A Review of Conventional, Modern and Big Data Analytics Techniques for  Short Term Load Forecasting in Smart Grid

Firoz Mohammed, Kamlesh Gupta, Namrata Nebhnani, Priya Pal

A Review of Conventional, Modern and Big Data Analytics Techniques for Short Term Load Forecasting in Smart Grid

Authors

Firoz Mohammed, Kamlesh Gupta, Namrata Nebhnani, Priya Pal

Keywords:

Load Forecasting, Artificial intelligent, Big Data, Data Analytics.

Abstract

Electric load forecasting is a very important part of smart grids. With the help of shortterm load forecasting, electric load from half an hour’s to several hours can be predicated. Thispaper is focused on full comparison among the different techniques of electric load forecasting

References

Changhao Xia, Jian Wang, Karen McMenemy, “Short, medium and long term load forecasting model and virtual load forecaster based on radial basis function neural networks”, Elsevier, Electrical Power and Energy Systems 32 (2010) 743–750

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Published

2019-05-15

How to Cite

Firoz Mohammed, Kamlesh Gupta, Namrata Nebhnani, Priya Pal. (2019). A Review of Conventional, Modern and Big Data Analytics Techniques for Short Term Load Forecasting in Smart Grid . Journal of Computational Analysis and Applications (JoCAAA), 26(5), 1–13. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3286