This work is licensed under the Creative Commons Attribution 4.0 International License.
Butt, O. M., Zulqarnain, M., & Butt, T. M. (2021). Recent advancement in smart grid technology: Future prospects in the electrical power network. Ain Shams Engineering Journal, 12(1), 687-695.Search in Google Scholar
Judge, M. A., Khan, A., Manzoor, A., & Khattak, H. A. (2022). Overview of smart grid implementation: Frameworks, impact, performance and challenges. Journal of Energy Storage, 49, 104056.Search in Google Scholar
Dileep, G. J. R. E. (2020). A survey on smart grid technologies and applications. Renewable energy, 146, 2589-2625.Search in Google Scholar
Moharm, K. (2019). State of the art in big data applications in microgrid: A review. Advanced Engineering Informatics, 42, 100945.Search in Google Scholar
Tu, C., He, X., Shuai, Z., & Jiang, F. (2017). Big data issues in smart grid–A review. Renewable and Sustainable Energy Reviews, 79, 1099-1107.Search in Google Scholar
Kezunovic, M., Pinson, P., Obradovic, Z., Grijalva, S., Hong, T., & Bessa, R. (2020). Big data analytics for future electricity grids. Electric Power Systems Research, 189, 106788.Search in Google Scholar
Munshi, A. A., & Yasser, A. R. M. (2017). Big data framework for analytics in smart grids. Electric Power Systems Research, 151, 369-380.Search in Google Scholar
Bhattarai, B. P., Paudyal, S., Luo, Y., Mohanpurkar, M., Cheung, K., Tonkoski, R., ... & Zhang, X. (2019). Big data analytics in smart grids: state‐of‐the‐art, challenges, opportunities, and future directions. IET Smart Grid, 2(2), 141-154.Search in Google Scholar
Hossain, E., Khan, I., Un-Noor, F., Sikander, S. S., & Sunny, M. S. H. (2019). Application of big data and machine learning in smart grid, and associated security concerns: A review. Ieee Access, 7, 13960-13988.Search in Google Scholar
Daki, H., El Hannani, A., Aqqal, A., Haidine, A., & Dahbi, A. (2017). Big Data management in smart grid: concepts, requirements and implementation. Journal of Big Data, 4, 1-19.Search in Google Scholar
Zhang, Y., Huang, T., & Bompard, E. F. (2018). Big data analytics in smart grids: a review. Energy informatics, 1(1), 1-24.Search in Google Scholar
Syed, D., Zainab, A., Ghrayeb, A., Refaat, S. S., Abu-Rub, H., & Bouhali, O. (2020). Smart grid big data analytics: Survey of technologies, techniques, and applications. IEEE Access, 9, 59564-59585.Search in Google Scholar
Chhaya, L., Sharma, P., Kumar, A., & Bhagwatikar, G. (2021). Application of data mining in smart grid technology. In Encyclopedia of Information Science and Technology, Fifth Edition (pp. 815-827). IGI Global.Search in Google Scholar
Liu, Y., Wang, G., Guo, W., Zhang, Y., Dong, W., Wang, Y., & Zeng, Z. (2021). Power data mining in smart grid environment. Journal of Intelligent & Fuzzy Systems, 40(2), 3169-3175.Search in Google Scholar
Qi, Y., Ren, J., Sun, N., & Yu, Y. (2021, July). Application of clustering algorithm by data mining in the Analysis of smart grid from the perspective of electric power. In Journal of Physics: Conference Series (Vol. 1982, No. 1, p. 012018). IOP Publishing.Search in Google Scholar
Memari Mehran,Karimi Ali & Hashemi-Dezaki Hamed. (2022). Clustering-based reliability assessment of smart grids by fuzzy c-means algorithm considering direct cyber–physical interdependencies and system uncertainties. Sustainable Energy, Grids and Networks.Search in Google Scholar
Ziheng Wu,Zhongcheng Wu & Jun Zhang. (2017). An improved FCM algorithm with adaptive weights based on SA-PSO. Neural Computing and Applications(10),3113-3118.Search in Google Scholar
Tiwari Anoop Kumar,Saini Rajat,Nath Abhigyan,Singh Phool & Shah Mohd Asif. (2024). Hybrid similarity relation based mutual information for feature selection in intuitionistic fuzzy rough framework and its applications. Scientific Reports(1),5958-5958.Search in Google Scholar
JiapingYang,DongpingRen,YongLiu,HailongZhou & YunquanSun. (2024). Research on PSO‐SVM base wine grade recognition based on Max‐Relevance and Min‐Redundancy feature selection. Concurrency and Computation: Practice and Experience(17).Search in Google Scholar
Hongyi Li,Shenhao Li,Yuxin Wu,Yue Xiao,Zhichong Pan & Min Liu. (2024). Short-term power load forecasting for integrated energy system based on a residual and attentive LSTM-TCN hybrid network. Frontiers in Energy Research.Search in Google Scholar
B. Hadjaissa,K. Ameur,S. M. Ait cheikh & N. Essounbouli. (2016). Bi-objective optimization of maintenance scheduling for power systems. The International Journal of Advanced Manufacturing Technology(5-8),1361-1372.Search in Google Scholar