ScholarWorks@경상국립대학교

초록

As societal demands for carbon neutrality continue to rise, reducing energy consumption in the building sector has become essential. Among various building types, data centers consume a significant amount of energy, prompting numerous studies to explore the application of Water-side Economizer (WSE) systems that enable Free Cooling operation for enhanced energy efficiency. This study aims to optimize the performance of WSE systems by proposing a control strategy that minimizes cooling energy consumption in response to varying outdoor conditions. As a preliminary step, a cooling energy prediction model for a data center was developed to derive optimal fluid temperature setpoints that minimize energy usage according to outdoor wet-bulb temperature. The predictive model was constructed using Long Short-Term Memory (LSTM) and Light Gradient Boosting Machine (LightGBM), and demonstrated high accuracy and reliability with R-squared value of 0.995, CV (RMSE) of 4.31%, and an MAE of approximately 1.13 kW. Based on this model, optimal fluid temperature combinations were determined for each outdoor wet-bulb condition throughout the year. These results are expected to serve as a foundational guideline for developing future control algorithms and establishing energy-efficient operation strategies.

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