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The existing microgrid-based distribution system restoration methods follow traditional restoration criteria, which achieve a maximum coverage of distribution systems. In extreme conditions (e.g., natural disasters and physical and cyber attacks), the traditional restoration plans could pose additional financial and security risks to local utility customers. That is, restored services could be further interrupted by subsequent outages in the extended event. To address such resilience challenges, this paper proposes the formation of adaptive multimicrogrids as part of the critical service restoration strategy. The proposed strategy comprises microgrid formation (MF) and load switching sequence (LSS) steps. The MF forms multiple microgrids with minimum overall scale and radial or looped topologies and includes optimally positioned mobile emergency resources to address potential risks in extreme conditions. The LSS determines a proper load switching sequence for ensuring the system dynamic performance in the restoration process. The effectiveness of the proposed strategy is verified by a case study on the IEEE 132-node test feeder system and the time-domain simulation in MATLAB Simulink. [ABSTRACT FROM AUTHOR]

Most existing approaches for distribution network reconfiguration assume that the distribution system is (three-phase) balanced and a single-phase equivalent is used. However, distribution feeders are usually unbalanced due to a large number of single-phase loads, nonsymmetrical conductor spacing, and three-phase line topology. This paper builds on our previous work and studies feeder reconfiguration for unbalanced distribution systems with distributed generation (DG). The three-phase bus locations and sizes of DG units are determined using sensitivity analysis and nonlinear programming, respectively, and distribution feeders are reconfigured every hour based on the status of time-varying loads, output power from DG units and faults on the network while minimizing the energy loss costs and DG operating costs. Simulation results show the effectiveness and computational efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

The European Union is targeting a 20% share of energy from renewable resources by 2020, and this increase is in turn expected to lead to operational challenges that will require various congestion management actions by system operators. In this paper, we deal with topology control of the transmission network as a congestion management resource and evaluate the impacts of topology control on the European electricity network. To do this, we co-optimize unit commitment and transmission switching over 24 h, and we use a decomposition scheme to tackle the resulting large-scale problem. Our analysis is conducted on different scenarios of load and renewable power generation. We find that topology control results in significant cost savings within Europe which tend to be inversely related to net load. The robustness of our results is supported by an extensive sensitivity analysis. [ABSTRACT FROM AUTHOR]

Optimal transmission switching (OTS) optimizes simultaneously the generation dispatch and the topology of a power system. It has been shown that taking some transmission lines out of service can significantly reduce the operating cost of the system while respecting the traditional deterministic N-1 security criterion of operational reliability. However, topology modifications could adversely affect probabilistic security metrics. The operational reliability of a power system can be translated into a cost by multiplying the expected energy not served by the value of lost load. This paper therefore explores whether it is possible to maintain a positive economic balance with OTS when considering not only the cost of generation but also the expected socio-economic cost of disruptions in the supply. This is done in two steps: the computation of an N-1 secure OTS and then the calculation of a probabilistic estimate of the operational reliability of the OTS solution. Based on the results obtained with two test systems, it is shown that OTS tends to significantly degrade probabilistic measures of security. It is thus not obvious that OTS can lead to a positive economic balance, even when N-1 security is enforced. Consequently, a probabilistic security analysis should be performed before implementing an OTS solution. [ABSTRACT FROM AUTHOR]

Distribution system reconfiguration (DSR) is a multi-objective, nonlinear problem. This paper introduces a new, fast, nondominated sorting genetic algorithm (FNSGA) for the purpose of solving the DSR problem in normal operation by satisfying all objectives simultaneously with a relatively small number of generations and relatively short computation time. The objectives of the problem are to minimize real power losses and improve the voltage profile and load balancing index with minimum switching operations. Instead of generating several ranks from the nondominated set of solutions, this algorithm deals with only one rank; then the most suitable solution is chosen according to the operator's wishes. If there is no preference and all objectives have the same degree of importance, the best solution is determined by simply considering the sum of the normalized objective values. Also, a guided mutation operation is applied instead of a random one to speed up convergence. Radial system topology is satisfied using graph theory by formulating the branch-bus incidence matrix (BBIM) and checking the rank of each topology. To test the algorithm, it was applied to two widely studied test systems and a real one. The results show the efficiency of this algorithm as compared to other methods in terms of achieving all the goals simultaneously with reasonable population and generation sizes and without using a mutation rate, which is usually problem-dependent. [ABSTRACT FROM PUBLISHER]