Skip to main content
The PACE AI Suite consists of a rugged, UL-listed industrial IoT edge node, with cloud-based AI/ML to both optimize and monitor Heating Ventilation Air Conditioning and Refrigeration (HVACR) equipment. It can be used for both building and industrial process heating/cooling applications. Each installation delivers remote dashboarding from any mobile device, with easy-to-use cloud API for interoperability with a wide range of building and process systems. PACE AI Suite's proven, patented AI/ML technology has reliably delivered 20-25% or more energy cost savings for a wide range of cooling, heating, and refrigeration equipment, in various climate zones in North America/Caribbean.
The PACE AI Suite is breakthrough edge+cloud technology to deliver connectivity, 24/7 monitoring, and predictive maintenance, and optimization for the equipment that heats and cools the world. The patented PACE AI/ML technology has reliably delivered 20-25% or more energy cost savings for a very wide range of cooling, heating, and refrigeration equipment, proven in various climate zones in North America and the Caribbean. The PACE AI Suite is qualified for many energy-efficiency incentives and rebates across North America, which may cover 50% and more of installed cost, and is qualified as well for utility On-Bill Funding programs, which are zero-upfront-cost ways for commercial electric- and gas-utility clients to pay for energy-saving projects.
PACE AI Suite HVACR monitoring node + cloud-base AI/ML optimization
In vapor-compression cooling and refrigeration, which is the vast majority of equipment worldwide, cooling and dehumidification are both driven by heat transfer through the heat exchanger (evaporator), and the vaporization of the refrigerant as it passes through the evaporator. PACE AI/ML optimizes compressor/fan/pump operation to enhance machine response to each control input, either from a thermostatic input or a building or process automation system. The result: improved energy efficiency and average demand reduction, plus component benefits, without compromising performance.
<Office cooling unit energy consumption vs. outside temperature, without (blue) and with (red) PACE AI online>
Similarly to cooling and refrigeration systems, energy is consumed in the transfer of thermal energy across the heat exchanger from its production by gas- or oil-fired burners or by electric resistance elements. PACE AI/ML technology is able to learn the call and response of the thermostatic input, optimizing burner and heating element operation to more closely match the demand in real time. The result: improved energy efficiency and fossil fuel savings, plus component benefits, without compromising performance.
<Retail heating unit energy consumption vs. outside temperature, without (blue) and with (red) PACE AI online>
Photo of smartphone-sized PACE Node in New York City rooftop HVAC unit: installs in 30-45 minutes, 25%+ energy savings plus real-time monitoring, fault detection and predictive maintenance
According to U.S. Energy Information Administration (EIA) Commercial Buildings Energy Consumption Survey in 2012*, food service, inpatient health care and food sales buildings are the top 3 energy users (see Figure 1 below). Food-service building consume large amounts of energy primarily for cooking and refrigeration, which consist of 40% of total energy consumption (64% including heating and cooling).
Figure 1: EIA survey: Total Energy Use per Square Foot
It is a significant challenge for QSRs to reduce energy consumption while they maintain food-safe temperatures in refrigeration unit to meet Food Safety Modernization Act (FSMA) safety requirement (click here to learn more about FSMA).
The post-retrofit kWh reduction was determined on a winter-baselined, degree-day-normalized basis for months (June-September) and compared to the same period during the previous year. The kWh overall savings were calculated at 9% (Figure 2). Figure 3 presents the normalized monthly restaurant kWh consumption for the summer months year over year, pre- vs. post-retrofit installation.
Figure 2: Pre-vs. post-retrofit kWh consumption comparison
Figure 3: The normalized monthly restaurant kWh consumption comparison
For the heading season, the gas reduction (CCFs) using a similar summer-baselined, degree-day-normalized procedure during a year-over-year comparison, was calculated at 16%. Figure 4 below shows a before- and after-comparison example.
Figure 4: Before- and after-comparison example