SBIR Phase II: A Low-Emissions Heating and Hot Water System

这个小型企业创新研究（SBIR）项目的更广泛的影响/商业潜力是实现一种新型的供暖和热水系统，在不影响舒适性的情况下减少能源使用和排放。用高效的电力替代品取代天然气/石油燃料的供暖和热水系统对于减少建筑行业的温室气体排放至关重要，该行业占全球排放量的近三分之一。这些减少是通过“负荷转移”增强电气化来实现的，负荷转移是在最便宜和最清洁的时候从电网消耗能源，并将这些能源储存起来供家庭全天使用（包括高峰使用时间）。该项目的目标是提高该系统的可靠性，安全性和可扩展的可制造性，使其能够为大多数家庭安装。住宅规模的负荷转移将有助于住房行业从基于化石燃料的供暖转向以具有成本效益的方式满足减排要求。利用随时可用的热水储存的负荷转移能力使公用事业能够平衡能源电网，并在降低基础设施成本的情况下增加可再生能源的部署，并减少温室气体（GHG）排放。该SBIR第二阶段项目旨在解决大规模部署供暖和热水负荷转移所面临的技术风险，以实现在美国住宅应用中快速部署高效热泵系统。该项目将系统地建立系统级性能、可靠性和故障模式的知识。系统集成和存储密度方面的成本驱动因素将得到解决和改善。安全的云计算架构和机器学习将解决广泛优化负载的技术障碍。总的来说，该计划支持部署可靠、安全、经过测试的硬件和软件作为解决方案的能力。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.