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• W3217020979 abstract "One of the challenges of integrating renewable resources such as wind and solar energy into the existing electric power system is their rapid fluctuations that tends to decrease the reliability of the grid. Direct load control is one method to mitigate this variability and thermostatically controlled appliances such as air conditioners can play a significant role due to their large share to the total load. However, the system operator requires a reliable estimation about the magnitude of this load and how much it can be shifted. This paper presents a model-based forecasting method to provide a short-term load forecast of the controllable load. The main benefits of this method are 1) using real-time measurements to build a model of system; therefore, there is no need for a large historical measurements nor physical parameters, 2) fast response to the sudden changes in the system parameters. The performance of the proposed method was evaluated using a numerical simulator that shows it can generate forecasts with less than 6% error." @default.
• W3217020979 created "2021-12-06" @default.
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• W3217020979 date "2021-10-10" @default.
• W3217020979 modified "2023-09-24" @default.
• W3217020979 title "A Model-Based Short-term Load Forecast Methodology for Aggregated Power Consumption of Thermostatically Controlled Appliances in DSM" @default.
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• W3217020979 doi "https://doi.org/10.1109/ecce47101.2021.9595608" @default.
• W3217020979 hasPublicationYear "2021" @default.
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