Abstract
The frequent natural disasters caused by global warming have been threatening the safety of power systems for decades. A resilient power system has the ability to recover quickly following a disaster and has been continuously studied these years. However, with the progress of energy transition, a large quantity of renewable energy sources (RESs) has been integrated into the power distribution systems and the uncertainty has complicated the decision and operation of resilient distribution systems. This paper proposes an online resilience assessment method for islanded distribution systems considering the time-varying uncertainty of RESs and loads, based on only the measured data without any forecasting tools. An offline probabilistic modeling and online conditional probability distribution derivation method is proposed to generate short-term power scenarios of RESs and loads dynamically, and an online resilience assessment framework is established with an optimization-based system response model in different outage scenarios of distribution systems. The case study to a modified IEEE 37-node test feeder validates the advantages of the proposed method in generating accurate short-term scenarios of uncertainties and providing reliable resilience assessment results. The proposed framework can be used as a basic tool for the online operation of resilient distribution systems.
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