SBIR-STTR Award

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be the reduction in home energy costs, electric grid system costs, and environmental impacts from electricity generation. The proposed research project will advance the state of the art in residential combined heating and hot water technology. The research project will resolve the technical risks associated with operating a high-efficiency CO2 heat pump in combined heating and hot water applications, and with implementing efficient load shifting in these applications. The project has the potential to reduce user energy costs, grid system costs, and environmental impacts by: shifting electrical load from peak demand times to off-peak demand times, reducing the need for costly and highly polluting peak power generation resources, and integrating variable renewable energy resources, such as wind and solar at times of low demand. This will put downward pressure on electric rates, as well as provide immediate user bill savings through lower demand and by shifting electricity demand to the cheapest times. The proposed system has the potential for large-scale commercial deployment due to its significantly lower operating costs and lowered initial fixed investments.This Small Business Innovation Research (SBIR) Phase I project aims to resolve technical challenges associated with the commercial deployment of high-efficiency CO2 heat pumps in combined heating and hot water applications. CO2 heat pumps have demonstrated high efficiency in hot water applications with coefficients of performance up to 5. However, they typically operate much less efficiently in combined systems due to a lack of advanced controls. The research will develop a thermal stratification model of a hot water tank based on customer use and charging conditions, a predictive thermal demand model, and a simulation model of the whole system integrating heat pump performance, tank stratification, and predictive customer demand. The project will then develop new controls (hardware and software) to optimize for user and grid costs and emissions and validate the effectiveness of the resulting control system by integrating it into the existing prototype. This assessment will demonstrate the commercial viability of CO2-based combined heat and hot water systems with load shifting.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to enable a novel heating and hot water system that reduces energy use and emissions without compromising comfort. The replacement of gas/oil-fueled heating and hot water systems by efficient electric alternatives is critical to reduce (GHG) emissions from the building sector that accounts for nearly one-third of emissions worldwide. These reductions are achieved through electrification enhanced by “load shifting,” the practice of consuming energy from the grid at times when it is cheapest and cleanest, and storing that energy for use in the home all day (including peak usage times). The project goals are to improve the reliability, security, and scalable manufacturability of this system, making it affordable to install for most households. Residential-scale load shifting will help the housing industry move from fossil fuel-based heating to meet emissions reduction requirements in a cost-effective way. The load shifting capability using readily available hot water storage allows utilities to balance the energy grid and increase the deployment of renewable energy sources with reduced infrastructure costs, as well as reduce greenhouse gas (GHG) emissions. This SBIR Phase II project proposes to address the technical risks facing large scale deployment of heating and hot water load shifting to enable rapid deployment of high-efficiency heat pump systems for residential applications in the United States. The project will systematically build knowledge of system-level performance, reliability, and failure modes. Cost drivers in system integration and storage density will be addressed and improved. Secure cloud computing architecture and machine learning will address technical barriers to wide-spread optimization of loads. Taken together, the program supports the capability to deploy reliable, secure, tested hardware and software as a solution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.