Abstract
Security analysis is the task of evaluating security and reliability limits of the power system, up to what level the system is secure. Power system security is divided into four classes, namely secure, critically secure, insecure, and highly insecure, depending on the value of security index. A multi-class support vector machine (SVM) classifier algorithm is used, in this paper, to categorize the patterns. These patterns are generated at different generating and loading conditions for IEEE 6 bus, IEEE 14 bus, and New England 39 bus systems by Newton–Raphson load flow method for line outage contingencies. The main target is to give a forewarning or hint to the system operator at security level which helps to actuate requisite regulating actions at the suitable time, to put a stop to the system collapse.
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Seshasai, B., Santhi, A., Rao, C.J.M., Rao, B.M., Chandra Sekhar, G.T. (2017). Analysis of Static Power System Security with Support Vector Machine. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-10-3874-7_78
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DOI: https://doi.org/10.1007/978-981-10-3874-7_78
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