A novel data-driven optimal chiller loading regulator based on backward modeling approach

Lian, Kuang‐Yow; Hong, Yong-Jie; Chang, Che‐Wei; Su, Yushan

doi:10.1016/j.apenergy.2022.120102

Cited by 9 publications

(1 citation statement)

References 26 publications

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“…Olszewski [10] ascertained the superior performance of variable speed chillers to handle part-load conditions compared with common on/off controlled chillers. Some recent studies in references [11][12][13][14][15][16][17][18] focus on the optimum loading of multiple chillers with various optimization algorithms. The chiller coefficient of performance (COP)-cooling capacity output in kW over chiller electric power input in kW-was expressed as a function of part-load ratio (PLR), only without considering the temperatures of chilled water and condenser water.…”

Section: Reference Research Problem Variables Optimized Optimization ...mentioning

confidence: 99%

Time Series Forecast of Cooling Demand for Sustainable Chiller System in an Office Building in a Subtropical Climate

2023

Sustainability

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Commercial buildings can take up one-third of the energy related carbon emissions. There is limited research on forecasting cooling demands to evaluate sustainable air conditioning systems under climate change. This paper develops a simplified cooling demand model based on the time series of climatic and architectural variables to analyze carbon reduction by a sustainable chiller system. EnergyPlus is used to simulate hourly cooling demands of a hypothesized high-rise office building in Hong Kong under a change of architectural parameters and future climate conditions. An hourly cooling demand model with R2 above 0.9 is developed with inputs of the window-to-wall ratio, outdoor air enthalpy, global solar radiation, wind speed and their two steps ahead. The validated model is then used to analyze carbon reduction potentials by free cooling and a full variable speed chiller system. The low carbon technologies reduce carbon emissions by over 20% with but the reduction shrinks to 2.51–4.93% under future climate conditions. The novelty of this study is the simplified cooling demand model based on the time series of climatic and architectural variables. The significances of this study are to quantify carbon reduction by a sustainable chiller system under climate change and to appeal for more carbon reduction technologies for carbon neutrality.

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Section: Reference Research Problem Variables Optimized Optimization ...mentioning

confidence: 99%

Time Series Forecast of Cooling Demand for Sustainable Chiller System in an Office Building in a Subtropical Climate

2023

Sustainability

View full text Add to dashboard Cite

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Parallel-Chiller Optimization Using Continuous Barnacles Mating Optimizer Considering Chiller Availability and Cooling Load Variations

Thou,

Wong,

Chong

et al. 2024

Process Integr Optim Sustain

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Improving the out-of-sample generalization ability of data-driven chiller performance models using physics-guided neural network

Guo,

Li,

Yue

et al. 2024

Applied Energy

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A novel data-driven optimal chiller loading regulator based on backward modeling approach

Cited by 9 publications

References 26 publications

Time Series Forecast of Cooling Demand for Sustainable Chiller System in an Office Building in a Subtropical Climate

Time Series Forecast of Cooling Demand for Sustainable Chiller System in an Office Building in a Subtropical Climate

Parallel-Chiller Optimization Using Continuous Barnacles Mating Optimizer Considering Chiller Availability and Cooling Load Variations

Improving the out-of-sample generalization ability of data-driven chiller performance models using physics-guided neural network

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