Paper
12 October 2006 Decision support in power systems based on load forecasting models and influence analysis of climatic and socio-economic factors
Cláudio A. Rocha, Ádamo L. de Santana, Carlos R. Francês, Ubiratan Bezerra, Armando Tupiassú, Vanja Gato, Liviane Rego, João Costa
Author Affiliations +
Proceedings Volume 6383, Wavelet Applications in Industrial Processing IV; 63830I (2006) https://doi.org/10.1117/12.686433
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Abstract
This paper presents a decision support system for power load forecast and the learning of influence patterns of the socio-economic and climatic factors on the power consumption based on mathematical and computational intelligenge methods, with the purpose of defining the future power consumption of a given region, as well as to provide a mean for the analysis of correlations between the power consumption and these factors. Here we use a linear modelo of regression for the forecasting, also presenting a comparative analysis with neural networks, to prove its efectiveness; and also Bayesian networks for the learning of causal relationships from the data.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cláudio A. Rocha, Ádamo L. de Santana, Carlos R. Francês, Ubiratan Bezerra, Armando Tupiassú, Vanja Gato, Liviane Rego, and João Costa "Decision support in power systems based on load forecasting models and influence analysis of climatic and socio-economic factors", Proc. SPIE 6383, Wavelet Applications in Industrial Processing IV, 63830I (12 October 2006); https://doi.org/10.1117/12.686433
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Cited by 7 scholarly publications.
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KEYWORDS
Climatology

Data modeling

Decision support systems

Neural networks

Visualization

Systems modeling

Databases

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