An Intelligent and Efficient ANN Approach | Short Term Electric Load Forecasting. Este artículo no está disponible.
Idioma: inglés
Editorial: LAP LAMBERT Academic Publishing, 2017
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- Nuevo

Librería: preigu, Osnabrück, Alemaniapreigu
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An Intelligent and Efficient ANN Approach | Short Term Electric Load Forecasting | Medha Joshi (u. a.) | Taschenbuch | 148 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659944864 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
N° de ref. del artículo 108251933
- Título
- An Intelligent and Efficient ANN Approach | Short Term Electric Load Forecasting
- Autor
- Medha Joshi (u. a.)
- Editorial
- LAP LAMBERT Academic Publishing
- Año de publicación
- 2017
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 3659944866
- ISBN 13
- 9783659944864
- Peso del artículo
- 238 gramos
- Dimensiones
- 220 x 150 x 10 mm
- Catálogos de vendedores
- Bücher
Load forecasting is very important for decision processes in the electricity sector. STELF provides an accurate estimate for the operating of the power system and also a basis for energy transactions and decision making in energy markets. It is also very important for daily maintenance of power plants because most of the decisions, like the unit commitment, load shedding and the economic load dispatch is necessarily based on forecasts of future demands. As seen in the literatures, conventional approaches, like the regression model and the time-series based models, are not very suitable because of the complexity and labour involved in modeling. So in this proposed work, to fulfill the requirement of accurate forecast, an ANN approach was used to forecast the next hour electrical load for Safdarjang, New Delhi region.
“Sinopsis” puede pertenecer a otra edición de este título.
Reseña del editor
Load forecasting is very important for decision processes in the electricity sector. STELF provides an accurate estimate for the operating of the power system and also a basis for energy transactions and decision making in energy markets. It is also very important for daily maintenance of power plants because most of the decisions, like the unit commitment, load shedding and the economic load dispatch is necessarily based on forecasts of future demands. As seen in the literatures, conventional approaches, like the regression model and the time-series based models, are not very suitable because of the complexity and labour involved in modeling. So in this proposed work, to fulfill the requirement of accurate forecast, an ANN approach was used to forecast the next hour electrical load for Safdarjang, New Delhi region.
“Acerca de” puede pertenecer a otra edición de este título.