Black hole optimizer for the optimal power injection in distribution networks using DG

Montoya, Oscar Danilo; Ramı́rez, D.; Grisales-Noreña, Luis Fernando

doi:10.1088/1742-6596/2135/1/012010

Cited by 2 publications

(1 citation statement)

References 36 publications

(54 reference statements)

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“…However, in that paper, they did not compare the their results with those reported in other studies in the literature. The authors of [28] proposed a master-slave methodology that combines the black hole (BH) optimization algorithm and the triangular-based power flow method to solve the OPF problem in an AC network; their objective function was the reduction of power losses. The numerical results they obtained in the 33-and the 69-node test systems demonstrated the effectiveness and robustness of the proposed approach compared to those of others in the literature.…”

Section: State Of the Artmentioning

confidence: 99%

Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks

et al. 2022

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In this paper, we solve the optimal power flow problem in alternating current networks to reduce power losses. For that purpose, we propose a master–slave methodology that combines the multiverse optimization algorithm (master stage) and the power flow method for alternating current networks based on successive approximation (slave stage). The master stage determines the level of active power to be injected by each distributed generator in the network, and the slave stage evaluates the impact of the proposed solution on each distributed generator in terms of the objective function and the constraints. For the simulations, we used the 10-, 33-, and 69-node radial test systems and the 10-node mesh test system with three levels of distributed generation penetration: 20%, 40%, and 60% of the power provided by the slack generator in a scenario without DGs. In order to validate the robustness and convergence of the proposed optimization algorithm, we compared it with four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: Particle Swarm Optimization, the Continuous Genetic Algorithm, the Black Hole Optimization algorithm, and the Ant Lion Optimization algorithm. The results obtained demonstrate that the proposed master–slave methodology can find the best solution (in terms of power loss reduction, repeatability, and technical conditions) for networks of any size while offering excellent performance in terms of computation time.

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Section: State Of the Artmentioning

confidence: 99%

Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks

et al. 2022

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Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method

et al. 2022

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In this paper, we address the problem of the optimal power dispatch of Distributed Generators (DGs) in Alternating Current (AC) networks, better known as the Optimal Power Flow (OPF) problem. We used, as the objective function, the minimization of power losses (Ploss) associated with energy transport, which are subject to the set of constraints that compose AC networks in an environment of distributed generation. To validate the effectiveness of the proposed methodology in solving the OPF problem in any network topology, we employed one 10-node mesh test system and three radial text systems: 10, 33, and 69 nodes. In each test system, DGs were allowed to inject 20%, 40%, and 60% of the power supplied by the slack generator in the base case. To solve the OPF problem, we used a master–slave methodology that integrates the optimization method Salps Swarm Algorithm (SSA) and the load flow technique based on the Successive Approximation (SA) method. Moreover, for comparison purposes, we employed some of the algorithms reported in the specialized literature to solve the OPF problem (the continuous genetic algorithm, the particle swarm optimization algorithm, the black hole algorithm, the antlion optimization algorithm, and the Multi-Verse Optimizer algorithm), which were selected because of their excellent results in solving such problems. The results obtained by the proposed solution methodology demonstrate its superiority and convergence capacity in terms of minimization of Ploss in both radial and mesh systems. It provided the best reduction in minimum Ploss in short processing times and showed excellent repeatability in each test system and scenario under analysis.

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Black hole optimizer for the optimal power injection in distribution networks using DG

Cited by 2 publications

References 36 publications

Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks

Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks

Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method

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