Impact of combining party building activities and digital transformation on distribution system performance

[1] Elsayed, A. T., Mohamed, A. A., & Mohammed, O. A. (2015). DC microgrids and distribution systems: An overview. Electric power systems research, 119, 407-417. Search in Google Scholar

[2] Abou El‐Ela, A. A., El‐Sehiemy, R. A., Shaheen, A. M., & Eissa, I. A. (2020). Optimal coordination of static VAR compensators, fixed capacitors, and distributed energy resources in Egyptian distribution networks. International Transactions on Electrical Energy Systems, 30(11), e12609. Search in Google Scholar

[3] Mieth, R., & Dvorkin, Y. (2018). Data-driven distributionally robust optimal power flow for distribution systems. IEEE Control Systems Letters, 2(3), 363-368. Search in Google Scholar

[4] Abdelaziz, A. Y., Ali, E. S., & Abd Elazim, S. M. (2016). Flower pollination algorithm for optimal capacitor placement and sizing in distribution systems. Electric Power Components and Systems, 44(5), 544-555. Search in Google Scholar

[5] Reno, M. J., Brahma, S., Bidram, A., & Ropp, M. E. (2021). Influence of inverter-based resources on microgrid protection: Part 1: Microgrids in radial distribution systems. IEEE Power and Energy Magazine, 19(3), 36-46. Search in Google Scholar

[6] Cao, D., Zhao, J., Hu, W., Ding, F., Huang, Q., Chen, Z., & Blaabjerg, F. (2021). Data-driven multi-agent deep reinforcement learning for distribution system decentralized voltage control with high penetration of PVs. IEEE Transactions on Smart Grid, 12(5), 4137-4150. Search in Google Scholar

[7] Jamil, E., Hameed, S., & Jamil, B. (2019). Power quality improvement of distribution system with photovoltaic and permanent magnet synchronous generator based renewable energy farm using static synchronous compensator. Sustainable energy technologies and assessments, 35, 98-116. Search in Google Scholar

[8] Xie, M., Ji, X., Hu, X., Cheng, P., Du, Y., & Liu, M. (2018). Autonomous optimized economic dispatch of active distribution system with multi-microgrids. Energy, 153, 479-489. Search in Google Scholar

[9] Chen, B., Ye, Z., Chen, C., Wang, J., Ding, T., & Bie, Z. (2018). Toward a synthetic model for distribution system restoration and crew dispatch. IEEE Transactions on Power Systems, 34(3), 2228-2239. Search in Google Scholar

[10] Li, Z., Jazebi, S., & De Leon, F. (2016). Determination of the optimal switching frequency for distribution system reconfiguration. IEEE Transactions on Power Delivery, 32(4), 2060-2069. Search in Google Scholar

[11] Elkadeem, M. R., Abd Elaziz, M., Ullah, Z., Wang, S., & Sharshir, S. W. (2019). Optimal planning of renewable energy-integrated distribution system considering uncertainties. IEEE Access, 7, 164887-164907. Search in Google Scholar

[12] Injeti, S. K. (2018). A Pareto optimal approach for allocation of distributed generators in radial distribution systems using improved differential search algorithm. Journal of Electrical Systems and Information Technology, 5(3), 908-927. Search in Google Scholar

[13] Guo, C., Wang, X., Zheng, Y., & Zhang, F. (2021). Optimal energy management of multi-microgrids connected to distribution system based on deep reinforcement learning. International journal of electrical power & energy systems, 131, 107048. Search in Google Scholar

[14] Kim Seunghyeon,Cha Minho,Park Younwon,Ryu Minsang,Park Sooyeun,Ahn Kyeongil... & Gong Haeyeol. (2024). A study on the establishment of database for local government disaster response and decision support system in the nuclear accidents. Journal of Nuclear Science and Technology(7),983-999. Search in Google Scholar

[15] Huaqun Chen,Minghui Yang & Xie Tang. (2024). Association rule mining of aircraft event causes based on the Apriori algorithm. Scientific reports(1),13440-13440. Search in Google Scholar

[16] Pan Hua & Liu Rong. (2024). Mining research on correlation factors of residential electricity stability based on improved FP-growth algorithm.Management of Environmental Quality. An International Journal(3),547-566. Search in Google Scholar

[17] Henning Kayser & Miu Ling Lau. (2024). Growing value of data standardization: Allotrope Foundation Connect Workshop Proceedings. Drug discovery today(6),103988-103988. Search in Google Scholar