RETRRAC (Retrofittable Efficiency Technology for Resilient Refrigeration with AI-based Controls)

Perishable food items consistently account for over 50% of U.S. supermarket sales, but the refrigeration infrastructure vital for these items faces significant resiliency and efficiency issues. Due to low profit margins, the food retail sector routinely relies on legacy refrigeration equipment without investing in new, expensive alternatives. As a result, most food stores lack sufficient backup power or energy storage to continue running their refrigeration systems when a power outage strikes. In addition to lack of resilience, food stores face high operational costs due to the low efficiency of their commercial refrigeration systems. These systems are the largest energy consumers in food retail stores, constituting up to 62% of their energy usage. Through this SBIR project, Grid Fruit is developing Retrofittable Efficiency Technology for Resilient Refrigeration, an AIdriven controls technology that provides food businesses with resilience and efficiency benefits to save each supermarket an average of $36,000/year. Grid Fruit’s technology uses machine learning to put unused data to work for food businesses and power grids. The controls software improves compressor efficiency and minimizes peak demand by controlling commercial refrigeration and HVAC, reducing store greenhouse gas emissions by up to 15% while protecting food quality for our retail customers. In Phase I, Grid Fruit developed a machinelearningbased prediction platform with case temperatures as inputs to an optimization control algorithm to provide resilience and reduce aggregate demand of multiple refrigeration units. Their results show Grid Fruit’s optimal control reduces aggregate demand by 30% when no power outages are present. In an outage scenario with backup power, they demonstrate reductions in total electricity consumption of 28% across a twohour outage. They also reduce aggregate peak demand by 64% compared to typical thermostat controls when unlimited backup power is present. In Phase II, Grid will focus on the physical demonstration of the control schemes developed in Phase I and provide data visualization of these schemes in an online dashboard. The project will develop predictive analytics from the Phase I data and validate these analytics in commercial refrigeration systems. To alleviate barriers to adoption and manufacturing challenges, the project will develop an IoT hardware prototype with a form factor similar to existing commercial refrigeration thermometers. The refrigeration demo will test the IoT hardware and confirm it receives wireless commands from a central server, a necessary step for commercialization. At the end of Phase II, Grid Fruit will be ready to commercialize the technology as a Software as a Service package they will sell to food retail chains. Grid Fruit’s technology will enable commercial building refrigeration systems to be retrofitted for better energy resilience and energy efficiency. Based on pilot data, Grid Fruit estimates the energy resilience and efficiency gains will save food retailers 15% in operational and maintenance costs, a domestic savings of $4.4 billion annually.