2020
DOI: 10.1016/j.jobe.2020.101263
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Optimal consumption modeling of multi–chiller system using a robust optimization algorithm with considering the measurement, control and threshold uncertainties

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Cited by 17 publications
(7 citation statements)
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“…COP is the common performance factor for chillers. Similar to the COP of heat pumps, the COP of chillers also can be modeled as a constant [136], a linear function of system states [137,138], a function of the part load ratio [139], a bi-quadratic function [80], polynomials [80] or an exponential function [79].…”
Section: Chillermentioning
confidence: 99%
“…COP is the common performance factor for chillers. Similar to the COP of heat pumps, the COP of chillers also can be modeled as a constant [136], a linear function of system states [137,138], a function of the part load ratio [139], a bi-quadratic function [80], polynomials [80] or an exponential function [79].…”
Section: Chillermentioning
confidence: 99%
“…The regular chillers operate in the set durations, and the auxiliary chillers are switched on when the cooling load is increased to provide enough cooling for buildings [ 31 ]. In optimal COP control, the cooling load is adjusted by changing the supply temperature of chilled water and the return temperature of cooling water, under the calculation of maximum COP which is based on the COP-PLR curve of chillers [ 32 ]. The optimal control of DCS in airport terminals can be achieved through the adjustments of water temperature settings when the COP of chillers reaches to the maximum value.…”
Section: Operation Control Strategies For Hub Airport Terminalsmentioning
confidence: 99%
“…Satisfying the cooling demand is an equality constraint. In practice, the Lagrange multiplier method [62,63,94] or the penalty function method [15,69,71] deals with the equality constraints. The equality constraint can also be expressed as inequality constraints with small deviation since it is difficult to obtain solutions that satisfy equality exactly.…”
Section: Satisfying the Cooling Demandmentioning
confidence: 99%
“…This difference occurred because the optimum solution was obtained from the worst-case, in which the cooling demand was 10.0% higher than the deterministic case. This method has also been successfully used for optimal chiller loading with multiple uncertainties, including measurement, control, and threshold uncertainties [63]. However, the ROC problem is difficult to solve directly, and the results are very conservative, indicating low energy efficiency.…”
Section: Robust Optimal Control (Roc)mentioning
confidence: 99%