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Day-ahead hourly electricity load modeling by functional regression

  • Published:2016-05 Issue: Volume:170 Page:455-465
  • ISSN:0306-2619
  • Container-title:Applied Energy
  • language:en
  • Short-container-title:Applied Energy

Author:

Feng Yonghan,Ryan Sarah M.

Funder

U.S. Department of Energy ARPA-e program under the Green Energy Network Integration (GENI) program

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference55 articles.

1. Long term forecasting of hourly electricity consumption in local areas in Denmark;Andersen;Appl Energy,2013

2. Seasonal climate forecasts for medium-term electricity demand forecasting;De Felice;Appl Energy,2015

3. Short-term load forecasting methods: an evaluation based on European data;Taylor;IEEE Trans Power Syst,2007

4. Hong T. short term electric load forecasting, Ph.D. thesis. North Carolina State University; 2011.

5. Functional clustering and linear regression for peak load forecasting;Goia;Int J Forecast,2010

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