Resilience assessment and planning in power distribution systems:Past and future considerations

Over the past decade, extreme weather events have significantly increased worldwide, leading to widespread power outages and blackouts. As these threats continue to challenge power distribution systems, the importance of mitigating the impacts of extreme weather events has become paramount. Consequently, resilience has become crucial for designing and operating power distribution systems. This work comprehensively explores the current landscape of resilience evaluation and metrics within the power distribution system domain, reviewing existing methods and identifying key attributes that define effective resilience metrics. The challenges encountered during the formulation, development, and calculation of these metrics are also addressed. Additionally, this review acknowledges the intricate interdependencies between power distribution systems and critical infrastructures, including information and communication technology, transportation, water distribution, and natural gas networks. It is important to understand these interdependencies and their impact on power distribution system resilience. Moreover, this work provides an in-depth analysis of existing research on planning solutions to enhance distribution system resilience and support power distribution system operators and planners in developing effective mitigation strategies. These strategies are crucial for minimizing the adverse impacts of extreme weather events and fostering overall resilience within power distribution systems.Comment: 27 pages, 7 figures, submitted for review to Renewable and Sustainable Energy Review

Current capabilities, requirements and a proposed strategy for interdependency analysis in the UK

The UK government recently commissioned a research study to identify the state-of-the-art in Critical Infrastructure modelling and analysis, and the government/industry requirements for such tools and services. This study (Cetifs) concluded with a strategy aiming to bridge the gaps between the capabilities and requirements, which would establish interdependency analysis as a commercially viable service in the near future. This paper presents the findings of this study that was carried out by CSR, City University London, Adelard LLP, a safety/security consultancy and Cranfield University, defense academy of the UK

Application of a Blockchain Enabled Model in Disaster Aids Supply Network Resilience

The disaster area is a dynamic environment. The bottleneck in distributing the supplies may be from the damaged infrastructure or the unavailability of accurate information about the required amounts. The success of the disaster response network is based on collaboration, coordination, sovereignty, and equality in relief distribution. Therefore, a reliable dynamic communication system is required to facilitate the interactions, enhance the knowledge for the relief operation, prioritize, and coordinate the goods distribution. One of the promising innovative technologies is blockchain technology which enables transparent, secure, and real-time information exchange and automation through smart contracts. This study analyzes the application of blockchain technology on disaster management resilience. The influences of this most promising application on the disaster aid supply network resilience combined with the Internet of Things (IoT) and Dynamic Voltage Frequency Scaling (DVFS) algorithm are explored employing a network-based simulation. The theoretical analysis reveals an advancement in disaster-aids supply network strategies using smart contracts for collaborations. The simulation study indicates an enhance in resilience by improvement in collaboration and communication due to more time-efficient processing for disaster supply management. From the investigations, insights have been derived for researchers in the field and the managers interested in practical implementation

The State-of-the-Art Survey on Optimization Methods for Cyber-physical Networks

Cyber-Physical Systems (CPS) are increasingly complex and frequently integrated into modern societies via critical infrastructure systems, products, and services. Consequently, there is a need for reliable functionality of these complex systems under various scenarios, from physical failures due to aging, through to cyber attacks. Indeed, the development of effective strategies to restore disrupted infrastructure systems continues to be a major challenge. Hitherto, there have been an increasing number of papers evaluating cyber-physical infrastructures, yet a comprehensive review focusing on mathematical modeling and different optimization methods is still lacking. Thus, this review paper appraises the literature on optimization techniques for CPS facing disruption, to synthesize key findings on the current methods in this domain. A total of 108 relevant research papers are reviewed following an extensive assessment of all major scientific databases. The main mathematical modeling practices and optimization methods are identified for both deterministic and stochastic formulations, categorizing them based on the solution approach (exact, heuristic, meta-heuristic), objective function, and network size. We also perform keyword clustering and bibliographic coupling analyses to summarize the current research trends. Future research needs in terms of the scalability of optimization algorithms are discussed. Overall, there is a need to shift towards more scalable optimization solution algorithms, empowered by data-driven methods and machine learning, to provide reliable decision-support systems for decision-makers and practitioners

The design of effective and robust supply chain networks

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2009-2010Pour faire face aux risques associés aux aléas des opérations normales et aux périls qui menacent les ressources d'un réseau logistique, une méthodologie générique pour le design de réseaux logistiques efficaces et robustes en univers incertain est développée dans cette thèse. Cette méthodologie a pour objectif de proposer une structure de réseau qui assure, de façon durable, la création de valeur pour l'entreprise pour faire face aux aléas et se prémunir contre les risques de ruptures catastrophiques. La méthodologie s'appuie sur le cadre de prise de décision distribué de Schneeweiss et l'approche de modélisation mathématique qui y est associée intègre des éléments de programmation stochastique, d'analyse de risque et de programmation robuste. Trois types d'événements sont définis pour caractériser l'environnement des réseaux logistiques: des événements aléatoires (ex. la demande, les coûts et les taux de changes), des événements hasardeux (ex. les grèves, les discontinuités d'approvisionnement des fournisseurs et les catastrophes naturelles) et des événements profondément incertains (ex. les actes de sabotage, les attentats et les instabilités politiques). La méthodologie considère que l'environnement futur de l'entreprise est anticipé à l'aide de scénarios, générés partiellement par une méthode Monte-Carlo. Cette méthode fait partie de l'approche de solution et permet de générer des replications d'échantillons de petites tailles et de grands échantillons. Elle aide aussi à tenir compte de l'attitude au risque du décideur. L'approche générique de solution du modèle s'appuie sur ces échantillons de scénarios pour générer des designs alternatifs et sur une approche multicritère pour l'évaluation de ces designs. Afin de valider les concepts méthodologiques introduits dans cette thèse, le problème hiérarchique de localisation d'entrepôts et de transport est modélisé comme un programme stochastique avec recours. Premièrement, un modèle incluant une demande aléatoire est utilisé pour valider en partie la modélisation mathématique du problème et étudier, à travers plusieurs anticipations approximatives, la solvabilité du modèle de design. Une approche de solution heuristique est proposée pour ce modèle afin de résoudre des problèmes de taille réelle. Deuxièmement, un modèle incluant les aléas et les périls est utilisé pour valider l'analyse de risque, les stratégies de resilience et l'approche de solution générique. Plusieurs construits mathématiques sont ajoutés au modèle de base afin de refléter différentes stratégies de resilience et proposer un modèle de décision sous risque incluant l'attitude du décideur face aux événements extrêmes. Les nombreuses expérimentations effectuées, avec les données d'un cas réaliste, nous ont permis de tester les concepts proposés dans cette thèse et d'élaborer une méthode de réduction de complexité pour le modèle générique de design sans compromettre la qualité des solutions associées. Les résultats obtenus par ces expérimentations ont pu confirmer la supériorité des designs obtenus en appliquant la méthodologie proposée en termes d'efficacité et de robustesse par rapport à des solutions produites par des approches déterministes ou des modèles simplifiés proposés dans la littérature

Minimising flood risk accumulation through effective private and public sector engagement

Flooding is a global problem affecting both developing and developed countries. Academics and practitioners in climate science frequently argue that changing climatic conditions are likely to worsen the length and severity of these flood events, which will have catastrophic consequences to economies and social lives of communities world over. Whilst the overall consequences affecting many regions have been established, effective and efficient strategies to cope with the effects of flooding and building up resilience strategies have not properly evolved. This paper examines this issue by exploring effective strategies undertaken in partnerships between private and public stakeholders. The paper details two case studies conducted in a developed and a developing country to investigate what global strategies for coping and resilience to flooding have worked in practice. The two case studies: Cockermouth in Cumbria, UK and Patuakhali in Bangladesh provide interesting insights on how some of the strategies work within the chosen developed and developing country contexts. The case study findings are mapped against UNISDR’s ten-point checklist under the “Making Cities Resilient Campaign”. In conclusion the paper examines how these findings can be incorporated within city development plans to develop stakeholder capacity and capability and eventually build up resilient cities