Solution

It’s hard to manage what you can’t even measure, and  traditional controls capture only a fraction of what matters in a central plant. Few of these traditional systems can even measure total chilled water output, and none can account for the complex thermodynamic and hydraulic interactions between pumps, chillers, and cooling towers.

These controls are also inherently reactive. They adjust setpoints and stage equipment in response to current conditions, but they are usually tuned for design-day scenarios that occur only a small fraction of the time. Because they cannot anticipate — or even measure — the consequences of their control moves, they may create stability issues that lie hidden until they turn into production problems.

The symptoms are familiar – if not always visible:

• Flow reversals in decoupler lines
• Chiller surge
• Frequent on/off cycling
• Excess stress on pumps, motors, and compressors

These issues accelerate equipment wear, increase the risk of unexpected failures that threaten uptime, and drive higher energy and water use. In fact, our measurements have shown near-instantaneous 100% increases in equipment loads and energy consumption triggered solely by a reactive control – even though nothing else had changed in the plant.

Advanced Measurement
SHIFT EOS features innovative measurement software based on recent advances in Machine Learning to measure the hydraulics and thermodynamics of every component in every branch of the plant. These measurement data serve two purposes; first, they enable Model Predictive Control, and second, they provide reliability and maintenance teams with engineering-grade data that has never before been available in the field.

Model Predictive Control (MPC) was pioneered in the late 1970s in process industries like oil refining and petrochemicals to handle complex, multivariable systems that conventional control methods could not. By using a dynamic model of the process to forecast behavior hours ahead, MPC enabled operators to maintain tighter control of quality, efficiency, and stability than traditional reactive controls ever could.

EOS extends this proven approach to chilled water plants. Its Predictive Digital Twin continuously measures the thermodynamic and hydraulic state of the plant, forecasts demand and performance hours ahead and evaluates thousands of possible control strategies. It then identifies the optimal control actions that maximize stability, keep the plant within operating limits, and minimize the total cost of energy and water.

Ensuring Equipment and System Reliability
In mission-critical plants, reliability depends on anticipating problems before they cause disruption. With the EOS Digital Twin, reliability engineers gain – for the first time – precise thermodynamic and hydraulic measurements for every major component. This visibility allows them to detect degradation early, trace root causes accurately, and take preventive action that protects uptime, improves chilled water delivery, and maintains compliance with regulatory standards.

Operators have learned to keep these plants running even with the limited capabilities of traditional control systems. EOS gives operations teams new foresight to get ahead of issues by forecasting cooling loads, predicting plant behavior, and recommending optimal control moves in advance. Each control recommendation is accompanied by a clear explanation, and operators can preview the resulting plant performance before acting. (In optional automatic mode, EOS communicates directly with the BAS to apply control settings.) With this support, operations teams have demonstrated steadier plant performance, eliminated well known instabilities such as flow reversals, chiller surge, and short cycling, and cut both energy costs and water consumption by double digits.

Sustainability managers are under pressure to deliver energy, carbon, and water savings that show rapid ROI and withstand external scrutiny. After years of incremental improvements, many have exhausted the easiest opportunities, leaving only costly and uncertain options.

EOS changes this in three ways:

Unlocks New Efficiency Gains — delivering 10–20% reductions in water and 20% energy savings from existing central plants, with minimal to no capital upgrades.

Quantifies Benefits Before Deployment — the EOS Digital Twin can simulate your plant with its exact piping, chillers, towers, pumps, load profile, and weather data, providing confidence in savings that drive your ROI.

Verifies Results Automatically — once deployed, EOScool provides real-time measurement and verification (M&V) of energy and water savings, eliminating the need for costly, time-consuming manual studies.

The Result: reliable, transparent proof of savings that supports ESG reporting and builds confidence in sustainability investments.