Resilient outage recovery of a distribution system: co-optimizing mobile power sources with network structure
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National Key R&D Program of China (2020YFF0305800). Science and Technol ogy Project of SGCC (520201210025).

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    Abstract:

    Outage recovery is important for reducing the economic cost and improving the reliability of a distribution system (DS) in extreme weather and with equipment faults. Previous studies have separately considered network reconfiguration (NR) and dispatching mobile power sources (MPS) to restore the outage load. However, NR cannot deal with the scenario of an electrical island, while dispatching MPS results in a long power outage. In this paper, a resilient outage recovery method based on co-optimizing MPS and NR is proposed, where the DS and traffic network (TN) are considered simultaneously. In the DS, the switch action cost and power losses are minimized, and the access points of MPSs are changed by carrying out the NR process. In the TN, an MPS dispatching model with the objective of minimizing power outage time, routing and power generation cost is developed to optimize the MPSs’ schedule. A solution algorithm based on iteration and relaxation methods is proposed to simplify the solving process and obtain the optimal recovery strategy. Finally, numerical case studies on the IEEE 33 and 119-bus systems validate the proposed resilient outage recovery method. It is shown that the access point of MPS can be changed by NR to decrease the power outage time and dispatching cost of MPS. The results also show that the system operation cost can be reduced by considering power losses in the objective function.

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Chenchen Li, Yanna Xi,, Yufan Lu,, Nian Liu,, Liudong Chen,, Li Ju, Yibin Tao. Resilient outage recovery of a distribution system: co-optimizing mobile power sources with network structure[J]. Protection and Control of Modern Power Systems,2022,V7(3):459-471.[Chenchen Li, Yanna Xi,, Yufan Lu,, Nian Liu,, Liudong Chen,, Li Ju, Yibin Tao. Resilient outage recovery of a distribution system: co-optimizing mobile power sources with network structure[J]. Power System Protection and Control,2022,V7(3):459-471]

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  • Online: September 02,2022
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