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Title:Optimal Allocation of Building Cooling Loads to Chilled Water Plant Equipment
Author(s):Olson, Rick Thomas
Doctoral Committee Chair(s):Liebman, Judith S.,
Department / Program:Mechanical Engineering
Discipline:Mechanical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Industrial
Engineering, Mechanical
Operations Research
Abstract:The air in most non-residential buildings needs to be cooled to maintain occupant comfort. Typically, the air is cooled by using cold water provided by a chiller plant consisting of liquid chillers, cooling towers and pumps. To meet the changing demand for cooling, most buildings have automated systems that control the operation of the chilled water plant. The system that controls the chilling equipment selects the temperatures of the water streams and the speed of the cooling tower fans to meet the building loads. In a system with several chillers or towers, the system also decides which combinations of chiller plant equipment should be used to meet the cooling loads.
This thesis presents Dynamic Chiller Sequencing (DCS); a new algorithm for controlling the selection and operation of chillers and cooling towers. The algorithm balances the trade-off between reducing the cost of electricity used and the amount charged for peak consumption during a billing period. This is accomplished by forecasting the cooling loads expected through a planning horizon, using non-linear programming to estimate the cost of meeting the individual loads with various combinations of equipment, and using network optimization techniques to determine the sequence of equipment selection that will minimize the cost of statisfying the expected loads for the entire planning horizon.
Validation of the DCS procedure took place in two stages. First, the sensitivity of the procedure to various internal and external factors was considered under the assumption that perfect load forecasts were available. This was followed by a study that explored the algorithm's sensitivity forecasting errors. These two studies confirmed that DCS is an improvement over conventional chiller sequencing strategies and that the DCS algorithm is stable over a wide range of operating conditions.
Issue Date:1988
Description:167 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1988.
Other Identifier(s):(UMI)AAI8815400
Date Available in IDEALS:2014-12-15
Date Deposited:1988

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