**2. Measurement of Percentage THD, a Single Feature for Load Consumption Pattern Identification**

PQ data are useful not only for assessing the quality of power for consumption and compensation aspects, but also for load pattern identification [32]. In particular, harmonic data can be found among PQ data. Among harmonic data, such as harmonic amplitudes, harmonic phases and percentage THD, the latter is found to be helpful to uniquely identify load patterns. Therefore, accurate measurement of percentage THD is essential for load identification. In general, the percentage THD of a current's harmonic signal is measured using FFT. If the measurements of harmonic orders are not accurate then the percentage THD value will be erroneous. FFT measurements have limitations such as spectral leakage and the picket fence effect [37,38]. Recently, EDLIFFT with a 4MSW for real-time harmonic estimation was proposed in [37], which overcame both the drawbacks of FFT. By using this algorithm, the harmonic orders are measured and the percentage THD of any given load pattern is computed as in Equation (1) [39,40]:

$$Percentage\text{ Current THD} = \frac{\sqrt{\sum\_{n=2}^{H} I\_n}}{I\_{fund}}\tag{1}$$

where

*H* = harmonic order *In* = *nth* harmonic current *Ifund* = fundamental current

Thus, we can employ percentage THD as a simple database lookup to find which combinations of appliances are in operation at any point in time. The rated power of all appliances is a known value, so we can compute the energy consumed by individual appliances for the time they spend operation. This lookup table is used to create the disaggregated load by appropriating the rated power of the appliance. The total sum of the active power at any point is compared to the power measured at the energy meter. This information, when applied with contextual data like occupancy, ambient temperature, etc., can deduce unnecessary use of appliances and can be shared with the customer suggest potential savings.
