Non Intrusive Load Monitoring and Load Disaggregation using Transient Data Analysis

Non Intrusive Load Monitoring (NILM) is gaining importance due to its crucial role in energy management and conservation. NILM uses smart meter data (aggregated power, current, power factor, etc.), and based on unique load signatures, it identifies different loads in operation at any point of time. Thus, enabling, direct feedback and control of energy consumption by different home appliances. This also helps in demand-response management and peak demand reduction by shifting operation of non-critical loads during non-peak periods. Earlier works are mainly focused on steady-state power supply data and, complex feature extraction and classification algorithms. This paper discusses the load disaggregation technique based on transient current data with common features, viz. RMS, THD, Mean, standard deviation, etc. Hence, resulting into a simple and cost-effective technique with reasonable performance.