Abstract: This disclosure relates generally to methods and systems for determining the power load disaggregation profile of a building. Most of the conventional techniques are algorithmic centric, specific to certain scenarios and does not employ the low-sampling rate data due to the complexity involved. Present disclosure determines the power load disaggregation profile of the building using the low-sampling rate power consumption data accurately. According to the present disclosure, firstly, the background power loads are detected and removed from the low-sampled data samples. Next, a robust event detection mechanism is employed to detect the events when the change in the power consumption occurred, and such events are paired using the iterative pairing technique. Further, a set of event clusters are formed using the density-based clustering technique and lastly, each of the set of event clusters are classified with each appliance type using a rule-based classification technique.