{"id":410,"date":"2023-10-31T16:08:31","date_gmt":"2023-10-31T20:08:31","guid":{"rendered":"https:\/\/sense.com\/resource-center\/smart-homes-smarter-grids-how-sense-is-shaping-the-future-of-energy-management\/"},"modified":"2025-06-18T14:30:57","modified_gmt":"2025-06-18T18:30:57","slug":"smart-homes-smarter-grids-how-sense-is-shaping-the-future-of-energy-management","status":"publish","type":"resources","link":"https:\/\/sense.com\/resources\/smart-homes-smarter-grids-how-sense-is-shaping-the-future-of-energy-management\/","title":{"rendered":"Smart Homes, Smarter Grids: How Sense is Shaping the Future of Energy Management"},"content":{"rendered":"

Sense has partnered with Fraunhofer USA<\/a> and Boston University to deliver on a Department of Energy<\/a> (DOE) pilot program. This project is part of the DOE\u2019s nearly $83 million in funding to 44 projects that aim to lower Americans\u2019 energy bills<\/a> by investing in new energy-efficient building technologies, construction practices, and the U.S. buildings-sector workforce.<\/p>\n

The project, entitled \u201cHigh Fidelity Self-Learning Tool for Residential Load and Load Flexibility Forecasting<\/em>\u201d aims to develop a self-learning computation tool that will continuously monitor and forecast major energy loads in the home (HVAC, water heating, electric vehicles), as well as on-site power generation (PV solar), to determine an optimal dispatch schedule that reduces utility grid load without compromising occupant comfort, and potentially achieving cost-savings for the end user.<\/p>\n

By collaborating on the project, Sense aims to improve its algorithms and ability to help its users reduce their carbon footprint. Potentially helping customers save money \u2013 while maintaining their comfort and having a minimal impact on their day.<\/p>\n

The Why and the How<\/h3>\n

Sense is working to advance device detection methods which will help improve energy science modeling. The goal is to improve energy management programs, significantly contributing to a brighter, cleaner future!<\/p>\n

The program will show how the incorporation of data from multiple sources can be used to model household net load and increase the accuracy of generation and load forecasts, as well as improve Sense\u2019s device detection capabilities. Some of the sources include communicating thermostats & EVs, smart appliances, weather forecasts and predictive formulas developed by our partner Fraunhofer.<\/p>\n

Sense will analyze the data from registered devices, ensuring first and foremost that all data is isolated and anonymized. Our goal is to gather valuable insights into energy usage patterns, enhance thermostat and EV detection, and contribute to the advancement of energy management technologies while prioritizing customer preferences and comfort. Through micro-actuation setpoints and charging actions, Sense will improve its ability to give you customized reporting on Energy Savings, Appliance performance, and potential fault detections.<\/p>\n

Through this pilot, Sense aims to improve its existing features through:<\/p>\n