Visible to the public Biblio

Filters: Author is Sarvestani, S.S.  [Clear All Filters]
2015-05-01
Albasrawi, M.N., Jarus, N., Joshi, K.A., Sarvestani, S.S..  2014.  Analysis of Reliability and Resilience for Smart Grids. Computer Software and Applications Conference (COMPSAC), 2014 IEEE 38th Annual. :529-534.

Smart grids, where cyber infrastructure is used to make power distribution more dependable and efficient, are prime examples of modern infrastructure systems. The cyber infrastructure provides monitoring and decision support intended to increase the dependability and efficiency of the system. This comes at the cost of vulnerability to accidental failures and malicious attacks, due to the greater extent of virtual and physical interconnection. Any failure can propagate more quickly and extensively, and as such, the net result could be lowered reliability. In this paper, we describe metrics for assessment of two phases of smart grid operation: the duration before a failure occurs, and the recovery phase after an inevitable failure. The former is characterized by reliability, which we determine based on information about cascading failures. The latter is quantified using resilience, which can in turn facilitate comparison of recovery strategies. We illustrate the application of these metrics to a smart grid based on the IEEE 9-bus test system.

Marashi, K., Sarvestani, S.S..  2014.  Towards Comprehensive Modeling of Reliability for Smart Grids: Requirements and Challenges. High-Assurance Systems Engineering (HASE), 2014 IEEE 15th International Symposium on. :105-112.


Smart grids utilize computation and communication to improve the efficacy and dependability of power generation, transmission, and distribution. As such, they are among the most critical and complex cyber-physical systems. The success of smart grids in achieving their stated goals is yet to be rigorously proven. In this paper, our focus is on improvements (or lack thereof) in reliability. We discuss vulnerabilities in the smart grid and their potential impact on its reliability, both generally and for the specific example of the IEEE-14 bus system. We conclude the paper by presenting a preliminary Markov imbedded systems model for reliability of smart grids and describe how it can be evolved to capture the vulnerabilities discussed.