Evaluating LMP Forecasting with LSTM Networks: A Deep Learning Approach to Analyzing Electricity Prices During Unpredictable Events-Reference-Cited by-同舟云学术

Evaluating LMP Forecasting with LSTM Networks: A Deep Learning Approach to Analyzing Electricity Prices During Unpredictable Events

Published:2023-06-14 Issue: Volume: Page:
ISSN:
Container-title:2023 5th Global Power, Energy and Communication Conference (GPECOM)
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Author:

Yildirim Basak Ersoz¹,Yildiz Sevval¹,Turkoglu A. Selim²,Erdinc Ozan¹,Boynuegri Ali Rıfat³

Affiliation:

1. Yildiz Technical University,Faculty of Electrical and Electronics Engineering,Department of Electrical Engineering,Istanbul,Turkey,34220

2. Yildiz Technical University,Graduate School of Science and Engineering,Department of Energy Technologies,Istanbul,Turkey,34220

3. Faculty of Electrical and Electronics Engineering & Clean Energy Technologies Institute, Yildiz Technical University,Department of Electrical Engineering,Istanbul,Turkey,34220

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10175636/10175666/10175743.pdf?arnumber=10175743

Reference27 articles.

1. Electricity price short-term forecasting using artificial neural networks

2. A GARCH Forecasting Model to Predict Day-Ahead Electricity Prices

3. A Deep Learning Technique for Electricity Price Forecasting in Consideration of Spikes

4. A Hybrid Method of Clipping and Artificial Neural Network for Electricity Price Zone Forecasting

5. ARIMA Models to Predict Next-day Electricity Prices;contreas;IEEE Trans on Power Systems,2003

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