Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method
This paper addresses the Optimal Power Flow (OPF) problem in Direct Current (DC) networks by considering the integration of Distributed Generators (DGs). In order to model said problem, this study employs a mathematical formulation that has, as the objective function, the reduction in power losses a...
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MDPI AG
2021-11-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/22/2837 |
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| author | Andrés Alfonso Rosales Muñoz Luis Fernando Grisales-Noreña Jhon Montano Oscar Danilo Montoya Diego Armando Giral-Ramírez |
| author_facet | Andrés Alfonso Rosales Muñoz Luis Fernando Grisales-Noreña Jhon Montano Oscar Danilo Montoya Diego Armando Giral-Ramírez |
| author_sort | Andrés Alfonso Rosales Muñoz |
| collection | DOAJ |
| description | This paper addresses the Optimal Power Flow (OPF) problem in Direct Current (DC) networks by considering the integration of Distributed Generators (DGs). In order to model said problem, this study employs a mathematical formulation that has, as the objective function, the reduction in power losses associated with energy transport and that considers the set of constraints that compose DC networks in an environment of distributed generation. To solve this mathematical formulation, a master–slave methodology that combines the Salp Swarm Algorithm (SSA) and the Successive Approximations (SA) method was used here. The effectiveness, repeatability, and robustness of the proposed solution methodology was validated using two test systems (the 21- and 69-node systems), five other optimization methods reported in the specialized literature, and three different penetration levels of distributed generation: 20%, 40%, and 60% of the power provided by the slack node in the test systems in an environment with no DGs (base case). All simulations were executed 100 times for each solution methodology in the different test scenarios. The purpose of this was to evaluate the repeatability of the solutions provided by each technique by analyzing their minimum and average power losses and required processing times. The results show that the proposed solution methodology achieved the best trade-off between (minimum and average) power loss reduction and processing time for networks of any size. |
| first_indexed | 2024-03-10T05:32:34Z |
| format | Article |
| id | doaj.art-7990777a77744197bbbf840ca9868fe7 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T05:32:34Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-7990777a77744197bbbf840ca9868fe72023-11-22T23:07:49ZengMDPI AGElectronics2079-92922021-11-011022283710.3390/electronics10222837Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation MethodAndrés Alfonso Rosales Muñoz0Luis Fernando Grisales-Noreña1Jhon Montano2Oscar Danilo Montoya3Diego Armando Giral-Ramírez4Department of Electromechanical and Mechatronic, Faculty of Engineering, Instituto Tecnológico Metropolitano, Robledo Campus, Medellín 050036, ColombiaDepartment of Electromechanical and Mechatronic, Faculty of Engineering, Instituto Tecnológico Metropolitano, Robledo Campus, Medellín 050036, ColombiaDepartment of Electronics and Telecommunications, Instituto Tecnológico Metropolitano, Medellín 050028, ColombiaFacultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, ColombiaFacultad Tecnológica, Universidad Distrital Francisco José de Caldas, Bogotá 110231, ColombiaThis paper addresses the Optimal Power Flow (OPF) problem in Direct Current (DC) networks by considering the integration of Distributed Generators (DGs). In order to model said problem, this study employs a mathematical formulation that has, as the objective function, the reduction in power losses associated with energy transport and that considers the set of constraints that compose DC networks in an environment of distributed generation. To solve this mathematical formulation, a master–slave methodology that combines the Salp Swarm Algorithm (SSA) and the Successive Approximations (SA) method was used here. The effectiveness, repeatability, and robustness of the proposed solution methodology was validated using two test systems (the 21- and 69-node systems), five other optimization methods reported in the specialized literature, and three different penetration levels of distributed generation: 20%, 40%, and 60% of the power provided by the slack node in the test systems in an environment with no DGs (base case). All simulations were executed 100 times for each solution methodology in the different test scenarios. The purpose of this was to evaluate the repeatability of the solutions provided by each technique by analyzing their minimum and average power losses and required processing times. The results show that the proposed solution methodology achieved the best trade-off between (minimum and average) power loss reduction and processing time for networks of any size.https://www.mdpi.com/2079-9292/10/22/2837optimal power flowpower flow problemoptimization algorithmsDC networkselectrical energycombinatorial optimization |
| spellingShingle | Andrés Alfonso Rosales Muñoz Luis Fernando Grisales-Noreña Jhon Montano Oscar Danilo Montoya Diego Armando Giral-Ramírez Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method Electronics optimal power flow power flow problem optimization algorithms DC networks electrical energy combinatorial optimization |
| title | Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method |
| title_full | Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method |
| title_fullStr | Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method |
| title_full_unstemmed | Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method |
| title_short | Optimal Power Dispatch of Distributed Generators in Direct Current Networks Using a Master–Slave Methodology That Combines the Salp Swarm Algorithm and the Successive Approximation Method |
| title_sort | optimal power dispatch of distributed generators in direct current networks using a master slave methodology that combines the salp swarm algorithm and the successive approximation method |
| topic | optimal power flow power flow problem optimization algorithms DC networks electrical energy combinatorial optimization |
| url | https://www.mdpi.com/2079-9292/10/22/2837 |
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