Artificial Intelligence Improves the Efficiency of Chillers

Artificial Intelligence (AI) continues to advance in everyday practical applications. Machinery such as chiller systems will benefit from AI algorithms that can detect potential failures before they occur. Predictive maintenance leverages the collection and analysis of chiller system operational data to determine when maintenance actions should be taken prior to catastrophic failure. As chillers systems represent the heart of most modern HVAC systems, the prevention of catastrophic failures that produce significant “downtime” will save on emergency repair costs as well as reputation. The critical role played by a chiller system warrants the increased scrutiny. Big Data and AI will minimize downtime and maximize productivity.

The Internet of Things (IoT) provides the data collection tool that can enable AI applications such as predictive maintenance. In fact, the future of HVAC is AI and IoT. IoT enables the collection of real-time data from a chiller to enable continual analysis of its operation. The granular IoT data collected from a chiller will go far beyond that obtained by visual inspection. IoT connects building engineers to real-time visibility of critical HVAC assets, thereby enabling informed monitoring of actual operating conditions.

Optimization

Chillers operate as part of a complex HVAC system. Water-cooled chillers have greater complexity due to the connection to a cooling tower system. Evaluating overall chiller plant performance will therefore involve an analysis of total power consumption of the compressor, pumps, cooling tower fans, etc. to evaluate comprehensive efficiency measures such as kW/ton.

Optimization of the overall chiller plant must be performed holistically. Various adjustments focusing on optimal chilled water set points, chiller sequencing and load balancing, peak demand management, cooling tower water management, etc. can only be performed with operational data. IoT can provide the tools for such optimization by providing real-time monitoring of power consumption from each part of the chiller plant, supply/return temperatures from the chiller and cooling tower, water flow rates from the condenser water loop, etc. IoT has found practical application in HVAC to facilitate true optimization.

Conclusion

Chiller operational efficiency will greatly impact your building operating costs. Ongoing routine maintenance represents the minimum from the perspective of facility management. Predictive maintenance and optimization of the chiller system requires real-time operational data. IoT has opened the door to new forms of chiller efficiencies.

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