[UC34] EV & Appliance Disaggregation

The Utility Problem

Energy disaggregation, or appliance disaggregation, breaks down a building’s total energy use to individual appliance-level consumption. This method deciphers the overall power signal using algorithms and machine learning to associate energy use with specific appliances, recognizing their unique operational patterns. Its benefits include:

• Energy Management: Allows users, be it homeowners or facility managers, to spot energy-intensive appliances and consider energy-saving decisions.
• Load Profiling & Demand Response: Assists utilities in creating detailed customer load profiles, aiding in tailored demand response programs such as Time-of-Use rates.
• Billing & Tariff Optimization: Analyzing specific equipment consumption, like EVs or solar panels, helps utilities propose better tariffs, enhancing data quality.

For utilities, energy disaggregation is crucial. It provides detailed insights into appliance-level energy use, helping in demand response programs, grid management, and infrastructure planning. As the energy sector evolves, such analytics become pivotal for efficiency and addressing customer and grid needs.

Awesense’s use cases are constantly evolving. Request free access to our Sandbox trial and GitHub repository to see the full use case descriptions and implementations, and to learn how you can create new use cases yourself.