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Cooling Tower Optimization

Cooling Tower Optimization

Cooling towers that use fans to create drafts can use substantial amounts of power, creating higher operating costs or decreased operating efficiency. Towers that have multi-cell systems operate on the assumption that all cells in the system operate identically, which compounds these costs and inefficiencies. Griffin’s Cooling Tower Optimization application leverages the unique characteristics of each cell to optimally control individual fan speeds in real-time, mitigating costs by reducing power consumption by 5% or more, without sacrificing the performance of the system.

Cooling Tower Optimization using the Griffin AI Toolkit

Cooling towers are an integral piece of equipment for many processes, from power generation to food processing. Such systems that utilize fans to create a draft (both forced and induced) can use a substantial amount of power, representing higher operating costs or decreasing operating efficiency.

An opportunity exists to reduce the power consumption of the fans within the cooling tower when the fan speed is adjustable due to motors being equipped with variable frequency drives (VFDs) or having multiple power output settings. Many systems having this capability operate on the assumption that
all cells in the system have identical operating efficiency and run all fans within the system at identical speeds to achieve a given temperature setpoint. Often this is not the case, and individual cell efficiency varies greatly from fan to fan and can also change based on load and other conditions.

Griffin Open Systems’ Cooling Tower Optimization application can significantly reduce power consumption while achieving similar or even improved process performance. A power consumption reduction capability of 5–10% has been demonstrated on a 12-cell-induced draft evaporative cooler at a large electric power plant, shown below. Installation of Griffin Open Systems’ AI platform and cooling tower optimization application is quick and simple, requiring less than one week after internal control system changes are in place. Necessary I/O points are minimal, needing less than 50 I/O points depending on system size and scope. After a short AI learning and exploratory period (typically 2 – 3 weeks), the benefits of the optimization system can be expected to be seen within one month of installation.

We at Griffin Open Systems look forward to aiding you in achieving optimal performance of your
cooling towers as well as all systems within your process. Contact us to get started!

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