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In the smart grid environment, a power system restoration plan with flexibility is needed to improve reliability and efficiency in an automated way. Traditional system restoration methods based on fixed time intervals may not meet the requirement. This article proposes a new permutation-based model for power system restoration within an optimized flexible duration considering available generator capability and load prioritization. By utilizing this new model, power system restoration is formulated as a permutation-based combinatorial optimization problem to maximize the restored load per unit time. Finally an action-by-action flexible time schedule is obtained for generator startup. A novel quantum-inspired evolutionary algorithm, called the quantum-inspired differential evolutionary algorithm, has been applied to solve this problem due its to high population diversity and fast convergence. The effectiveness of the proposed restoration approach has been validated using IEEE 39- and 57-bus systems. [ABSTRACT FROM PUBLISHER]

As an important way of addressing energy and environmental challenges, the market share of wind power generation has increased dramatically in the past decade and has introduced significant challenges to power system operation. In this article, the tail correlation between multiple wind farms is studied. The joint probability distribution of multiple wind farms is estimated by employing the Gumbel copula function. Based on the estimated joint probability distribution, a stochastic optimal dispatch model is proposed to take into account the chance constraints of energy utilization from multiple wind farms in the power system. The sample average approximation method is employed to handle the chance constraints in the proposed model, so as to transform stochastic optimal dispatch into a deterministic non-linear optimization problem. The quantum-inspired evolutionary algorithm is used to solve the proposed model. The proposed model and algorithm are tested with comprehensive case studies to demonstrate their effectiveness. [ABSTRACT FROM AUTHOR]