Chiller Staging Controller for Multi-Chiller Efficiency Optimization
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Solution Overview
Problem
Conventional HVAC system controllers activate and deactivate chillers based on cooling load requirements, leading to inefficient operation in multi-chiller systems, as they do not optimize the number of chillers online or their operational sequence for maximum efficiency.
Innovation Solution
A method and system that determine the thermal load and current efficiency of a chiller group, generate performance curves for each chiller to relate thermal transfer rate with power consumption parameters, and strategically bring online or offline chillers to optimize efficiency, using a weighted average of estimated efficiencies to decide staging operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional HVAC system controllers activate and deactivate chillers based primarily on cooling load requirements, then the cooling load is met, but the chiller operation efficiency is suboptimal
Solution Approach 1:
The system changes the control parameters from simple on/off decisions based solely on cooling load to a multi-parameter optimization approach that considers individual chiller efficiency characteristics, thermal load requirements, and operational sequencing. This enables the controller to select optimal chiller combinations and operational orders to maximize overall system efficiency.
Solution Approach 2:
The control system transitions from static on/off control to dynamic optimization that continuously evaluates multiple chiller configurations and selects the most efficient operational sequence based on current thermal load conditions and individual chiller performance characteristics.
2Power
If multiple chillers are operated simultaneously to meet peak cooling capacity requirements, then the cooling capacity is sufficient, but the energy consumption increases
Solution Approach 1:
The system applies partial action by selectively activating only the necessary number of chillers required to meet the current thermal load, rather than operating all available chillers. The operational sequencing ensures that chillers are brought online in an optimized order to minimize energy consumption while providing sufficient cooling capacity.
Solution Approach 2:
The system applies different operational strategies to different chillers based on their individual efficiency characteristics and performance curves. Each chiller is evaluated and selected for operation based on its specific local efficiency properties rather than treating all chillers uniformly.
3Temperature
If chillers are cycled on and off to maintain building temperature, then the temperature control is achieved, but the efficiency optimization is lost
Solution Approach 1:
The system incorporates feedback by continuously monitoring the thermal load requirements and evaluating the efficiency impact of different chiller operational sequences. This feedback mechanism enables the controller to adjust the chiller staging strategy to maintain temperature control while minimizing energy loss through optimized cycling patterns.
Data Source
AI summary
Systems, methods, and computer program products for staging chillers in a chiller group. Operational data is collected on chillers in a chiller group, and performance curves indicative of chiller efficiency generated for each chiller based on the operational data. During operation, a current thermal load and a current group efficiency is determined for the chiller group. Estimated group efficiencies are also determined for the chiller group for one or more scenarios in which one or more offline chillers are brought online, online chillers are taken offline, or both online chillers are taken offline and offline chillers are brought online. If the estimated efficiency of the chiller group is higher than the current efficiency for any of the scenarios, chillers in the chiller group are brought online or taken offline so that the chiller group operates in accordance with the most efficient scenario.