Improving Energy Use Forecast for Campus Micro-grids Using Indirect Indicators

@article{Aman2011ImprovingEU,
  title={Improving Energy Use Forecast for Campus Micro-grids Using Indirect Indicators},
  author={S. Aman and Y. Simmhan and V. Prasanna},
  journal={2011 IEEE 11th International Conference on Data Mining Workshops},
  year={2011},
  pages={389-397}
}
  • S. Aman, Y. Simmhan, V. Prasanna
  • Published 2011
  • Computer Science
  • 2011 IEEE 11th International Conference on Data Mining Workshops
  • The rising global demand for energy is best addressed by adopting and promoting sustainable methods of power consumption. We employ an informatics approach towards forecasting the energy consumption patterns in a university campus micro-grid which can be used for energy use planning and conservation. We use novel indirect indicators of energy that are commonly available to train regression tree models that can predict campus and building energy use for coarse (daily) and fine (15-min) time… CONTINUE READING
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    References

    SHOWING 1-10 OF 16 REFERENCES
    Applying support vector machines to predict building energy consumption in tropical region
    • 501
    Occupancy-driven energy management for smart building automation
    • 505
    • PDF
    Energy-savings predictions for building-equipment retrofits
    • 73
    • PDF
    Toward data-driven demand-response optimization in a campus microgrid
    • 18
    • PDF
    Long-term energy demand predictions based on short-term measured data
    • 68
    A classification and regression tree model of controls on dissolved inorganic nitrogen leaching from European forests.
    • 53
    Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression
    • 558