Indoor ice rinks and ski resorts consume substantial cooling energy to maintain low-temperature environments, making energy efficiency a critical concern. Their unique floor structures, comprising an ice or snow layer and embedded cooling/heating coils, pose significant challenges for thermal modeling. This study proposes a state-space floor thermal model integrated with the building energy simulation tool, DeST, to simulate the dynamic thermal processes and annual hourly thermal loads of such arenas. The integrated model can efficiently handle the coupled heat and mass transfer between the floor frozen layer and the indoor air, and accurately calculate and distinguish the thermal loads borne by floor cooling coils, floor heating coils, and air coolers, respectively. The model is validated with theoretical and experimental data across three tiers (frozen layer, floor, and room levels), and the root-mean-square error of frozen surface temperatures remains within 0.3 ℃. A simplified indoor ice rink case study demonstrates the integrated model’s capability: hourly simulation results of temperatures and thermal loads exhibit reasonable seasonal and diurnal variations, aiding in analyzing floor insulation thickness and determining when floor heating coils are required. This work can provide a fundamental simulation analysis tool for the energy-efficient design and operation of indoor ice rinks and ski resorts.

The emergence of building condenser water systems with all-variable speed pumps and tower fans allows for increased efficiency and flexibility of chiller plants in partial load operation but also increases the control complexity of condenser water systems. This study aims to develop an integrated modeling technique for evaluating and optimizing the energy performance of such a condenser water system. The proposed system model is based on the semi-physical semi-empirical chiller, pump, and cooling tower models, with capabilities of fully considering the hydraulic and thermal interactions in the condenser water loop, being solved analytically and much faster than iterative solvers and supporting the explicit optimization of the pump and tower fan frequency. A mathematical approach, based on the system model and constrained optimization technique, is subsequently established to evaluate the energy performance of a typical dual setpoint-based variable speed strategy and find its energy-saving potential and most efficient operation by jointly optimizing pumps and tower fans. An all-variable speed chiller plant from Wuhan, China, is used for a case study to validate the system model’s accuracy and explore its applicability. The results showed that the system model can accurately simulate the condenser water system’s performance under various operating conditions. By optimizing the frequencies of pumps and tower fans, the total system energy consumption can be reduced by 12%–13% compared to the fixed dual setpoint-based strategy with range and approach setpoints of 4 ℃ and 2 ℃. In contrast, the energy-saving potential of optimizing the cooling tower sequencing is insignificant. A simple joint speed control method for optimizing the pumps and tower fans emerged, i.e., the optimal pump and fan frequency are linearly correlated (if both are non-extremes) and depend on the chiller part load ratio only, irrespective of the ambient wet-bulb temperature and chilled water supply temperature. It was also found that the oversizing issue has further limited the energy-saving space of the studied system and results in the range and approach setpoints being inaccessible. The study’s findings can serve as references to the operation optimization of all-variable speed condenser water systems in the future.

Chiller model is a key factor to building energy simulation and chiller performance prediction. With spread of new types of electric water chillers that have higher performance and wider operating range, new challenges have been faced by building energy simulation tools and their chiller models. This work takes a new type of electric water chiller as a case study and reevaluates eight typical empirically based models for predicting the energy performance of electric water chiller to verify whether they are suitable for the new type of chiller, using both laboratory test data from chiller manufacturer and online monitoring data from on-site operation of a central cooling plant with chillers of the same type. The prediction ability of the chiller models (including model prediction accuracy and generation ability) in laboratory test and on-site operation situations are examined. The results show that the existing models can well describe the chiller performance in the laboratory test situation but perform poorly in the on-site operation situation. As the best two models in the laboratory dataset, the overall prediction errors of DOE-2 and GN model increase more than 250% and 75% respectively in the field dataset. The big discrepancy of model prediction accuracy in the two situations is mainly due to the differences of evaporator and condenser water flow rates between the laboratory and on-site operation datasets, which indicates the limitations of the empirical chiller models and implies further research in future in order to improve the suitability and reliability of chiller model.