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Once blackouts occur the system operators should re‐energise the affected system in the shortest time. To attain this, restoration plans should be developed beforehand. A deliberate restoration plan considers the supply duration of the cranking power to non‐black‐start units (NBSUs), besides the static and dynamic constraints of the power system. Hence, there should be a method to estimate the restoration duration of NBSUs considering the failure in breakers operating mechanism and the stochastic nature of restoration actions. Accordingly, in this study, generally distributed transition stochastic Petri net is employed to calculate the supply duration of NBSUs, critical loads and the execution time of restoration actions. This is significant because the planners can validate their restoration plans from the NBSUs critical times' point of view or determine energisation time of critical loads. The proposed method has been applied in three test cases, two of these are used for benchmarking, and the other one is a part of Iran bulk power system, which includes a real black‐start test. The results show the effectiveness of the method in estimating the restoration duration. [ABSTRACT FROM AUTHOR]

Summary: Blackouts rarely occur in power systems; nevertheless, in case of occurrence, its impact on the economy, industry, and social life can be noticeable. To minimize the negative financial and social impacts of blackouts, power systems should be restored in the shortest possible time. Therefore, system operators should access a formulated method to estimate the restoration duration. In this paper, a method based on the Petri Net is used to calculate the restoration duration. Therefore, a restoration plan is resolved into its constituent steps, and for each step, a stochastic duration is considered. Applying the Petri Net model of the restoration plan and the duration of each restoration step, the total restoration time can be calculated. The proposed method is applied in two system tests, and the results show consistency with those of the critical path method. [ABSTRACT FROM AUTHOR]

Summary: Despite power system operators' efforts, blackouts occur; therefore, power systems should be restored. To attain this, power system restoration is done applying different strategies after a complete blackout. The most famous one is the bottom‐up strategy. Determining the islands is of extreme importance in this strategy. Hence, this paper proposes a new version of multi‐objective populated simulated annealing considering the cohesiveness and the quality of islands as objective functions. The proposed method takes into account miscellaneous constraints such as black‐start availability in each island, load‐generation balance, power flow establishment equations, and the availability of synchronization devices. Simulation results for the IEEE 39 and 118‐bus test systems confirm the effectiveness of the proposed method in determining the islands. [ABSTRACT FROM AUTHOR]