No abstract

This study aims to enhance the reliability of the urban power grid system and decrease the economic loss due to power network faults. Based on the analysis of the traditional algorithms for restructuring the urban distribution system after faults, this study proposes an upgraded genetic algorithm (GA) and ant colony algorithm (ACA) and combines these two to overcome the limitations of the local optimum of GAs and low convergence speed of ACAs. Taking the IEEE33-node system as the research object, the network loss, maximum recovery of the power-loss load, and the number of switching operations as the objective function, the impact of different algorithms on the restoration and reconfiguration of the distribution system was examined according to MATLAB system simulation and the optimal algorithm for the reconfiguration of the urban distribution system failure recovery. The experimental results revealed that compared with the current distribution system reconfiguration algorithm, the genetic-ant colony algorithm (GACA) has higher algorithm time efficiency and solution accuracy and can markedly decrease the recovery time and improve the impact of the distribution system in a short period. Overall, the proposed GACA is an efficient self-healing algorithm of urban distribution systems and useful for augmenting the reliability of the urban power system.

In the future Internet operation and service model, users put forward network application requirements, and the service provider allocates the corresponding virtual network for users according to the demands. Virtual network resource allocation is an NP-hard problem; hence, the existing research work is mainly based on heuristic algorithms to solve the above problem. However, these traditional algorithms based solely on resource attributes are not sufficient to configure virtual networks. We design a virtual network configuration algorithm (ERTA-CA) based on the two-stage heuristic resource utilization that considers both local and global resource attributes and topological attributes of the network. The experimental results verify that our proposed algorithm can improve the acceptance rate and configuration revenue of the virtual network, which further indicates that ERTA-CA can achieve the virtual network configuration with efficient use of resources.