期刊
IEEE TRANSACTIONS ON SMART GRID
卷 2, 期 3, 页码 507-518出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2011.2145010
关键词
Data visualization; demand forecasting; demand response; energy efficiency; energy management; load management; regression analysis
资金
- U.S. Department of Energy [DE-AC02-05CH11231]
- California Energy Commission (CEC) [500-03-026]
- University of California, Berkeley
We present methods for analyzing commercial and industrial facility 15-min-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to ask the right questions to discover opportunities for demand response, energy efficiency, electricity waste elimination, and peak load management. We primarily focus on demand response. Methods discussed include graphical representations of electric load data, a regression-based electricity load model that uses a time-of-week indicator variable and a piecewise linear and continuous outdoor air temperature dependence and the definition of various parameters that characterize facility electricity loads and demand response behavior. In the future, these methods could be translated into easy-to-use tools for building managers.
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