Big Data Analytics for Smart Grid: A Review on State-of-Art Techniques and Future Directions

Author:

Umapathy K.,Sivakumar M.,Kumar T. Dinesh,Omkumar S.,Archana M. A.,Amannah Constance,Alkhayyat Ahmed Hussein

Publisher

Springer Nature Switzerland

Reference40 articles.

1. Yu, H., Wang, Z., Wei, W., Zhang, J.: A review of block chain technology for smart grid: State-of-the-art, challenges and future directions. J. Clean. Prod. 290, 125932–125940 (2021)

2. Zhang, Z., et al.: Demand response optimization in smart grid: A survey. IEEE Access 9, 105062–105076 (2021)

3. Kandil, A., Elsaid, M., Abdallah, H., Kim, H.: Machine learning-based demand response optimization techniques in smart grids: A comprehensive review. Energies 14(10), 3064–3070 (2021)

4. Liu, X., Chen, X., Chen, Y.: A survey of integration of big data analytics with smart grid. IEEE Access 9, 14310–14326 (2021)

5. Ma, J and Zhang, X, “A survey of artificial intelligence in smart grid”, Renewable and Sustainable Energy Reviews, 2021, Volume 145, pp.111031–111–37.

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