Open AccessGame framework for optimal allocation of spinning reserve to confront intelligent physical attacks on power system
Author(s) -
Ranjbar Mohammad Hossein,
Kheradmandi Morteza,
Pirayesh Abolfazl
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6005
Subject(s) - spinning , probabilistic logic , electric power system , computer science , operator (biology) , game theory , computer security , scheme (mathematics) , power (physics) , operations research , reliability engineering , engineering , artificial intelligence , economics , microeconomics , mechanical engineering , physics , quantum mechanics , mathematical analysis , biochemistry , chemistry , mathematics , repressor , transcription factor , gene
Spinning reserve (SR) serves as an efficient tool to respond to a sudden outage of power system components caused by either natural events or physical attacks. Contrary to natural threats, the intelligent physical attacks are strongly influenced by the measures taken by the system operator to defend the system and exhibit no stochastic behaviour. As a consequence, the probabilistic methods of SR provision and allocation do not prove to be appropriate to confront intelligent attacks. In this study, the interaction between the system operator as the defender and the intelligent attacker is investigated within a game model. In this model, the SR is allocated in such a way that the highest interruption cost that the attacker can impose is minimised. The technical limitations of SR provision together with operational constraints are taken into consideration. The efficacy of the proposed method is examined by conducting case studies of single and multiple‐target attacks on components of IEEE 24‐bus and IEEE 118‐bus test systems. The results show that the proposed scheme produces a considerable reduction in the system interruption cost in comparison with the probabilistic methods.