# Resilience Quantification of Smart Distribution Networks--A Bird's Eye View Perspective
## 1 Introduction
The advent of smart grids renewed interest in enhancing the PDN performance [49] as nearly all SG provided abilities of self-healing, high reliability, energy management, and real-time pricing are empowered by technologies introduced at the distribution level such as advanced metering, automation, distributed generation, and distributed storage [50]. ICTs are the main enabler of this new portfolio of applications [7], by transforming a traditionally one-way, limited-control, and radial PDN into a two-way power flow, intelligent, and mesh-networked grid capable of guaranteeing improved service for all connected loads [51]. In this regard, expected high-performance capabilities of smart distribution grid can succeed in coping with most failures in the system [49; 50]. The smart PDN remains susceptible to HILP events, or even more prone in some cases, due to increased uncertainty (in events, load, distributed generation, market prices) [52; 53; 54] and strong dependency on telecommunications that widen the attack surface [55] and may cause undesirable cascade effects [56]. Consequently, the resilience of smart PDN becomes a concern from both electric and communication domain perspectives, as a failure in the telecommunication service may affect the electric service [57] and vice-versa [58]. Recent publications recommend a joint handling of smart PDN resilience quantification as the robustness and adaptation ability of a coupled system are even lower than a single system [56; 59; 60; 61]. However, such an approach needs to build upon a solid understanding of resilience assessment of electric and communication domains when considered distinctly. The present paper aims to set the ground for future joint evaluation of PDN resilience by reviewing relevant works, centered thus far on electric service, and to a lesser extent on ICT service. Essentially, the type of HILP event is identified from each selected contribution with details in the method used for contingency characterization. Also, the measure of performance, recognized as an enabler for resilience quantification [62], is tracked through this work to explain how it is defined and computed, relying usually on system modeling, or empirical and surrogate models in some cases. In addition, a classification based on the temporal phase where resilience evaluation takes place is proposed, which allows for addressing practical requirements of utility companies. The resilience phase-based approach was linked with different objectives of the assessment, from simple metrics evaluation, to either planning or response for survivability and recovery, achieved through a variety of improvement strategies for which allocation is optimized under the constraint of a limited budget. This bridges resilience studies and economic considerations in order to help stakeholders in investment plan elaboration and crisis decision-making. Aspects of cost, critical load, microgrids, and uncertainty of hazards, load, and distributed generation are discussed to show their high importance, and available tools to date for their involvement in the study. We extend by this work the wide spectrum of subjects associated with resilience quantification in power networks (modeling and simulation, enhancement strategies, metrics, and extreme events), covered in recent reviews [28; 36; 44; 45; 63; 64; 65]. The main contributions and novelty of this paper can be summarized as follows: (a) focus on resilience assessment of both electric and telecommunications domains of smart power distribution networks. (b) Detailed analysis and classification of performance calculation techniques. (c) Fine-grained categorization of quantitative resilience works based on time of evaluation and target objective.