Advanced Methods of Power Load Forecasting

Format:

Book

Author/Creator:

García-Díaz, J. Carlos, Editor.

Contributor:

Trull, Óscar, Editor.

García-Díaz, J. Carlos

Trull, Óscar

Language:

English

Physical Description:

1 online resource (128 p.)

Place of Publication:

Basel MDPI - Multidisciplinary Digital Publishing Institute 2022

Language Note:

English

Summary:

This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load.

Access Restriction:

Open Access Unrestricted online access