Converged Security and Information Management System as a Tool for Smart City Infrastructure Resilience Assessment

Current research on smart cities is primarily focused on the area of applicability of information and communication technologies. However, in the context of a multidisciplinary approach, it is also necessary to pay attention to the resilience and converged security of individual infrastructures. Converged security represents a particular security type based on a selected spectrum of certain convergent security types of, assuming the creation of a complementary whole. Considering the outputs of the analysis of security breaches manifestations, this kind of security makes it possible to detect emerging security breaches earlier (still in the symptom stage), thus providing a more efficient and targeted solution suitable for building smart city infrastructure. In its essence, the article refers to the practical application of the converged security theoretical principles presented in the publication to a functional sample, deployed and tested in practical conditions in context of selected smart city infrastructure protection and resilience. Considering the nature of the practical application, the convergence of a wider spectrum of smart security alarm systems in the resilience assessment context is defined. In the beginning, the general principles of security/safety and the need for their convergence are presented. In this context, the mathematical model called Converged Resilience Assessment (CRA) method is presented for better understanding. Subsequently, Physical Security Information Management (PSIM) and Security Information and Event Management (SIEM) systems are described as a technological concept that can be used for resilience assessment. The most beneficial part is the structural, process, and functional description of the Converged Security and Information Management System (CSIM) using the concept of smart security alarm systems converged security

Knee-Deep in Two "bathtubs'': Extending Holling's Ecological Resilience Concept for Critical Infrastructure Modeling and Applying It to an Offshore Wind Farm

Multistability is a common phenomenon which naturally occurs in complex networks. Many engineered infrastructures can be represented as complex networks of interacting components and sub-systems which possess the tendency to exhibit multistability. For analyzing infrastructure resilience, it thus seems fitting to consider a conceptual framework which incorporates the phenomenon of multistability – the ecological resilience provides such a framework. However, we note that the ecological resilience misses some aspects of infrastructure resilience. We therefore propose to complement the concept by two model extensions which consider the generation of perturbations to the infrastructure service and the remedial actions of service restoration after regime shifts. The result is a three-layer framework for modeling infrastructure resilience. We demonstrate this framework in an exemplary disturbance scenario in an offshore wind farm. Based on this use case, we further demonstrate that infrastructure resilience can benefit a lot from the notion of multistability

Estimating Hydrogen Usage of a Crew Transport Vessel Fleet for Offshore Windfarm Maintenance

Using hydrogen fuel may help to decarbonize maritime transportation. This paper presents an estimate for the mass of hydrogen that would be needed to power the current fleet of crew transport vessels used for maintaining the German offshore wind farms. The estimate is based on a calculation of the marine diesel oil consumption of the current fleet. We use vessel position data, weather data, and diesel consumption estimates to perform this calculation. Various hull shapes are used in small coastal vessels. This creates a challenge to estimate their energy needs. As a shortcoming, certain effects are excluded from the current estimate. However, this work presents an approach that can be improved and used for estimating hydrogen consumption in future scenarios. In these scenarios, a vessel type and parameters can be set. While here the challenge was to create a generic model that can be applied to multiple types of vessels

Validation of copula-based weather generator for maintenance model of offshore wind farm

This article discusses the aspect of modelling weather conditions in marine environment for implementation in the offshore wind farm domain. It is clear that harsh sea weather conditions influence many characteristics of any offshore installation. The accessibility to the infrastructure, maintenance procedures, failure ratios of components, energy provision levels, or utilization of vessels – are the examples of weather-related issues connected to the offshore wind industry. Regarding the growing popularity of digital twin methodology authors present a novel view to generate weather data with copula-based method. The results obtained are compared to selected historical data and implemented into the maintenance model. The selected indicators of maintenance service are used for usability assessment of proposed copula-based method

Resilient Recovery Features of Offshore Wind Farm with Maintenance Service

This work discusses the maintenance of Offshore Wind Farms in the context of resilience. Therefore, the relation between the system response to disruptions due to severe weather conditions and redundancy of operating vessels is analyzed. The study is executed using an appropriate simulation model, which employs reported component failures rates and real weather data. The obtained results indicate that redundancy of maintenance vessels has no effect on the robustness against severe weather conditions, but a considerable impact during the recovery phase

Influence of the Personnel Availability on Offshore Wind Farm Maintenance

Offshore Wind Farms (OWFs) have rising importance for energy provision of many regions worldwide. However, their harsh environment leads to considerably higher failure rates and degradation compared to its onshore counterparts. Consequently, OWFs require well-established maintenance processes in order to provide required operational availability of all wind turbines. Amongst the several factors impacting these processes the personnel plays an important role, bearing in mind that no maintenance is possible without having access to technicians or seamen operating the required vessel. This work proposes a comprehensive model for evaluating the actual impact the personnel availability has on the corrective maintenance processes of an OWF and, consequently, its energy production. Therefore, maintenance processes and WT failure rates based on reported data are considered. Furthermore, a pandemic model is employed in order to elaborate the possible impact a health crisis can have on the operational availability of an OWF. Results indicate that the monthly energy production can drop by up to 74% in case of a constant reduction of the personnel by 50%, while a worst case pandemic scenario results in a 23% lower energy production over the whole year

Indicator-based Safety and Security Assessment of Offshore Wind Farms

Bearing in mind their exposed position and the rising importance for power provision, Offshore Wind Farms (OWFs) are facing a multitude of safety and also security threats. This leads to growing interest in methods for real-time and longterm assessment of the safety and security state of this type of infrastructure. Following this observation, we present the concept of a methodology for the indicator-based assessment of the security and safety of OWFs, which employs key performance indicators as well as key risk indicators. These indicators enable the online monitoring of the infrastructure, but also the exploration of its response to hazardous events - a fundamental requirement for resilience assessment. The applicability of the proposed technique is explored at hand of exemplary scenarios