Short-Term Load Forecasting Based on Deep Neural Networks Using LSTM Layer

Author:

Kwon Bo-Sung,Park Rae-Jun,Song Kyung-Bin

Funder

KETEP

Korea Electric Power Corporation

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Reference39 articles.

1. Mocanu E, Nguyen PH, Gibescu M, Kling WL (2016) Deep learning for estimating building energy consumption. Sustain Energy Grids Netw 6:91–99

2. Korea Power Exchange (2011) A study on short-term load forecasting technique and its application

3. Ribeiro GH, Neto PSDM, Cavalcanti GD (2011) Lag selection for time series forecasting using particle swarm optimization. In: Proceedings of the IEEE 2011 IJCNN, San Jose, CA, USA, Aug 2011

4. Box GE, Jenkins GM, Reinsel GC (2015) Time series analysis: forecasting and control. Wiley, Hoboken

5. Chen JF, Wang WM, Huang CM (1995) Analysis of an adaptive time-series autoregressive moving-average(ARMA) model for short-term load forecasting. Electr Power Syst Res 34:187–196

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