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Abstract Distribution system (DS) communication failures following extreme events often degrade monitoring and control functions, thus preventing the acquisition of complete global DS component state information, on which existing post‐disaster DS restoration methods are based. This paper proposes methods of inferring the states of DS components in the case of incomplete component state information. By using the known DS information, the operating states of unobservable DS branches and buses can be inferred, providing complete information for DS performance restoration before full communication recovery.

Abstract Distributed energy resources (DERs) provide flexible load restoration strategies, which can effectively enhance the resilience of active distribution systems (ADSs). Whereas, the widespread DERs in ADSs complicates the supply‐demand relationship and make the system resilience difficult to access. Therefore, this paper proposes a simulation‐based resilience assessment algorithm of ADSs considering the microgrid formation based on grid‐edge DERs. Microgrid formation is used to depict the resilience gain of grid‐edge DERs on ADSs. Specifically, a resilience assessment framework for ADSs is firstly proposed, where the uncertainty of component state and supply‐demand is modelled based on probability statistics. Then the mixed integer linear programming is used to search for optimal load restoration strategies with microgrid formation. On this basis, a set of resilience indices are defined to quantitatively analyse the resilience of ADSs, and a resilience assessment algorithm with uncertainty scenario generation is proposed to obtain these indices. Furthermore, extensive numerical results based on a modified IEEE 123‐bus feeder validate the effectiveness of the proposed method.

Abstract Considering the limited information sharing between natural gas systems (NGS) and electrical power systems (EPS), this paper proposes a distributed resilience assessment method for NGS and EPS. First, a coordinated restoration framework is presented for incompletely integrated energy systems, and the collaborative benefit redistribution mechanism is proposed to motivate the participation of the cooperative restoration. Then fragility and recovery models for NGS and EPS components are developed, involving the impact of wind and rainfall during typhoons. An emergency load shedding model considering the conditional value at risk under typhoons is built, where the dynamic constraints of gas storage in NGS's pipelines is considered, and a linear approximation method is adopted to make the solution feasible. The modified alternating direction method of multipliers algorithm is used to solve the problem, and herein the self‐adaptive penalty factor is leveraged to boost the efficiency. Based on the valley‐shaped resilience model, the concept of skewness and kurtosis are introduced to give risk‐adverse metrics more systematically to the impact of extreme events. The proposed model and algorithm are validated by case studies. Except for the performance exploration, the weakness and enhancement suggestions are also concluded from the case analysis.

Abstract Successive failure propagating through a power system, typically caused by extreme weather such as storm and lightning, can cause blackouts by means of a variety of processes. To address this issue, this paper proposes preventive control for successive failures of power system to mitigate the consequences of successive failures in extreme weather. First, based on the Poisson process theory, the authors model the successive failure propagation, and present the confidence interval estimation for the time interval between successive failures. Then, a failure pre‐control methodology that quantifies the grid regulating ability and actions is developed to make decisions for system operators on mitigating overloads of transmission lines. Furthermore, a systematic pre‐control framework for successive failures is first proposed to detect latent risks, eliminate predictable consequential outages, and secure power system stability. Results from IEEE‐9 bus and IEEE‐39 bus standard systems as well as a real‐world system show the feasibility and effectiveness of the proposed method. The proposed preventive control framework can provide a systematic pre‐control action scheme for system operators, and realize enhancement of stability and resilience to power system failures.

Abstract The large‐scale blackouts of distribution systems (DS) caused by extreme natural disasters have aroused a lot of attention. To enhance the resilience of DSs, a novel service restoration and recovery model to minimize the system‐wide load loss is proposed here, where reconfiguration systems and two kinds of moveable resources, that is, mobile sources (MS) and repair crews (RC), are considered. Then, time‐space network (TSN) is applied to model the movement of MSs and RCs over the real‐world transportation networks (TN). However, the introduction of TSN makes solving the model become a time‐consuming task as plenty of variables are involved by it. To tackle this challenge which may lead to the impracticability of the model, a Floyd‐algorithm based TN simplification method is proposed to reduce the variables without sacrificing the equivalence of the TNs before and after the transformation. Finally, the applicability and effectiveness of the proposed model are verified on a 33‐bus test DS and a real‐world DS with complicated TNs.

Abstract Composed of multiple integrated energy systems (IESs) belonging to different stakeholders, multi‐agent IESs (MA‐IESs) are widely concerned because of data privacy protect. As the basis of planning design and reliability evaluation for MA‐IESs, distributed energy resource coordination (DERC) problem is studied in this paper. First, a DERC model for MA‐IESs is established, which considers energy conversion process specifically. Meanwhile, a novel distributed accelerated descent (DAD) algorithm is proposed to realize fully distributed solving. Different from most of the existing researches that investigate the DERC with box constraints, the presented algorithm is able to solve the DERC with general convex constraints. Moreover, the backward operators in the method improve the convergence rate to the best of distributed first‐order optimization algorithm with fixed step size, O(1/T). Furthermore, the presented approach is initialization robustness when the load fluctuations suddenly happened in MA‐IESs. The convergence property, computing, and communication complexity are strictly proved. Finally, the effectiveness of DERC model and DAD algorithm are demonstrated by some modified case studies.

Abstract Extreme weather events, such as hurricanes, impose severe impacts on power systems. A rapid repair for power systems is desired after hurricanes pass to mitigate load‐shedding losses. This study proposes a proactive repair crew deployment model to prepare for post‐disaster repair and restoration. A two‐stage stochastic optimisation framework is designed. In the first stage, the repair crews are allocated to candidate locations ahead of a hurricane. In the second stage, the repair dispatch and load restoration are implemented under several damage scenarios to support the first‐stage decision‐making. A novel repair crew routing method is proposed which considers repair crew cooperation on important damaged components to enable earlier restoration of critical load. A linear‐programming approximation of AC power flow is applied to model the restoration of the transmission system in which the generator start‐up characters and security constraints are incorporated. A scenario‐based decomposition algorithm is applied to solve the stochastic problem and a preprocessing method to identify necessary components is proposed to further reduce computation time. Case studies validate the effectiveness of the proposed model in improving transmission system resilience.

How to restore the load of power system after disasters, especially to guarantee the power supply of the important load, is a significant segment of the research on power system resilience. Nowadays, quantities of research existing has been done to reduce the load loss after disasters. However, there is no clear methodologies or metrics available to evaluate the effects of restoration strategies. Here, a method for evaluating the recovery and economic efficiency of the power system post-disaster recovery strategy is explored, and assessment metrics related are defined. The method considers the repair and recovery process of transmission lines, generators, and the distributed generation at load nodes. After given the repair strategies, components state sampling and system power flow calculation will be conducted to analyse the running state of the system, then simulate the component repair and the load recovery procedure, and finally calculate corresponding metrics. This novel method can obtain and compare the expected effects of different restoration strategies in advance, providing more reliable reference information for system decision makers. Finally, the proposed method is applied to IEEE 14-bus system and verifies its effectiveness and application value.