Abstract
The increasing penetration of distributed generators (DGs) and the advancement of information and communication technologies (ICTs) will facilitate the transformation of the traditional passive distribution network towards a cyber-physical active distribution system (CPADS). With the increasing risks of extreme events, such as natural disasters (e.g., flooding) and cyber-physical attacks, it is critical for CPADS to formulate a restoration scheme to improve its resilience. Therefore, in this paper, a distributed adaptive robust restoration scheme with voltage/var control is presented to cope with the high-impact but low-frequency events. First, a detailed cyber-physical system model is established, including the dynamic routing and the quality-of-services (QoS) in both optical fiber networks and 5G wireless networks. Then, the interactions between the cyber system and the physical system are analyzed. Based on the cyber-physical system model, a two-stage restoration scheme with voltage/var control is proposed by coordinately scheduling different network assets in day-ahead and in real-time. The formulated problem is solved by adaptive robust optimization (ARO). To further enhance the resilience of the CPADS, a distributed restoration framework is proposed. The distributed problem is solved by the alternating direction method of multipliers (ADMM) algorithm, and the convergence of the discrete problem is ensured by introducing the alternating optimization procedure (AOP). Considering the cyber faults, a boundary variable compensation and residual relaxation mechanism is proposed in ADMM. The proposed framework and methodology are verified in the case study. The convergence and the efficiency of the proposed algorithm are verified. Compared with the state-of-art works, the advantages in load restoration capability of the proposed method are shown.
© 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
© 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
| Original language | English |
|---|---|
| Pages (from-to) | 2170-2184 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 39 |
| Issue number | 1 |
| Online published | 1 Mar 2023 |
| DOIs | |
| Publication status | Published - Jan 2024 |
| Externally published | Yes |
Funding
This work was supported in part by the Australian Research Council (ARC) Research Hub under Grant IH180100020, in part by the ARC Training Centre under Grant IC200100023, in part by the ARC Linkage Project under Grant LP200100056, in part by the ARC under Grant DP220103881, in part by the Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), the National Natural Science Foundation of China under Key Programs 71931003 and 72061147004, in part by the National Natural Science Foundation of China under Grant 72171206, and in part by Shenzhen Key Lab of Crowd Intelligence Empowered Low-Carbon Energy Network under Grant ZDSYS20220606100601002.
Research Keywords
- Cyber-physical active distribution system
- distributed adaptive robust optimization
- load restoration
- voltage/var control
