Power system security assessment studies are carried out on a regular basis off-line by expert engineers in order to verify the reliability of a system and take appropriate decisions when necessary. Such decisions may concern system expansion or changes in operating rules used in real-time to cope with the security/economy tradeoff. Under open access, such studies are also carried out in order to determine and publish total transfer capacity values on various interfaces (or corridors). Traditionally, these studies are based on a small, but carefully selected, subset of scenarios (typically peak load, with and without planned outages) for which simulation tools are used in order to assess the potential insecurities of a list of credible contingencies. Traditionally, also, there has been a tendancy to underestimate the size of the so determined security region in order to cope with various uncertainties and second order effects which could not be taken into account explicitly and systematically with the restricted set of scenarios used for a study. Today, because of the necessity to open the transmission system to a maximum number transactions to avoid discrimination and/or under-utilization of the system, there is a strong pressure from various actors (gencos, consumers, traders, regulators) in order to push the security limits as far as possible, so as to avoid unjustified uplift costs. At the same time, the environment of the transmission system has become less predictible than in the past. Thus, engineers are now faced with more uncertainties and higher pressure to optimize and justify their decisions in the context of security. Consequently, there is also a stronger need for security assessment methodologies and tools which would allow to increase the quality of decision rules designed, while explicitly taking into account a number of uncertainties and helping to objectively justify the decisions.

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{{Explor lien
   |wiki=    Wicri/Belgique
   |area=    OpenAccessBelV2
   |flux=    OpenAccess
   |étape=   Analysis
   |type=    RBID
   |clé=     Pascal:04-0201025
   |texte=   Data Mining for power system security assessment: A large scale study
}}