Abstract
The electrical network should ensure that an adequate supply is available to meet the estimated load of the consumers in both the near and more distant future. This must of course, be done at minimum possible cost consistent with satisfactory reliability and quality of the supply. In order to avoid excessive voltage drop and minimise loss, it may be economical to install apparatus to balance or partially balance the loads. It is believed that the technology to achieve an automatic load balancing lends itself readily for the implementation of different types of algorithms for automatically rearranging the connection of consumers on the low voltage side of a feeder for optimal performance. In this paper the authors present a Support Vector Machines (SVM) implementation. The loads are first normalised and then sorted before applying the SVM to do the balancing.
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Jordaan, J.A., Siti, M.W., Jimoh, A.A. (2008). Distribution Feeder Load Balancing Using Support Vector Machines. In: Fyfe, C., Kim, D., Lee, SY., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2008. IDEAL 2008. Lecture Notes in Computer Science, vol 5326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88906-9_9
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DOI: https://doi.org/10.1007/978-3-540-88906-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88905-2
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