Abstract

Building cooling drives the peak electric demand in summer; therefore, it is an important component in energy related costs. While there have been efforts to optimize chiller(s) on individual buildings and/or district cooling systems, previous studies use simplified models for the involved components (e.g., cooling towers, pumps) that do not fully represent the actual performance of components or neglect some of the utilized components. This paper provides an open-source approach for electric demand minimization of existing district cooling systems developing data-driven performance models with as-operated data to realistically simulate district-scale heating, ventilating, and air-conditioning components. In addition, a flexible, non-linear model for the electric demand minimization of chiller plants in districts with a rigid or flexible thermal cooling demand is proposed in this study. The proposed methodologies for model development and optimization are brand-agnostic, and their capabilities are demonstrated using the Colorado School of Mines’ main chilled water plant. Our results show a daily peak electric demand reduction of up to 15.2% for the week with the highest electric demands on the Mines campus using a rigid thermal cooling demand constraint. A 5% flexibility on thermal cooling demand provides a peak electric demand reduction of up to 18.7%. The results of this study highlight the extent of benefits that could be achieved by optimizing the district-scale operation of chiller plants with and without thermal cooling demand flexibility. This demand flexibility could be achieved through flexible resources and/or district-scale demand side management as buildings have diverse primary applications.

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