A common analysis framework for smart distribution networks applied to survivability analysis of distribution automation

Koziolek, Anne; Happe, Jens; Avritzer,; Suresh, Vignesh

doi:10.1109/se4sg.2012.6225713

Cited by 9 publications

(13 citation statements)

References 6 publications

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“…Modelbased design has proven to be an effective way of modeling complex systems and has been applied in the context of evaluation of attributes of the smart grid, including a modeldriven analysis framework for smart distribution networks based on the Common Information Model (CIM) [24], and for model-based CPES co-simulation [25].…”

Section: Related Workmentioning

confidence: 99%

Uncertainty Analysis of Middleware Services for Streaming Smart Grid Applications

Akkaya¹,

Liu

Lee³

2016

IEEE Trans. Serv. Comput.

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Abstract-Accuracy and responsiveness are two key properties of emerging cyber-physical energy systems (CPES) that need to incorporate high throughput sensor streams for distributed monitoring and control applications. The electric power grid, which is a prominent example of such systems, is being integrated with high throughput sensors in order to support stable system dynamics that are provisioned to be utilized in real-time supervisory control applications. The end-to-end performance and overall scalability of cyber-physical energy applications depend on robust middleware services that are able to operate with variable resources and multi-source sensor data. This leads to uncertain behavior under highly variable sensor and middleware topologies. We present a parametric approach to modeling the middleware service architecture for distributed power applications and account for temporal satisfiability of system properties under network resource and data volume uncertainty. We present a heterogeneous modeling framework that combines Monte Carlo simulations of uncertainty parameters within an executable discrete-event middleware service model. By employing Monte Carlo simulations followed by regression analysis, we quantify system parameters that significantly affect behavior of middleware services and the achievability of temporal requirements.

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Section: Related Workmentioning

confidence: 99%

Uncertainty Analysis of Middleware Services for Streaming Smart Grid Applications

Akkaya¹,

Liu

Lee³

2016

IEEE Trans. Serv. Comput.

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“…In other work, cf. [36,35], we show how these input parameters can be derived for existing power grids and how investments can be optimised. We have also applied the approach to a distribution automation benchmark derived from a German medium voltage distribution network [35].…”

Section: Case Studymentioning

confidence: 99%

Survivability Evaluation of Gas, Water and Electricity Infrastructures

Avritzer

Carnevali

Ghasemieh

et al. 2015

Electronic Notes in Theoretical Computer Science

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The infrastructures used in cities to supply power, water and gas are consistently becoming more automated. As society depends critically on these cyber-physical infrastructures, their survivability assessment deserves more attention. In this overview, we first touch upon a taxonomy on survivability of cyber-physical infrastructures, before we focus on three classes of infrastructures (gas, water and electricity) and discuss recent modelling and evaluation approaches and challenges.

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“…Several approaches utilize the Common Information Model (CIM) as a model to combine several traditional power system analyses [4,23]. These approaches focus on the interoperability of different energy management subsystems.…”

Section: Related Workmentioning

confidence: 99%

“…CIM contains standard-based entities and attributes to present the semantics of power system entities and their organization. [23,18].…”

Section: Related Workmentioning

confidence: 99%

Modeling and Simulation of Network Aspects for Distributed Cyber-Physical Energy Systems

Akkaya

Liu

Lee

2015

Cyber Physical Systems Approach to Smart Electric Power Grid

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Abstract. Electric power grids are presently being integrated with sensors that provide measurements at high rates and resolution. The abundance of sensor measurements, as well as the added complexity of applications trigger a demand for cyber-physical system (CPS) modeling and simulation for evaluating the characteristics of appropriate network fabrics, timing profiles and distributed application workflow of power applications. Although simulation aids in the pre-deployment decision making process, system models for complex CPS can quickly become impractical for the purposes of specialized evaluation of design aspects. Existing modeling techniques are inadequate for capturing the heterogeneous nature of CPS and tend to inherently couple orthogonal design concerns. To address this issue, we present an aspect-oriented modeling and simulation paradigm. The aspectoriented approach provides a separation between functional models and crosscutting modeling concerns such as network topology, latency profiles, security aspects, and quality of service (QoS) requirements. As a case study, we consider a three-area smart grid topology and demonstrate the aspect-oriented approach to modeling network and middleware behavior for a distributed state estimation application. We also explore how aspects leverage scalable co-simulation, fault modeling, and middleware-in-the loop simulation for complex smart grid models.

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A common analysis framework for smart distribution networks applied to survivability analysis of distribution automation

Cited by 9 publications

References 6 publications

Uncertainty Analysis of Middleware Services for Streaming Smart Grid Applications

Uncertainty Analysis of Middleware Services for Streaming Smart Grid Applications

Survivability Evaluation of Gas, Water and Electricity Infrastructures

Modeling and Simulation of Network Aspects for Distributed Cyber-Physical Energy Systems

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