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• A multi-scenario set depicting the uncertainty of wind power is built based on the extreme scenario method. • A loop-network reconfiguration optimization model is established to eliminate line overloads in detail. • A two layer solving framework is proposed to simplify solving the optimization model. • The loop-network reconfiguraition strategy can meet the multi-scenario set of wind power and eliminate line overloads effectively. With large-scale wind power integration, the uncertainty of the wind power outputs will aggravate the transmission line overloads during the black-start restoration process. By constructing regional loop-networks, this paper proposes an optimization method of network reconfiguration strategies to eliminate the line overloads. Firstly, a multi-scenario set of the wind power outputs is constructed based on the extreme scenario method. Secondly, a loop-network reconfiguration optimization model is established to meet the requirements of the multi-scenario set simultaneously, where the line overloads are not permitted. Then, a two-layer solving framework is proposed to solve the optimization model. The upper-level layer is a multi-scenario mixed integer linear programming (MILP) model with the DC power flow constraints, whose objective is to minimize the operation complexity index. The lower-level layer serves to check the standing phase angle (SPA) constraint and the AC power flow constraints of the optimal schemes obtained from the upper-level layer. Therefore, the loop-network reconfiguration optimization model is alternatively solved by iterative computation. The effectiveness of the proposed method is verified by the modified IEEE 39-bus system and the modified IEEE 118-bus system, and applicability of this method to practical systems is verified by the southwestern Yunnan power system in China. [ABSTRACT FROM AUTHOR]

It has been revealed that dyslexic children learning alphabetic languages are characterized by aberrant topological organization of brain networks. However, little is known about the functional organization and the reconfiguration pattern of brain networks in Chinese dyslexic children. Using graph theoretical analysis and functional magnetic resonance images (fMRI), we examined this issue specifically from the perspective of functional integration and segregation. We first compared large-scale topological organizations between dyslexic children and typically developing children during a Chinese phonological rhyming task, and found that dyslexic children showed increased local efficiency and clustering coefficient compared with typically developing children, which were negatively correlated with task performance. Furthermore, dyslexic children and typically developing children could be accurately distinguished at the individual-subject level based on the nodal local efficiency or clustering coefficient. Second, we studied the group difference of network reconfiguration and found that dyslexic children showed more difficulty when shifting from the resting state to the phonological task. Our results suggest an over-segregated brain functional organization and deficits in brain network reconfiguration in Chinese dyslexic children, which helps to advance our knowledge on the neural mechanisms underlying dyslexia., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

• A multi-objective model of power supply capability (PSC) is practical. • Uncertainties of the demand-side response and renewable DGs should be considered. • Coordination of reconfiguration, DG control, and load management can improve PSC. • The improved crossover operator and elimination strategy of NSGA-II perform well. • Entropy-TOPSIS method can select the eclectic optimal solution from Pareto front. Aiming at the power supply capability evaluation under the background of controllable source-network-load in power system, a multi-objective power supply capability evaluation method for active distribution network considering the active control cost is proposed. Firstly, uncertain factors such as renewable distributed generations' output and demand response are modeled. Then, the maximization of regional power supply capacity and the minimization of active control costs are taken as the optimization objective from the perspective of both the planning and operation. Considering the constraints of distributed generations output ability, the network topology, load controllable levels, and so on, a multi-objective optimization uncertainty model for the active distribution network is constructed. In addition, the crossover operator and the selection strategy of NSGA-II are improved based on the non-uniform arithmetic crossover and phase-out strategy, which is used to solve the proposed optimization model. The Pareto optimal solution set obtained by the multi-objective optimization algorithm has a large scale and contains a wealth of information, and a method based on entropy-TOPSIS is also provided to select one eclectic solution set by the operator. Finally, the effectiveness of the proposed evaluation method and the performance of the improved algorithm are verified by the improved IEEE 33-bus distribution system and one of China's actual power grid. [ABSTRACT FROM AUTHOR]