Simulation-based validation for Smart Grid environments: Framework and experimental results

Wonkyu Han, Mike Mabey, Gail-Joon Ahn, Tae Sung Kim

Research output: Contribution to journalArticle

Abstract

Large and complex systems, such as the Smart Grid, are often best understood through the use of modeling and simulation. In particular, the task of assessing a complex system’s risks and testing its tolerance and recovery under various attacks has received considerable attention. However, such tedious tasks still demand a systematic approach to model and evaluate each component in complex systems. In otherwords, supporting a formal validation and verification without needing to implement the entire system or accessing the existing physical infrastructure is critical since many elements of the Smart Grid are still in the process of becoming standardized for widespread use. In this chapter, we describe our simulation-based approach to understanding and examining the behavior of various components of the Smart Grid in the context of verification and validation. To achieve this goal, we adopt the discrete event system specification (DEVS) modeling methodology, which allows the generalization and specialization of entities in the model and supports a customized simulation with specific variables. In addition, we articulate metrics for supporting our simulation-based verification and validation and demonstrate the feasibility and effectiveness of our approach with a real-world use case.

Original languageEnglish (US)
Pages (from-to)27-44
Number of pages18
JournalAdvances in Intelligent Systems and Computing
Volume263
DOIs
StatePublished - 2014

Fingerprint

Large scale systems
Critical infrastructures
Discrete event simulation
Specifications
Recovery
Testing

Keywords

  • Discrete event system specification
  • Risk assessment
  • Simulation
  • Smart grid
  • Validation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Simulation-based validation for Smart Grid environments : Framework and experimental results. / Han, Wonkyu; Mabey, Mike; Ahn, Gail-Joon; Kim, Tae Sung.

In: Advances in Intelligent Systems and Computing, Vol. 263, 2014, p. 27-44.

Research output: Contribution to journalArticle

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