Toward a MILP Modeling Framework for Distribution System Restoration

Journal Article · Mon Dec 24 04:00:00 EST 2018 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/TPWRS.2018.2885322· OSTI ID:1507794

Chen, Bo ^[1]; Ye, Zhigang ^[2]; Chen, Chen ^[1]; Wang, Jianhui ^[3]

---

1. Argonne National Lab. (ANL), Lemont, IL (United States)
2. Xi’an Jiaotong Univ., Xi’an (China); Argonne National Lab. (ANL), Argonne, IL (United States)
3. Southern Methodist Univ., Dallas, TX (United States)

Large-scale blackouts and extreme weather events in recent decades raise the concern for improving the resilience of electric power infrastructures. Distribution service restoration (DSR), a fundamental application in outage management systems, allows restoration solutions for system operators when power outages happen. As distribution generators (DGs) and remotely controllable devices are increasingly installed in distribution systems, an advanced DSR framework is critical to perform optimally coordinated restoration that can achieve maximal restoration performance. This work introduces a DSR modeling framework, which can generate optimal switching sequences and estimated time of restoration in the presence of remotely controllable switches, manually operated switches, and dispatchable DGs. Two mathematical models, a variable time step model and a fixed time step model, are presented and compared. The proposed models are formulated as a mixed-integer linear programming model, and their effectiveness is evaluated via the IEEE 123 node test feeder.

• Research Organization: Argonne National Lab. (ANL), Lemont, IL (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
• Grant/Contract Number: AC02-06CH11357
• OSTI ID: 1507794
• Journal Information: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 3 Vol. 34; ISSN 0885-8950
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
Adaptation models
Distribution system
Load modeling
Mathematical model
Power system reliability
Regulators
distributed generation
mixed-integer linear programming
service restoration
switching sequence management