Optimal Generation Dispatch of Ethiopian Power System Using Hybrid Genetic Algorithm-Hopfield Neural Network
In this paper, an optimal generation dispatch of the Ethiopian power system using a hybrid Genetic Algorithm-Hopfield Neural Network (GA-HNN) is presented to reduce recursive blackouts. Reformulation of generation dispatch for a power grid comprising biomass, hydro, solar, waste...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
European Alliance for Innovation (EAI)
2022
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/6050e83a0a8b4eafb382150a8db4cd1f |
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| Sumario: | In this paper, an optimal generation dispatch of the Ethiopian power system using a hybrid Genetic Algorithm-Hopfield Neural Network (GA-HNN) is presented to reduce recursive blackouts. Reformulation of generation dispatch for a power grid comprising biomass, hydro, solar, waste to energy plant, wind and geothermal have been carried out. Each of these sources requires a mathematical formulation that considers security limits and intermittency of renewables. Modelling and simulation was conducted on MATLAB. According to the simulation results obtained, it can be deduced that GA-HNN based optimal generation dispatch of Ethiopian power system is a key solution in connection to developments needed in the adoption and realization of smarter grids as it concurrently increases its security level and decreases total generation cost. Generally, reducing the number of recursive blackouts, decreasing generation cost, allocating optimal generation level, and reducing computation time are prospects of employing GA-HNN based OGD. |
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