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• W3080927722 abstract "The objective of this project is to develop and evaluate a load forecasting technique that gives input to a demand management algorithm for a building in the presence of a Time-of-Use demand rate structure. The objective of the demand management controller is to minimize the annual electricity bill with the help of behind-the-meter energy storage by shifting the load partially from peak pricing periods. The forecasting algorithm uses a two-stage method where a deterministic part uses an exponentially weighted moving average (EWMA) model accounting for longer-term trends and a third-order regression model (AR3) accounting for the short-term variations. It is shown that a very small increase in forecasting error can result in a significant loss of the annual savings achieved by a demand response controller. A building in University Campus with a highly dynamic load profile is considered for studies." @default.
• W3080927722 created "2020-09-01" @default.
• W3080927722 creator A5051519232 @default.
• W3080927722 creator A5070878209 @default.
• W3080927722 date "2020-06-01" @default.
• W3080927722 modified "2023-09-28" @default.
• W3080927722 title "Effect of Forecaster Performance on Peak Shaving in a University Building by Battery Scheduling" @default.
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• W3080927722 doi "https://doi.org/10.1109/icps48389.2020.9176774" @default.
• W3080927722 hasPublicationYear "2020" @default.
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