Chiller Efficiency Curve Measurement for Multi-Chiller Load Optimization
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Solution Overview
Problem
Existing chiller efficiency determination methods rely on estimates or testing, which are inaccurate and costly, especially for older chillers, leading to suboptimal energy management in multi-chiller systems, as building automation systems lack precise data to orchestrate chiller operation for maximum efficiency across varying loads.
Innovation Solution
A method where chillers measure and calculate their own efficiency curves by monitoring temperature and power consumption across a range of operating capacities, using sensors and a control system to generate accurate efficiency data for the building automation system, allowing for dynamic optimization of chiller operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chiller efficiency is determined using estimates or testing methods, then the process is simple and low-cost, but the accuracy of efficiency data is poor
Solution Approach 1:
The chiller system performs self-measurement of its own efficiency characteristics by incorporating sensors and control systems that automatically collect operating data (power consumption, temperatures, flow rates) and generate efficiency curves without requiring external testing equipment or manual intervention
Solution Approach 2:
The system continuously monitors chiller operating parameters through sensors and feeds this data back to the control system, which automatically calculates efficiency metrics and updates efficiency curves in real-time, enabling continuous improvement of measurement accuracy
2Measurement precision
If chiller efficiency is determined through detailed testing, then the accuracy of efficiency data is high, but the cost and time required increase significantly
Solution Approach 1:
The system continuously collects operating data during normal chiller operation without requiring separate testing periods, transforming the chiller's regular operational cycles into opportunities for efficiency measurement and curve generation
Solution Approach 2:
The system proactively collects and stores operating parameter data during normal operation in advance, so that when efficiency determination is needed, the data is already available for immediate analysis and curve generation
3Productivity
If building automation systems use estimated efficiency data, then system operation is simple, but energy management optimization is suboptimal
Solution Approach 1:
The control system serves multiple functions: it not only controls chiller operation but also simultaneously collects operating data, calculates efficiency metrics, generates efficiency curves, and provides optimization recommendations, eliminating the need for separate measurement systems
Data Source
AI summary
The present disclosure relates to a method for determining an efficiency curve of a chiller that includes operating a chiller over a range of operating capacities, measuring a temperature of water entering the chiller at an initial capacity, measuring a temperature of water exiting the chiller at the initial capacity, measuring a power consumption of the chiller at the initial capacity, calculating an initial efficiency of the chiller at the initial capacity, measuring a plurality of temperatures of water entering the chiller at a plurality of capacities, measuring a plurality of temperatures of water exiting the chiller at each of the plurality of capacities, measuring a plurality of power consumptions at each of the plurality of capacities, calculating a plurality of efficiencies at each of the plurality of capacities, and generating an efficiency curve for the chiller with the initial efficiency and the plurality of efficiencies.