2020
Conference article  Open Access

Trading dependability and energy consumption in critical infrastructures: Focus on the rail switch heating system

Chiaradonna S., Di Giandomenico F., Masetti G.

Availability  Energy consumption  Railroad switch heating system  Stochastic modeling  Critical infrastructure  Reliability  Energy management 

Traditionally, critical infrastructures demand for high dependability, being the services they provide essential to human beings and the society at large. However, more recent attention to cautious usage of energy resources is changing this vision and calls for solutions accounting for appropriate multi-requirements combinations when developing a critical infrastructure. In such a context, analysis supports able to assist the designer in envisioning a satisfactory trade-off among the multi-requirements for the system at hand are highly helpful. In this paper, the focus is on the railway sector and the contribution is a stochastic model-based analysis framework to quantitatively assess trade-offs between dependability indicators and electrical energy consumption incurred by the rail switch heating system.Moving from a preliminary study that concentrated on energy consumption only, the analysis framework has been extended to become a solid support to devise appropriate tuning of the heating policy that guarantees satisfactory trade-offs between dependability and energy consumption. An evaluation campaign in a variety of climate scenarios demonstrates the feasibility and utility of the developed framework.

Source: 25th IEEE Pacific Rim International Symposium on Dependable Computing, pp. 150–159, Perth, Australia, 01/12/2021


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:446525,
	title = {Trading dependability and energy consumption in critical infrastructures: Focus on the rail switch heating system},
	author = {Chiaradonna S. and Di Giandomenico F. and Masetti G.},
	doi = {10.1109/prdc50213.2020.00026},
	booktitle = {25th IEEE Pacific Rim International Symposium on Dependable Computing, pp. 150–159, Perth, Australia, 01/12/2021},
	year = {2020}
}