Detalhes bibliográficos
| Resumo: | Energy management in the microgrid system is generally formulated as an optimization problem. This paper focuses on the design of a distributed energy management system for the optimal operation of the microgrid using linear and nonlinear optimization methods. Energy management is defined as an optimal scheduling power flow problem. Furthermore, a technical-economic and environmental study is adopted to illustrate the impact of energy exchange between the microgrid and the main grid by applying two management scenarios. Nevertheless, the fluctuating effect of renewable resources especially wind, makes optimal scheduling difficult. To increase the results reliability of the energy management system, a wind forecasting model based on the artificial intelligence of neural networks is proposed. The simulation results showed the reliability of the forecasting model as well as the comparison between the accuracy of optimization methods to choose the most appropriate algorithm that ensures optimal scheduling of the microgrid generators in the two proposed energy management scenarios allowing to prove the interest of the bi-directionality between the microgrid and the main grid. |
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| Autores principais: | Amoura, Yahia |
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| Outros Autores: | Pereira, Ana I.; Lima, José |
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| Assunto: | Microgrid Energy management system Optimization algorithms Set-points Wind forcasting Artificial neural network |
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| Ano: | 2021 |
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| País: | Portugal |
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| Tipo de documento: | comunicação em conferência |
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| Tipo de acesso: | acesso aberto |
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| Instituição associada: | Instituto Politécnico de Bragança |
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| Idioma: | inglês |
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| Origem: | Biblioteca Digital do IPB |
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