The frequency of extreme events (e.g., hurricanes, earthquakes, and floods) and man-made attacks (cyber and physical attacks) has increased dramatically in recent years. These events have severely impacted power systems ranging from long outage times to major equipment (e.g., substations, transmission lines, and power plants) destructions. This calls for developing control and operation methods and planning strategies to improve grid resilience against such events. The first step toward this goal is to develop resilience metrics and evaluation methods to compare planning and operation alternatives and to provide techno-economic justifications for resilience enhancement. Although several power system resilience definitions, metrics, and evaluation methods have been proposed in the literature, they have not been universally accepted or standardized. This paper provides a comprehensive and critical review of current practices of power system resilience metrics and evaluation methods and discusses future directions and recommendations to contribute to the development of universally accepted and standardized definitions, metrics, evaluation methods, and enhancement strategies. This paper thoroughly examines the consensus on the power system resilience concept provided by different organizations and scholars and existing and currently practiced resilience enhancement methods. Research gaps, associated challenges, and potential solutions to existing limitations are also provided. INDEX TERMS Critical review, extreme events, power system resilience, resilience definitions, metrics, and enhancement strategies. MOHAMMED BENIDRIS (Member, IEEE) received the B.Sc. and M.Sc. degrees in electrical engineering from the

An analytical method for placement and sizing of distributed generation on power distribution systems for loss reduction is introduced. The proposed analytical method is developed based on a new formulation for the power flow problem, which is non-iterative, direct, and involves no convergence issues even for systems with high R/X branch ratios. Further, this power flow solution is extremely useful whenever fast and repetitive power flow estimations are required. A priority list based on loss sensitivity factors is developed to determine the optimal locations of the candidate distributed generation units. Sensitivity analysis is performed to estimate the optimal size and power factor of the candidate distributed generation units. Various types of distributed generators (DGs) have been dealt with and viable solutions are proposed to reduce total system loss. The proposed method has been tested on 33-bus and 69-bus distribution systems, which are extensively used as examples in solving the placement and sizing problem of DGs. Exhaustive power flow routines are also performed to verify the sizes obtained by the analytical method. The test results show that the proposed analytical method could lead to optimal or near-optimal solution, while requiring lower computational effort.

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It is well-known that the reliability evaluation of composite power systems is computationally demanding. This work introduces a state space classification (SSC) technique that classifies a systems state space into failure, success, and unclassified subspaces without performing power flow analysis.

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