LIT 2: foresee™

LIT 2: foresee™

Residential buildings generally lack sensors and building automation systems, which leaves operating decisions up to individual appliances' controllers and to homeowner discretion. Because homes are the largest segment of electricity use and dominate peak load, the opportunity for energy savings and cost reduction are significant—and is increasingly possible due to the rapid adoption of connected "smart" appliances. The National Renewable Energy Laboratory (NREL) has developed foresee™, software that automates connected residential devices to deliver these and other benefits, customized for every home. Lab experiments have shown that over 20% utility cost savings can be achieved, and firm, reliable demand response service delivered in a homeowner-friendly way.

Market Needs

Homeowners lack a tool to simply and uniformly manage connected devices in their homes. Today, they are instead forced to use individual appliance/manufacturer apps, and/or program rules themselves. foresee™ helps by coordinating across communication protocols to seamlessly integrate many devices and automate how they run. It prioritizes that operation based on homeowner goals and values, such as saving money, improving air comfort, increasing hot water service, conveniently operating schedulable appliances, and reducing environmental footprint. Finally, foresee™ enables higher PV penetrations vs. utility practice today.

Value Proposition

foresee™ simplifies operation of a smart home and delivers outcomes based on homeowner-provided preferences and incentives from third parties like utilities. This results in at least 10% utility cost savings (typically $200+/year saved) and a payback time less than 3 years. It also can deliver several kW demand response reliably from a home, depending on the equipment and weather.

Benefited Parties

Homeowners will be able to get more benefit from connected products than any one product or manufacturer can do on its own, in line with their values and goals.

Utilities will achieve higher DR participation, knowing that there is low risk of customer dissatisfaction.

Builders will have a strong selling feature and reduce utility challenges to high-penetration rooftop solar installations.


NREL is finalizing our initial R&D effort, and discussing field trials and commercialization strategy. Several companies have expressed strong interest in licensing foresee™.


Dane Christensen

Team Lead, Residential Systems Performance, National Renewable Energy Laboratory

PhD Mechanical Engineering, University of California-Berkeley

BS Mechanical Engineering, Rice University

Dr. Christensen leads a team of energy geeks at the National Renewable Energy Laboratory (NREL), focusing on transformational data, control and integration for sensors, analytics, appliances, homes, buildings and communities. Dane joined NREL in 2008 with a goal to optimize buildings for their installed environment, software platforms for community-scale sustainability, and next-generation energy management algorithms and systems. They perform hands-on demonstrations of prototype and product alike, in both laboratories such as NREL's Systems Performance Lab as well as in real-world homes and buildings, to confirm product performance, understand and overcome failure modes, and verify positive impacts such as enhanced comfort, convenience, utility costs, ancillary services, and environmental benefits. Dane has over 40 peer-reviewed publications, three issued patents, and numerous software copyrights, patents pending and other innovative ventures.

Xin Jin

Controls Engineer, National Renewable Energy Laboratory

PhD Mechanical Engineering, Pennsylvania State University

MS Electrical Engineering, Pennsylvania State University

MS Mechanical Engineering, Pennsylvania State University

BS Mechanical Engineering, Shanghai Jiao Tong University, China

Xin Jin joined National Renewable Energy Laboratory (NREL) in 2012. His research focuses on control systems, fault detection and diagnosis, load monitoring and disaggregation, and grid-integrated building systems. Xin's background is in sensors and controls, machine learning, and embedded systems. Prior to his current position at NREL, Xin worked as a project engineer at A.O. Smith Corporate Technology Center creating innovative electronic control solutions for water heaters and was a postdoctoral researcher at NREL developing automated home energy management technologies.