Deep Learning Based Short- Term Load Forecasting for Urban Areas

M. Maksut; A. Karbozov; M. Myrzaliyeva; H. S.V.S.Kumar Nunna; Prashant K. Jamwal; Suryanarayana Doolla

doi:10.1109/IAS.2019.8912321

Deep Learning Based Short- Term Load Forecasting for Urban Areas

M. Maksut, A. Karbozov, M. Myrzaliyeva, H. S.V.S.Kumar Nunna, Prashant K. Jamwal, Suryanarayana Doolla

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper proposes a short-term load forecasting for residential applications. Deep learning is considered to be a powerful method in forecasting electricity load. As the present state of deep learning is still in progress, new updates towards improving the accuracy of the load forecasting are significantly important. Therefore, this paper proposes a restricted Boltzmann pre-training method and a rectifier linear unit method to enhance the current structure of Deep Neural Network (DNN) method. Moreover, making a priority list of factors that influence residential electricity consumption based on a location (London) is performed and analyzed in the paper.

Original language	English
Title of host publication	2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538645390
DOIs	https://doi.org/10.1109/IAS.2019.8912321
Publication status	Published - Sep 2019
Event	2019 IEEE Industry Applications Society Annual Meeting, IAS 2019 - Baltimore, United States Duration: Sep 29 2019 → Oct 3 2019

Publication series

Name	2019 IEEE Industry Applications Society Annual Meeting, IAS 2019

Conference

Conference	2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
Country	United States
City	Baltimore
Period	9/29/19 → 10/3/19

Keywords

Artificial Neural Network (ANN)
Deep Neural Network (DNN)
Rectifier Linear Unit (ReLU)
restricted Boltzmann machine pre-training
Short term load forecasting (STLF)

ASJC Scopus subject areas

Filtration and Separation
Fluid Flow and Transfer Processes
Process Chemistry and Technology
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Industrial and Manufacturing Engineering
Transportation

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Maksut, M., Karbozov, A., Myrzaliyeva, M., Nunna, H. S. V. S. K., Jamwal, P. K., & Doolla, S. (2019). Deep Learning Based Short- Term Load Forecasting for Urban Areas. In 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019 [8912321] (2019 IEEE Industry Applications Society Annual Meeting, IAS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS.2019.8912321

Deep Learning Based Short- Term Load Forecasting for Urban Areas. / Maksut, M.; Karbozov, A.; Myrzaliyeva, M.; Nunna, H. S.V.S.Kumar ; Jamwal, Prashant K.; Doolla, Suryanarayana.

2019 IEEE Industry Applications Society Annual Meeting, IAS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8912321 (2019 IEEE Industry Applications Society Annual Meeting, IAS 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Maksut, M, Karbozov, A, Myrzaliyeva, M, Nunna, HSVSK , Jamwal, PK & Doolla, S 2019, Deep Learning Based Short- Term Load Forecasting for Urban Areas. in 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019., 8912321, 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019, Baltimore, United States, 9/29/19. https://doi.org/10.1109/IAS.2019.8912321

Maksut M, Karbozov A, Myrzaliyeva M, Nunna HSVSK , Jamwal PK, Doolla S. Deep Learning Based Short- Term Load Forecasting for Urban Areas. In 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8912321. (2019 IEEE Industry Applications Society Annual Meeting, IAS 2019). https://doi.org/10.1109/IAS.2019.8912321

Maksut, M. ; Karbozov, A. ; Myrzaliyeva, M. ; Nunna, H. S.V.S.Kumar ; Jamwal, Prashant K. ; Doolla, Suryanarayana. / Deep Learning Based Short- Term Load Forecasting for Urban Areas. 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE Industry Applications Society Annual Meeting, IAS 2019).

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title = "Deep Learning Based Short- Term Load Forecasting for Urban Areas",

abstract = "This paper proposes a short-term load forecasting for residential applications. Deep learning is considered to be a powerful method in forecasting electricity load. As the present state of deep learning is still in progress, new updates towards improving the accuracy of the load forecasting are significantly important. Therefore, this paper proposes a restricted Boltzmann pre-training method and a rectifier linear unit method to enhance the current structure of Deep Neural Network (DNN) method. Moreover, making a priority list of factors that influence residential electricity consumption based on a location (London) is performed and analyzed in the paper.",

keywords = "Artificial Neural Network (ANN), Deep Neural Network (DNN), Rectifier Linear Unit (ReLU), restricted Boltzmann machine pre-training, Short term load forecasting (STLF)",

author = "M. Maksut and A. Karbozov and M. Myrzaliyeva and Nunna, {H. S.V.S.Kumar} and Jamwal, {Prashant K.} and Suryanarayana Doolla",

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AB - This paper proposes a short-term load forecasting for residential applications. Deep learning is considered to be a powerful method in forecasting electricity load. As the present state of deep learning is still in progress, new updates towards improving the accuracy of the load forecasting are significantly important. Therefore, this paper proposes a restricted Boltzmann pre-training method and a rectifier linear unit method to enhance the current structure of Deep Neural Network (DNN) method. Moreover, making a priority list of factors that influence residential electricity consumption based on a location (London) is performed and analyzed in the paper.

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Deep Learning Based Short- Term Load Forecasting for Urban Areas

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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