Forecast of the demand for hourly electric energy by artificial neural networks
Artículo de revista
2020
Corporación Universidad de la Costa
Obtaining an accurate forecast of the energy demand is fundamental to support the several decision processes of the electricity service agents in a country. For market operators, a greater precision in the short-term load forecasting implies a more efficient programming of the electricity generation resources, which means a reduction in costs. In the long term, it constitutes a main indicator for the generation of investment signals for future installed capacity. This research proposes a prognostic model for the demand of electrical energy in Bogota, Colombia at hourly level in a full week, through Artificial Neural Network.
- Artículos científicos [3154]
Descripción:
Forecast of the demand for hourly electric energy by artificial neural networks.pdf
Título: Forecast of the demand for hourly electric energy by artificial neural networks.pdf
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Título: Forecast of the demand for hourly electric energy by artificial neural networks.pdf
Tamaño: 166.2Kb
PDFLEER EN FLIP
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