This paper presents the analysis and development of a new approach to monitor and update the  on–off  status of appliances in residential loads (RSLs). The proposed approach is structured to employ power meter readings   $P$   to determine the values for the magnitude   $\vert \bar{S}\vert $   and phase   $\theta$   of the apparent power. The value of   $\vert \bar{S}\vert $  , associated with a value of   $P$  , is determined using Newton iterations, where a value of   $\theta$   is calculated using six phaselet frames during each iteration. Once the iterations converge, the values of   $P$   and   $\theta$   are used to construct the ZIP model (polynomial model) for the RSL, from which   $P$   is provided. The constructed ZIP model provides the values for the constants   $K_{pf}$   and   $K_{qf}$   that relate the change in frequency to the active and reactive power demands of the modeled load. The obtained values of   $K_{pf}$   and   $K_{qf}$   are compared to standardized values that are defined for each appliance in an RSL. The ZIP model-phaselet frame approach is implemented as an algorithm for monitoring the  on–off  status of appliances in RSLs. The algorithm for the proposed approach is developed without a need to collect data for training. Test results show simple implementation, good accuracy, and insensitivity to variations in energy demands.
['Petrus Pijnenburg', 'S. A. Saleh', 'Peter McGaw']
Performance Evaluation of the ZIP Model-Phaselet Frame Approach for Identifying Appliances in Residential Loads