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🔗 Source: aceee.org
📊 Size: 398 KB
📄 Pages: 13 pages
⬇️ Downloads: 99

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A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant with thermal storage, aiming to optimize energy consumption by taking advantage of weather forecasts and lower ambient wet bulb temperatures. The plant includes three water-cooled chillers and a two million gallon chilled water storage tank. A detailed model of the chilled water plant and simplified models of the campus buildings were developed using Modelica, and a semi-empirical model was used to predict the temperature and flow rate of the chilled water returning to the plant. The MPC algorithm determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The goal is to save more energy than possible with simple scheduling control by optimizing the charging window and system loop temperature set-points for each night.

Description

A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant with thermal storage, aiming to optimize energy...

Technical Information

  • File Format: PDF
  • File Size: 398 KB
  • Pages: 13
  • Language: EN
  • Total Downloads: 99
  • Last Updated: 11 hours ago

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