Forecasting for smart energy: an accurate and effificient negative binomial additive model
Smart energy requires accurate and effificient short-term electric load forecasting to enable effificient energy management and active real-time power control. Forecasting accuracy is inflfluenced by the char acteristics of electrical load particularly overdispersion, nonlinearity, autocorrelation a...
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Main Authors: | , , , |
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Format: | EJournal Article |
Published: |
Institute of Advanced Engineering and Science,
2020-11-01.
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Online Access: | Get fulltext |
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Call Number: |
A1234.567 |
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Copy 1 | Available |