Modelica-Based Modeling and Simulation of District Cooling Systems: A Case Study

Hinkelman, Kathryn; Wang, Jing; Gautier, Antoine; Wetter, Michael; Fan, Chenjie; Long, Nicholas J.

doi:10.31224/osf.io/vpafs

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…Cucca & Ianakiev (2020) coupled a model of a district heating system built using Dymola-Modelica with the EnergyPlus model of the buildings, allowing for the development and evaluation of different control strategies. Hinkelman et al (2022) present a systematic methodology for Modelica modelling and simulation of district cooling systems.…”

Section: Introductionmentioning

confidence: 99%

Integrating low energy cooling and ventilation strategies in Indian residences

Cook

Shukla

Rawal

et al. 2022

Buildings and Cities

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Rapidly developing economies of countries in hot climates face the risk of a significant increase in CO 2 emissions. This study developed strategies for low energy cooling and ventilation for Indian residences (LECaVIR). Ventilation and cooling techniques were developed and tested for India's four climatic zones. The analysis shows that natural ventilation is possible in typical residential buildings for about 20-40% of the year. Using an enhanced natural ventilation mode with appropriately sized openable windows and controls, the total number of hours for which natural ventilation is able to offer satisfactory conditions for occupants can be extended by a further 13 percentage points, leading to a potential reduction of 46% in the mechanical cooling hours for residences. Dynamic thermal simulation models, coupled with control software, were used to test the most promising natural ventilation strategies as part of a mixed-mode approach to ensure year-round comfort at minimal energy cost. The simulation shows that energy savings of up to 55% are possible. PRACTICE RELEVANCEThis paper demonstrates that it is possible to design and control cooling and ventilation strategies that make significant use of natural ventilation, despite hot climates. The paper contains details of innovative control algorithms that were tested using real designs for Indian residences where poor ventilation and overheating are common problems, often leading to the excessive use of inefficient, portable air-conditioning systems. Practitioners will also benefit from guidance on how to use dynamic thermal simulation coupled with control software to quantify the energy and thermal comfort performance of mixedmode ventilation and cooling strategies.

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Section: Introductionmentioning

confidence: 99%

Integrating low energy cooling and ventilation strategies in Indian residences

Cook

Shukla

Rawal

et al. 2022

Buildings and Cities

View full text Add to dashboard Cite

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Benchmarking high performance HVAC Rule-Based controls with advanced intelligent Controllers: A case study in a Multi-Zone system in Modelica

O’Neill

2023

Energy and Buildings

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Research on Model Calibration Method of Chiller Plants Based on Error Reverse Correction with Limited Data

2023

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Model-based optimization is an important means by which to analyze the energy-saving potential of chiller plants. To obtain reliable energy-saving results, model calibration is essential, which strongly depends on operating data. However, sufficient data cannot always be satisfied in reality. To improve the prediction accuracy of the model with limited data, a model calibration method based on error reverse correction was investigated. A traditional optimization-based calibration method was first used for preliminary model calibration to obtain simulation data and simulation errors. Then, the sources of the simulation errors were analyzed to determine the distribution characteristics of the corresponding operating conditions of the model. Finally, the performance of the model was reversely corrected by adding a correction term to the original model. The proposed calibration method was tested on a chiller plant in Xiamen, China. The results showed that the proposed calibration method improved prediction accuracy by 2.61% (the coefficient of variation of the root mean square error (CV (RMSE)) was reduced from 3.96% to 1.35%) compared to the traditional method. The maximum mean bias error (MBE) for monthly chiller energy consumption was 2.66% with the proposed calibration method, while it was 10.42% with the traditional method. Overall, in scenarios with limited data, the proposed calibration method can effectively improve the accuracy of simulation results.

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Modelica-Based Modeling and Simulation of District Cooling Systems: A Case Study

Cited by 3 publications

References 36 publications

Integrating low energy cooling and ventilation strategies in Indian residences

Integrating low energy cooling and ventilation strategies in Indian residences

Benchmarking high performance HVAC Rule-Based controls with advanced intelligent Controllers: A case study in a Multi-Zone system in Modelica

Research on Model Calibration Method of Chiller Plants Based on Error Reverse Correction with Limited Data

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