ACE IoT has launched a new YouTube channel - @ACEIoTSolutions! In the coming months, members of the ACE IoT technical team will record deep-dive technical conversations on topics of interest to Smart Buildings practitioners. Our first interview was with Iain Stewart of Exergenics, discussing Chiller Plant Optimization.
In the interview, Andrew Rodgers delves into the world of chillers and chiller plants with the help of industry expert Iain Stewart, co-founder and CEO of Exergenics. Iain shares generously his extensive knowledge and experience working on chiller optimization projects. For folks who are just starting to think about how chiller optimization projects might have value for their organization or for their customers, Iain provides a comprehensive overview of essential project components and uses plain language to describe and explain how chillers work.
What is a Chiller Optimization Plant Project?
Chiller plant optimization involves optimizing chillers, pumps and cooling towers using a systems approach aiming to: 1) always meet the building load, 2) improve system stability, 3) improve plant Coefficient of Performance (CoP) or kW/ton, and 4) extend equipment life.
For folks who have more experience with Chiller Plant Optimization projects, Andrew and Iain discuss effective strategies to maximize efficiency and minimize energy consumption, including: ongoing tuning, black-box optimization, and digital twin generative controls. Andrew and Iain agree that, regardless of the chosen strategy, chiller plant optimization projects involve a three-step process related to understanding limits, trade-offs, and equipment staging. Limits must be understood to correctly determine optimal trades-offs, just as trade-offs must be understood to correctly determine optimal equipment staging.
Limits:
In the context of Chiller Optimization projects, limits refer to physical limitations or constraints of the system of equipment within the plant. These limits can include minimum cooling tower fan speed, cooling tower minimum flow rate, chiller minimum condenser and evaporator flow rates, chiller minimum condenser and evaporator differential pressure, and chiller minimum lift.
Trade-offs:
When executing a Chiller Optimization project, every set point or operating parameter that you tune can have positive and/or negative effects for other parameters. When designing and executing an optimization project, we are always trying to find the balance between these trade-offs. We are looking to identify the optimal point(s) where the efficiency of two or more pieces of equipment in the plant results in the lowest plant kW/ton. These set points or algorithms can be solved for a given state of equipment stage, thermal load, and outside ambient conditions while avoiding dangerous or unstable operating conditions by maintaining the limits, including condenser water temperature reset, chilled water temperature reset, condenser flow reset, chilled water flow reset, and chiller load balancing.
Equipment staging:
Equipment staging - set points and sequences that enable or disable equipment from operation - is based entirely off of the limits and trade offs of the system. These set points and sequences depend on the system state, including flow, load, and ambient conditions. The aim of the staging is to achieve the lowest kW/ton while avoiding excessive cycling, which can lead to instability, short cycling and low runtime per cycle, and reducing equipment life. Staging includes chiller sequencing, chiller stage up and down demand set points, cooling tower staging strategy, and manifold pumping staging strategy.
What is Central Plant optimization?
Central Plant Optimization is 1) a process of: establishing physical and/or operation equipment limits; 2) using design/operation data to evaluate equipment efficiency profiles to determine optimal set points and/or algorithms for energy trade-offs within the plant; and 3) using operational data to evaluate load profiles to determine optimal equipment staging (particularly focused on chillers) to ensure efficient, stable and safe operation.
Example of optimal operating point between two equipment power curves, demonstrating ideal application of trade-offs to achieve total system efficiency
Key Takeaways:
Free cooling is a great way to improve the efficiency of a chiller plant.
The coefficient of performance (COP) is a measure of chiller efficiency.
Chiller optimization is a complex problem that can be solved with the help of data.
Data is essential for tracking the performance of a chiller plant and identifying areas where improvements can be made.
Nerdy Knowledge Nuggets Playlist:
Subscribe to this playlist for more short clips of our upcoming interviews.
We hope this thought-provoking video will be a valuable resource for anyone seeking a comprehensive understanding of chillers and chiller plants. It offers a wealth of knowledge and insights into this crucial aspect of modern systems, empowering viewers to make informed decisions and optimize the performance of their own chiller plants.
Looking ahead to 2025, ACE IoT will use our new channel to record deep-dive technical conversations on topics of interest to Smart Buildings practitioners. ACE IoT’s goal is to establish a repository of video content that practitioners can draw upon as they work to optimize the operations of buildings. There is no need for all of us to pay the same learning tax!
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