Long-Term Electrical Energy Forecasting of the Residential Sector Using the LSTM Model: The Italian Use Case
Author:
Affiliation:
1. Università degli Studi di Brescia,Department of Information Engineering,Brescia,Italy
2. Physics named after Professor I.S. Surovtseva Voronezh State Technical University,Department of Innovation and Building,Voronezh,Russian Federation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10182286/10182373/10182653.pdf?arnumber=10182653
Reference26 articles.
1. Methods of day ahead load forecasting on the example of a residential area
2. Spillover Effects among Electricity Prices, Traditional Energy Prices and Carbon Market under Climate Risk
3. Predicting Electricity Consumption in Residential Building’s Using Deep Transfer Learning with Attention-LSTM
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