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This paper addresses the optimal power flow problem in direct current (DC) networks employing a master–slave solution methodology that combines an optimization algorithm based on the multiverse theory (master stage) and the numerical method of successive approximation (slave stage). The master stage proposes power levels to be injected by each distributed generator in the DC network, and the slave stage evaluates the impact of each power configuration (proposed by the master stage) on the objective function and the set of constraints that compose the problem. In this study, the objective function is the reduction of electrical power losses associated with energy transmission. In addition, the constraints are the global power balance, nodal voltage limits, current limits, and a maximum level of penetration of distributed generators. In order to validate the robustness and repeatability of the solution, this study used four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: ant lion optimization, particle swarm optimization, continuous genetic algorithm, and black hole optimization algorithm. All of them employed the method based on successive approximation to solve the load flow problem (slave stage). The 21- and 69-node test systems were used for this purpose, enabling the distributed generators to inject
Andrés Rosales-Muñoz; Luis Grisales-Noreña; Jhon Montano; Oscar Montoya; Alberto-Jesus Perea-Moreno. Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks. Sustainability 2021, 13, 8703 .
AMA StyleAndrés Rosales-Muñoz, Luis Grisales-Noreña, Jhon Montano, Oscar Montoya, Alberto-Jesus Perea-Moreno. Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks. Sustainability. 2021; 13 (16):8703.
Chicago/Turabian StyleAndrés Rosales-Muñoz; Luis Grisales-Noreña; Jhon Montano; Oscar Montoya; Alberto-Jesus Perea-Moreno. 2021. "Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks." Sustainability 13, no. 16: 8703.
This paper presents an accurate application of the Grasshopper Optimization Algorithm (GOA) for estimating the optimal parameters of the single diode model (SDM) of a photovoltaic (PV) module from experimental data, which as is well known, and its non-linear current vs voltage (I–V) profile make its modeling challenging. The accuracy and execution time obtained with GOA were compared with metaheuristic techniques such as genetic algorithm (GA) and particle swarm optimization algorithm (PSO). The analysis and validation were effectuated on four different types of PV modules for each optimization algorithm, confirming a good relation between computational time and reliability of GOA in estimating the parameters of the PV module.
Jhon Jairo Rojas Montano; A. F. Tobón; Juan Villegas; M. Durango. Grasshopper optimization algorithm for parameter estimation of photovoltaic modules based on the single diode model. International Journal of Energy and Environmental Engineering 2020, 11, 367 -375.
AMA StyleJhon Jairo Rojas Montano, A. F. Tobón, Juan Villegas, M. Durango. Grasshopper optimization algorithm for parameter estimation of photovoltaic modules based on the single diode model. International Journal of Energy and Environmental Engineering. 2020; 11 (3):367-375.
Chicago/Turabian StyleJhon Jairo Rojas Montano; A. F. Tobón; Juan Villegas; M. Durango. 2020. "Grasshopper optimization algorithm for parameter estimation of photovoltaic modules based on the single diode model." International Journal of Energy and Environmental Engineering 11, no. 3: 367-375.
This article presents a method for the Maximum Power Point Tracking (MPPT) of a Photovoltaic (PV) panels array with partial shading, applying an Improved Pattern Search Method (IPSM). The method is simulated in PSIM @ and then implemented in hardware in the loop system, emulating the PV array on an industrial computer (Speedgoat) that allows real-time emulations and the IPSM is applied in an Arduino DUE. The experiments were carried out with TP245S-20/WD, KYOCERA KC200GT, YINGLY SOLAR JS65, and MSX60 photovoltaic panels. The results are the proper MPPT with changes in partial shading over time, inducing the increase and decrease of the maximum power point. The results obtained are the search for the global maximum power point in a matrix of panels in which, due to partial shading, it might have several local maximum power points, and thanks to the IPSM algorithm, it always manages to find the global maximum power point. Finally, the results are compared with other methods where it was found that IPSM had faster answers.
Andrés Tobón; Julián Peláez-Restrepo; Jhon Jairo Rojas Montano; Mariana Durango; Jorge Herrera; Asier Ibeas. MPPT of a Photovoltaic Panels Array with Partial Shading Using the IPSM with Implementation Both in Simulation as in Hardware. Energies 2020, 13, 815 .
AMA StyleAndrés Tobón, Julián Peláez-Restrepo, Jhon Jairo Rojas Montano, Mariana Durango, Jorge Herrera, Asier Ibeas. MPPT of a Photovoltaic Panels Array with Partial Shading Using the IPSM with Implementation Both in Simulation as in Hardware. Energies. 2020; 13 (4):815.
Chicago/Turabian StyleAndrés Tobón; Julián Peláez-Restrepo; Jhon Jairo Rojas Montano; Mariana Durango; Jorge Herrera; Asier Ibeas. 2020. "MPPT of a Photovoltaic Panels Array with Partial Shading Using the IPSM with Implementation Both in Simulation as in Hardware." Energies 13, no. 4: 815.