving the problem regarding the optimal daily operation of Photovoltaic (PV) distributed generators in Alternate Current (AC) distribution grids. To this effect, a nonlinear programming problem (NLP) was formulated which considered the improvement of economic (investment and maintenance costs), technical (energy losses), and environmental ( C O 2 emission) grid indices as objective functions, considering all technical and operating constraints for the operation of AC networks with the presence of PV sources. To solve this mathematical formulation, a master–slave methodology was implemented, whose master stage employed the antlion optimizer to find the power dispatch of PV sources in each period of time considered (24 h). In the slave stage, an hourly power flow based on the successive approximations method was used in order to obtain the values of the objective functions and constraints associated with each possible PV power configuration proposed by the master stage. To evaluate the effectiveness and robustness of the proposed methodology, two test scenarios were used, which included three installed PV sources in an urban and a rural network, considering the PV power generation and demand located reported for Medellín and Capurganá, respectively. These systems correspond to connected and standalone grids located in two different regions of Colombia. Furthermore, the proposed methodology was compared with three optimization methodologies reported in the literature: the Chu and Beasley genetic algorithm, the particle swarm optimization algorithm, and the vortex search optimization algorithm. Simulation results were obtained via the MATLAB software for both test scenarios with all the optimization methodologies. It was demonstrated that the proposed methodology yields the best results in terms of solution quality and repeatability, with shorter processing times.

Keywords: distribution grids; photovoltaic generators; mathematical optimization; master–slave methodology; antlion optimizer; optimal power flow; minimization of operating costs; minimization of energy losses; minimization of CO 2 emissions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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