{"id":9852,"date":"2026-08-12T14:32:56","date_gmt":"2026-08-12T06:32:56","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=9852"},"modified":"2026-08-17T23:48:45","modified_gmt":"2026-08-17T15:48:45","slug":"jase-202611-34-040","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202611-34-040","title":{"rendered":"High Resilience Integrated Emergency Interconnection and Communication Technology Applicable to Power Systems under Extreme Climatic Conditions"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 34<\/a><\/p>\n<\/div>\n\n\n\n

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Anjiang Liu1<\/sup><\/i><\/a>, Shuqing Hao1<\/sup>, Yue Li1<\/sup>, Yu Miao1<\/sup>, and Hongyu Zuo2<\/sup><\/p>\n\n\n\n

1<\/sup>Electric Power Research Institute, Guizhou Power Grid Co., Ltd, Guiyang, Guizhou, China<\/p>\n\n\n\n

2<\/sup>Zunyi Power Supply Bureau of Guizhou Power Grid Company, Zunyi, Guizhou, China<\/p>\n<\/div>\n\n\n\n

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Received: May 21, 2026
Accepted: July 26, 2026
Publication Date: August 12, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Voltage Recovery Performance Before and After OPF Control  <\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:\u00a0 BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202611_34.040<\/a>\u00a0\u00a0<\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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Extreme climatic conditions pose significant operational challenges to power systems by increasing fault occurrences, communication failures, voltage instability, and large-scale outages. This study proposes a high resilience integrated emergency interconnection and communication framework for reliable power system operation during extreme weather events. The proposed system combines Optimal Power Flow (OPF) control with hybrid communication technologies, including satellite, unmanned aerial vehicle (UAV), and Mobile Ad Hoc Network(MANET)-based communication systems. In addition, a hybrid artificial intelligence fault detection model integrating Random Forest (RF) and Support Vector Machine (SVM) with ensemble learning is developed for accurate fault identification. The methodology is implemented on the IEEE 14-Bus System using the Newton\u2013Raphson load flow method. Extreme climatic conditions are modeled through scenario based simulations, while Monte Carlo simulations are employed to generate synthetic disturbances and faults. Communication performance is evaluated through delay and packet loss analysis within hybrid fiber\u2013IoT communication networks. The framework also incorporates rule-based communication selection, optimization driven coordination strategies, load shedding optimization, and power balancing mechanisms to maintain system stability during emergencies. Experimental results demonstrate strong resilience and communication performance, achieving a Voltage Deviation Index (VDI) of 0.04281 p.u., Resilience Index (RI) of 0.7241, Recovery
Time (RT) of 5.64 hours, and Energy Not Supplied (ENS) of 2.85 MWh. The communication system records latency between 0.005 s and 0.018 s, throughput of 99.34 Mbps, and a Communication Reliability Index (CRI) of 0.9782. The hybrid fault detection model achieves 98.83% accuracy, confirming the effectiveness of the proposed framework for resilient smart grid operations.<\/p>\n\n\n\n

Keywords: Power System Resilience, Extreme Climatic Conditions, Optimal Power Flow, Hybrid Communication Networks, AI-Based Fault Detection<\/em><\/p>\n\n\n\n

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