Abstract
Thermostatically controlled loads (TCLs) are playing a promising role in demand response (DR) programs as a result of their huge capability. It tends to be difficult to accurately obtain aggregated performances of TCLs when they are controlled to provide services for the grid as a result of the insufficient and inaccurate physical parameters. In order to address this problem, high dimensional model representative (HDMR) is employed to build the relationship between aggregated performance index (i.e. the baseline power, capacity and cold load pickup) of TCLs and the uncertain physical parameters. Then aggregated TCL performances can be estimated by fewer important parameters quickly and accurately, which will save lots of efforts for constructing TCL models with DR functionality by paying less attention to unimportant parameters. Simulations demonstrate that the aggregated performance index of TCLs can be accurately calculated by HDMR.
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