Co-Design of Active Power Control and UAV-Assisted Two-Stage Emergency Communication for ADN: A Cyber-Physical Cross-Space Understanding and Cooperation Method
Since massive distributed resources have been aggregated into active distribution network (ADN), the operation of ADN faces serious challenges. One of these challenges is the significant power fluctuations in physical-space due to the uncoordinated integration of multi-aggregator generation; another one is the network congestion in cyber-space due to the quick growth of power data. Both of them will seriously affect the operational performance of ADN. To address these issues, a co-design approach for active power control and two-stage emergency communication scheme is first proposed with the idea of cyber-physical cross-space understanding and cooperation. In physical-space, considering the flow correlation among aggregators, a centralized power control is studied to achieve optimal regulation. In cyber-space, a two-stage communication architecture coordinated with unmanned aerial vehicles (UAVs) is studied to relieve congestion. In Stage I, through understanding the demand for power control regarding transmission performance, a demand-driven path reconfiguration strategy is proposed to restore transmission and gain time for UAV movement. In Stage II, considering the uncertainty of UAV flight altitude, a flight method based on stochastic planning is proposed, which ensures reliable communication via UAVs in case the reconfigured paths become severely congested again. Case studies are presented at the end.
Authors
- Houjun Li (ORCID: https://orcid.org/0000-0002-7514-5656)
- Bo Zhang (ORCID: https://orcid.org/0000-0001-6124-2642)
- Dongmei Yuan
- Chunxia Dou
- Dong Yue (ORCID: https://orcid.org/0000-0001-7810-9338)
- Lei Xu (ORCID: https://orcid.org/0000-0002-7288-6061)
Institutions
- Nanjing University of Posts and Telecommunications (CN)
- Nanjing Xiaozhuang University (CN)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1109/tsg.2025.3613985
- Primary Topic
- Air Traffic Management and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00