Facility power usage modeling and short term prediction with artificial neural networks

  • Authors:

  • Sunny Wan;Xiao-Hua Yu

  • Affiliations:

  • Department of Electrical Engineering, California Polytechnic State University, San Luis Obispo, CA;Department of Electrical Engineering, California Polytechnic State University, San Luis Obispo, CA

  • Venue:
  • ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
  • Year:
  • 2010

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Abstract

Residential and commercial buildings accounted for about 68% of the total U.S electricity consumption in 2002 Improving the energy efficiency of buildings can save energy, reduce cost, and protect the global environment In this research, artificial neural network is employed to model and predict the facility power usage of campus buildings The prediction is based on the building power usage history and weather conditions such as temperature, humidity, wind speed, etc Different neural network configurations are discussed; satisfactory computer simulation results are obtained and presented.