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An Intelligent Hybrid Model for Bus Load Forecasting in Electrical Short-Term Operation Tasks

An Intelligent Hybrid Model for Bus Load Forecasting in Electrical Short-Term Operation Tasks
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Author(s): Ricardo Menezes Salgado (Institute of Exact Sciences, Federal University of Alfenas, Brazil & University of Campinas, Brazil), Takaaki Ohishi (University of Campinas, Brazil)and Rosangela Ballini (Institute of Economics, University of Campinas, Brazil)
Copyright: 2012
Pages: 23
Source title: Handbook of Research on Industrial Informatics and Manufacturing Intelligence: Innovations and Solutions
Source Author(s)/Editor(s): Mohammad Ayoub Khan (Centre for Development of Advanced Computing, India)and Abdul Quaiyum Ansari (Jamia Millia Islamia, India)
DOI: 10.4018/978-1-4666-0294-6.ch023

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Abstract

The main objective of this chapter is to present a hybrid model for bus load forecasting. This approach represents an essential tool for the operation of the electrical power system and the hybrid model combines a bus clustering process and a load forecasting model. As a case study, the model was applied to the real Brazilian electrical system, and the results revealed a performance similar to that of conventional models for bus load forecasting, but about 14 times faster. The results are compatible with the safe operating load levels for the Brazilian electrical power system and have proved to be adequate for use in real operation tasks.

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