Sine-Cosine Algorithm for OPF Analysis in Distribution Systems to Size Distributed Generators
This paper addresses the analysis the optimal power flow (OPF) problem in alternating current (AC) radial distribution networks by using a new metaheuristic optimization technique known as a sine-cosine algorithm (SCA). This combinatorial optimization approach allows for solving the nonlinear non-co...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9183
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9183
- Palabra clave:
- Optimal power flow
Optimal sizing of distributed generation
Radial distribution networks
Sine-cosine algorithm
Soft computing optimization technique
Acoustic generators
Combinatorial optimization
Convex optimization
Distributed power generation
Electric impedance measurement
Electric load flow
Genetic algorithms
MATLAB
Particle size analysis
Particle swarm optimization (PSO)
Silicon compounds
Soft computing
Optimal power flows
Optimal sizing
Optimization techniques
Radial distribution networks
Sine-cosine algorithm
Electric load dispatching
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| Summary: | This paper addresses the analysis the optimal power flow (OPF) problem in alternating current (AC) radial distribution networks by using a new metaheuristic optimization technique known as a sine-cosine algorithm (SCA). This combinatorial optimization approach allows for solving the nonlinear non-convex optimization OPF problem by using a master-slave strategy. In the master stage, the soft computing SCA is used to define the power dispatch at each distributed generator (dimensioning problem). In the slave stage, it is used a conventional radial power flow formulated by incidence matrices is used for evaluating the total power losses (objective function evaluation). Two conventional highly used distribution feeders with 33 and 69 nodes are employed for validating the proposed master-slave approach. Simulation results are compared with different literature methods such as genetic algorithm, particle swarm optimization, and krill herd algorithm. All the simulations are performed in MATLAB programming environment, and their results show the effectiveness of the proposed approach in contrast to previously reported methods. © 2019, Springer Nature Switzerland AG. |
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