Istituto di Scienza e Tecnologie dell'Informazione     
Chiaradonna S., Di Giandomenico F., Masetti G. A stochastic modelling framework to analyze smart grids control strategies. In: SEGE 2016 - 4th IEEE International Conference on Smart Energy Grid Engineering (Oshawa, Canada, 21-24 August 2016). Proceedings, pp. 123 - 130. IEEE, 2016.
assess representative indicators of the resilience and quality of service of the distribution grid, in presence of accidental faults and malicious attacks. The results from the performed analysis can be exploited to understand the dynamics of failures and to identify potential system vulnerabilities, against which appropriate countermeasures should be developed. The features of the proposed analysis framework are discussed, pointing out the strong non-linearity of the involved physics, the developed solutions to deal with control actions and the definition of indicators under analysis. A case study based on a number of application sectors, several of which are critical from the perspective of human life, environment or financials. It is therefore paramount to be assisted by technologies able to analyze the smart grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this paper, we present a stochastic modelling framework to quantitatively Smart grids Abstract- provide services at the basis of a real-world network is also presented
URL: http://ieeexplore.ieee.org/document/7589512/
DOI: 10.1109/SEGE.2016.7589512
Subject Smart grids
Stochastic activity networks
Stochastic models
Model based evaluation
Quantitative analysis

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