Ensuring optimal energy efficiency of chiller plant systems has been a constant challenge that engineers work tirelessly to overcome as manually adjusting chiller plant setpoints are often time-consuming and require constant monitoring
from engineers. This is where our solution comes in.
Our application aims to use suitable ML models for finding the optimal setpoints for the chiller plant by iterating through a grid search algorithm and machine learning models to find the parameters that can result in the highest energy saving possible. In this way, not only can our application ease the jobs of engineers, but also help to make it more cost efficient for the consumer. Additionally,
Explainable AI is used for interpretation of model decisions, allowing the operators to understand the result of our AI model.