A Methodology for Modeling Interoperability for Smart Sensors in Smart Grids
Edward Griffor, Eugene Song, Kang B. Lee, Gerald J. FitzPatrick
Smart sensors in smart grids (SGs) can provide real-time data and status of modernized, bidirectional flows of energy, electrical power grids for monitoring, protection, and control of grid operations to improve reliability and resilience. Smart sensor data exchange and interoperability are major challenges for SGs. Interoperability of systems or components is defined by the Institute of Electrical and Electronics Engineers (IEEE) as the ability of two or more systems or components to exchange information and to use the information that has been exchanged. We interpret and analyze this definition in this setting by formalizing the relationship between state models of systems and evidence for information exchange and use. To render an interpretation of interoperability testable and measurable, it is required that such evidence can be manipulated and assessed computationally. This paper proposes a methodology for modeling interoperability for smart sensors in terms of interactions using labeled transition systems (LTSs) and finite state processes (FSPs) in order to provide a measurement and automated assessment of the interoperability of smart sensors. The interaction that passes messages from a sender to a receiver is proposed as a method to model interoperability between them. A case study is provided to illustrate this model for the interoperability between IEEE C37.118 phasor measurement unit- based smart sensors and phasor data concentrators. By constructing an expression in the language of LTSs and FSPs that can be executed across the SG networks, this model provides an approach to measuring and automated assessment of the interoperability of smart sensors in order to support efforts to assure the interoperability of devices and systems in SGs.
, Song, E.
, Lee, K.
and FitzPatrick, G.
A Methodology for Modeling Interoperability for Smart Sensors in Smart Grids, IEEE Transactions on Smart Grid, [online], https://doi.org/10.1109/TSG.2021.3124490
(Accessed November 30, 2023)