EA, “Energy and AI,” Apr. 2025. Available : https://www.iea.org/

Ministry of Trade, Industry and Energy, “The 11th Basic Plan for Long-term Electricity Supply and Demand (2024-2038),” Mar. 2025. Available : https://www.motie.go.kr/

IEA, “Electricity 2024 : Analysis and Forecast to 2026,” Jan. 2024. Available : https://www.iea.org/

Kong, X., et al., “A comprehensive review of power flow tracing methods and their applications in modern power systems,” Energies, vol. 16, no. 18, pp. 5974, Aug. 2023. DOI:10.1109/ACCESS.2020.2968461

Rofiqul, I. & Ramadhan, R., “Application of power flow tracing methods for cost allocation in distribution networks with high DG penetration,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 32, no. 1, pp. 58-66, Sep. 2024. DOI:10.11591/ijeecs.v37.i2.pp715-729

D. Cao, et al., “Physics-Informed Graphical Learning and Bayesian Averaging for Robust Distribution State Estimation,” in IEEE Transactions on Power Systems, vol. 39, no. 2, pp. 2879-2892, Mar. 2024. DOI:10.1109/TPWRS.2023.3282413

J. Bialek, “Tracing the Flow of Electricity,” in Generation, Transmission and Distribution, IEE Proceedings, vol. 143, no. 4, pp. 313-320, Jul. 1996. DOI:10.1049/ip-gtd:19960461

T. Ströher and J. Strüker, “Power Flow Tracing: Analyzing the Embedding of Eleks Dakar in Research and Practice,” Fraunhofer-Institute for Applied Information Technology, Dec. 2024. Available : https://www.fraunhofer.de/en.html

Sudhakar Uppalapati, et al., “Precision biochar yield forecasting employing random forest and XGBoost with Taylor diagram visualization,” Sci Rep 15, 7105, Feb. 2025. DOI:10.1038/s41598-025-91450-w

Hamad, S.A., Ghalib, M.A., Munshi, A. et al., “Evaluating machine learning models comprehensively for predicting maximum power from photovoltaic systems,” Sci Rep 15, 10750, Mar. 2025. DOI:10.1038/s41598-025-91044-6