Electric load forecasting using an artificial neural networks: Methods and solutions - Couverture souple

Gotman, Natalia; Shumilova, Galina; Starceva, Tatiana

 
9783659459382: Electric load forecasting using an artificial neural networks: Methods and solutions
Couverture souple
ISBN 10 : 3659459380 ISBN 13 : 9783659459382
Editeur : LAP LAMBERT Academic Publishing, 2014

Synopsis

Electric load forecasting is an important research field in electric power industry. It plays a crucial role in solving a wide range of tasks of short-term planning and operating control of electric power system operating modes. Load forecasting is carried out in different time spans. Load forecasting within a current day – operating forecasting; one-day-week-month-ahead load forecasting – short-term load forecasting; one-month-quarter-year-ahead load forecasting – long-term load forecasting. So far a great number of both conventional and non-conventional electric load forecasting methods and models have been developed. The work presents research results of electric load forecasting for electrical power systems using artificial neural networks and fuzzy logic as one of the most advanced and perspective directions of solving this task. A theoretical approach to the issues discussed is combined with the data of experimental studies implemented with application of load curves of regional electrical power systems. The book is addressed to specialists and researchers concerned with operational control modes of electric power systems.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Electric load forecasting is an important research field in electric power industry. It plays a crucial role in solving a wide range of tasks of short-term planning and operating control of electric power system operating modes. Load forecasting is carried out in different time spans. Load forecasting within a current day – operating forecasting; one-day-week-month-ahead load forecasting – short-term load forecasting; one-month-quarter-year-ahead load forecasting – long-term load forecasting. So far a great number of both conventional and non-conventional electric load forecasting methods and models have been developed. The work presents research results of electric load forecasting for electrical power systems using artificial neural networks and fuzzy logic as one of the most advanced and perspective directions of solving this task. A theoretical approach to the issues discussed is combined with the data of experimental studies implemented with application of load curves of regional electrical power systems. The book is addressed to specialists and researchers concerned with operational control modes of electric power systems.

Biographie de l'auteur

Galina P. Shumilova, Ph.D. (Technical Sciences), St.PSTU, a senior researcher at the ISE&EPN Komi SC UB RAS, Syktyvkar, the Russian Federation (RF).Natalia E. Gotman, SSU, a research fellow of the ISE&EPN Komi SC UB RAS, Syktyvkar, the RF.Tatiana B. Starceva, Komi SPI, a research fellow of the ISE&EPN Komi SC UB RAS, Syktyvkar, the RF.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2014
Langue
anglais
ISBN 10 
3659459380
ISBN 13 
9783659459382
Reliure
Broché
Nombre de pages
100
Coordonnées du fabricant
non disponible
Personne responsable
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