Poster Abstract: Predicting the Power Consumption of Electric Appliances through Time Series Pattern Matching

We present a system to forecast the power consumption of electric household appliances. Accurate load prediction has numerous application domains, e.g., the facilitation of peak load prediction at a much higher resolution than permitted by state-of-the-art load profiles. Our solution is based on the identification and isolation of representative character-istic signatures from previously collected power consump-tion traces. Subsequently, time series pattern matching is applied to detect these signatures in real-time data, and emit predictions of an appliance’s future consumption based thereupon. We evaluate the prediction accuracy of our ap-proach with thousands of device-level power consumption traces and highlight the achievable prediction horizon