Short term forecasting based on hourly wind speed data using deep learning algorithms

Vikash Kumar Saini, Rajesh Kumar, Akhilesh Mathur, Akash Saxena

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

30 Citations (Scopus)

Abstract

Application of Internet of Things (IoT) in smart grid is evident in current trends. Smart grid management have greater impact on market economics, security, and distribution of energy. Smart grid is an integration of several components like, wind, solar, cyber-security etc. One of major concern in smart grid is optimal control of wind generation and accurate prediction of wind speed. This paper aims to predict the wind speed with meteorological time series data as input variable using deep learning topology for one-year wind speed data. The dynamic recurrent type network (RNN) integrates and processed with the Extreme Learning-Machine (ELM), nonlinear autoregressive network with exogenous inputs (NARX), and Long short-term memory (LSTM) model. Three models having the same Network's architecture, intermediate layer in architecture have 19 neurons and an activation function. Feature selection method is used for feature extraction from wind data (have four features as wind speed, pressure, humidity, air temperature) and applied to models. Comparative analysis of different models are assessed by performance matrices such as MAPE, MAE, and RMSE.

Original languageEnglish
Title of host publicationProceedings of 3rd International Conference on Emerging Technologies in Computer Engineering
Subtitle of host publicationMachine Learning and Internet of Things, ICETCE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages30-35
Number of pages6
ISBN (Electronic)9781728116839
DOIs
Publication statusPublished - Feb 2020
Externally publishedYes
Event3rd International Conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things, ICETCE 2020 - Jaipur, India
Duration: 7 Feb 20208 Feb 2020

Publication series

NameProceedings of 3rd International Conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things, ICETCE 2020

Conference

Conference3rd International Conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things, ICETCE 2020
Country/TerritoryIndia
CityJaipur
Period7/02/208/02/20

Keywords

  • Deep Learning
  • LSTM
  • RNN
  • Wind Forecasting

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture

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