“…There have been some co-simulation tools and platforms that capture power system and communication system interactions but are exclusively for transmission systems such as GECO [75] and EPOCHS [76]. Some of the tools such as FNCS and HELICS have been developed, which are capable of cosimulating distribution systems and communication networks and can study interactions such as the effects of communication network characteristics on the transmission network and distribution grid performance [77][78][79]. The capabilities of the cosimulators can be leveraged for numerous resilience use cases.…”
Section: Co-simulation Of Interdependent Systemsmentioning
Distribution system resilience is an emerging topic of interest given an increasing number of extreme events and adverse impacts on the power grid (e.g. Hurricane Maria and Ukraine cyber-attack). The concept of resilience poses serious challenges to the power system research community given varied definitions and multivariate factors affecting resilience. The ability of nature or malicious actors to disrupt critical services is a real threat to the life of our citizens, national assets and the security of a nation. Many examples of such events have been documented over the years. Promising research in this area has been in progress focused on the quantification and in enabling resilience of the distribution system. The objective of this study is to provide a detailed overview of distribution system resilience, the classification, assessment, metrics for measuring resilience, possible methods for enabling resilience, and the associated challenges. A new multi-dimensional and multi-temporal resilience assessment framework is introduced along with a research roadmap outlining the future of resilience to help the reader conceptualise the theories and research gaps in the area of distribution system cyber-physical resilience.
“…There have been some co-simulation tools and platforms that capture power system and communication system interactions but are exclusively for transmission systems such as GECO [75] and EPOCHS [76]. Some of the tools such as FNCS and HELICS have been developed, which are capable of cosimulating distribution systems and communication networks and can study interactions such as the effects of communication network characteristics on the transmission network and distribution grid performance [77][78][79]. The capabilities of the cosimulators can be leveraged for numerous resilience use cases.…”
Section: Co-simulation Of Interdependent Systemsmentioning
Distribution system resilience is an emerging topic of interest given an increasing number of extreme events and adverse impacts on the power grid (e.g. Hurricane Maria and Ukraine cyber-attack). The concept of resilience poses serious challenges to the power system research community given varied definitions and multivariate factors affecting resilience. The ability of nature or malicious actors to disrupt critical services is a real threat to the life of our citizens, national assets and the security of a nation. Many examples of such events have been documented over the years. Promising research in this area has been in progress focused on the quantification and in enabling resilience of the distribution system. The objective of this study is to provide a detailed overview of distribution system resilience, the classification, assessment, metrics for measuring resilience, possible methods for enabling resilience, and the associated challenges. A new multi-dimensional and multi-temporal resilience assessment framework is introduced along with a research roadmap outlining the future of resilience to help the reader conceptualise the theories and research gaps in the area of distribution system cyber-physical resilience.
“…Transformers [16]. Integrated T&D systems: [17–19]. Smart grid, ICT and communication systems: [2, 20–29].…”
Section: Literature Reviewmentioning
confidence: 99%
“…This approach requires a communication middleware to maintain synchronisation and data exchange. Examples include framework for network co‐simulation (FNCS) [17], VPNET [37], and EPOCHS [68]. Global event: A global event list is prepared that schedules simulator events according to their time‐stamps.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In [70], a new co‐simulated framework called hierarchical engine for large‐scale infrastructure co‐simulation (HELICS) is proposed for modelling transmission and distribution physical phenomena, communication infrastructure, and bulk and distributed market (TDC + M) interactions. HELICS has improved some features of FNCS [17] such as the implementation of high‐level architecture, increase the framework scalability, and support co‐iteration within a time step to guarantee the convergence among federates. In [71], a new architecture is used to design a quasi‐static (hourly interval) T&D co‐simulation framework with a tight coupling protocol to study the impact of bulk volt/VAR control (VVC) on the transmission system.…”
“…Ref. [21] describes an open-source "framework for network co-simulation" (FNCS) for power system transmission and distribution dynamics co-simulation. FNCS provides libraries for supporting C, Java, Matlab, Python and FORTRAN interfaces for flexible simulator integration.…”
Scientists and engineers involved in the design of complex system solutions use computational workflows for their evaluations. Along with growing system complexity, the complexity of these workflows also increases. Without integration tools, scientists and engineers are often highly concerned with how to integrate software tools and model sets, which hinders their original research or engineering aims. Therefore, a new framework for streamlining the creation and usage of automated computational workflows is introduced in the present article. It uses state-of-the-art technologies for automation (e.g., container-automation) and coordination (e.g., distributed message oriented middleware), and a microservice-based architecture for novel distributed process execution and coordination. It also supports co-simulations as part of larger workflows including additional auxiliary computational tasks, e.g., forecasting or data transformation. Using Apache NiFi, an easy-to-use web interface is provided to create, run and control workflows without the need to be concerned with the underlying computing infrastructure. Initial framework testing via the implementation of a real-world workflow underpins promising performance in the realms of parallelizability, low overheads and reliable coordination.
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