Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility
References:
[1] U.S. Energy Information Administration. “How much energy is
consumed in residential and commercial buildings in the United States?”
Available at: http://www.eia.gov/tools/faqs/faq.cfm?id=86&t=1
[2] S. Darby, “The effectiveness of feedback on energy consumption.”
Environmental Change Institute, University of Oxford, 2006. Available
at: http://www.globalwarmingisreal.com/energyconsump-feedback.pdf.
Visited: September 2015
[3] J. S. John, “Putting energy disaggregation tech to the test,” November,
2013. Greentech Media. Available at:
http://www.greentechmedia.com/articles/read/putting-energydisaggregation-tech-to-the-test.
Visited: September 2015
[4] A. Zoha, A. Gluhak, M. A. Imran, S. Rajasegarar, “Non-intrusive load
monitoring approaches for disaggregated energy sensing: a survey,”
Sensors, vol. 12, no. 12, pp. 16838-16866, December 2012.
[5] G. W. Hart, “Nonintrusive appliance load monitoring,” in Proc. of the
IEEE, vol. 80, pp. 1870-1891, December 1992.
[6] M. Baranski, J. Voss, “Non-intrusive appliance load monitoring based
on Optical Sensor,” IEEE Bologna PowerTech Conference, Bologna,
Italy, June 2003. Available at:
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1304732
[7] L. Farinaccio, R. Zmeureanu, “Using a pattern recognition approach to
disaggregate the total electricity consumption in a house into the major
en-uses,” Elsevier, Energy and Buildings, vol. 30, no. 3, pp. 245-259,
August 1999.
[8] J. M. Abreu, F. C. Pereira, P. Ferrão, “Using pattern recognition to
identify habitual behavior in residential electricity consumption,”
Elsevier, Energy and Buildings, vol. 49, pp. 479-487, June 2012.
[9] C. Beckel, L. Sadamori, S. Santini, “Automatic socio-economic
classification of households using electricity consumption data,” in
Proc. of the 4th international conference on future energy systems, New
York, 2013, pp. 75-86.
[10] H. Zhao, F. Magoulès, “A review on the prediction of building energy
consumption,” Elsevier, Renewable and Sustainable Energy Reviews,
vol. 16, no. 6, pp. 3586-3592, August 2012.
[11] G. K. F. Tso, K. K. W. Yau, “Predicting electricity energy consumption:
A comparison of regression analysis, decision tree and neural networks,”
Elsevier, Energy, vol. 32, no. 9, pp. 1761-1768, September 2007.
[12] F. Farzan, S. A. Vaghefi, K. Mahani, M. A. Jafari, J. Gong, “Operational
planning for multi-building portfolio in an uncertain energy market,”
Elsevier, Energy and Buildings, vol. 103, pp. 271-283, September 2015.