Search

• Equation-based object-oriented Modelica models for data center cooling systems are built and released in the open-source Modelica Buildings library. • Together with the Electrical package in the Modelica Buildings library, the introduced package can simulate the thermal dynamics as well as the electrical dynamics for conventional and renewable data centers. • New strategies toward emergency operations for the data center cooled by chillers and waterside economizers are investigated. In this paper, we introduce a newly developed open source data center package in the Modelica Buildings library to support modeling and simulation of cooling and control systems of data centers. The data center package contains major thermal and control component models, such as Computer Room Air Handler, Computer Room Air Conditioner, models of different subsystem configurations such as chillers with differently configured waterside economizers, as well as templates for different systems. Two case studies based on this package are performed to investigate the performances of the cooling and electrical system under normal conditions and emergency situations such as a blackout: one is for a data center powered by conventional energy, and the other is for a data center powered by renewable energy. Simulation results show that the dynamic modeling and multi-domain simulation in the Modelica-based tool make it convenient for users to investigate both normal and emergent operations for conventional and renewable data centers. [ABSTRACT FROM AUTHOR]

Fast fluid dynamics (FFD) can potentially be used for real-time indoor air-flow simulations. This study developed two-dimensional fast fluid dynamics (2-D FFD) into three-dimensional fast fluid dynamics (3-D FFD). The implementation of boundary conditions at the outlet was improved with a local mass conservation method. A near-wall treatment for the semi-Lagrangian scheme was also proposed. This study validated the 3-D FFD with five flows that have features of indoor air flow. The results show that the 3-D FFD can successfully capture the three dimensionality of air-flow and provide reliable and reasonably accurate simulations for indoor air flows with a speed of about 15 times faster than current computational fluid dynamics (CFD) tools. [ABSTRACT FROM PUBLISHER]

Abstract: Fast indoor airflow simulations are necessary for building emergency management, preliminary design of sustainable buildings, and real-time indoor environment control. The simulation should also be informative since the airflow motion, temperature distribution, and contaminant concentration are important. Unfortunately, none of the current indoor airflow simulation techniques can satisfy both requirements at the same time. Our previous study proposed a Fast Fluid Dynamics (FFD) model for indoor flow simulation. The FFD is an intermediate method between the Computational Fluid Dynamics (CFD) and multizone/zonal models. It can efficiently solve Navier–Stokes equations and other transportation equations for energy and species at a speed of 50 times faster than the CFD. However, this speed is still not fast enough to do real-time simulation for a whole building. This paper reports our efforts on further accelerating FFD simulation by running it in parallel on a Graphics Processing Unit (GPU). This study validated the FFD on the GPU by simulating the flow in a lid-driven cavity, channel flow, forced convective flow, and natural convective flow. The results show that the FFD on the GPU can produce reasonable results for those indoor flows. In addition, the FFD on the GPU is 10–30 times faster than that on a Central Processing Unit (CPU). As a whole, the FFD on a GPU can be 500–1500 times faster than the CFD on a CPU. By applying the FFD to the GPU, it is possible to do real-time informative airflow simulation for a small building. [Copyright &y& Elsevier]

Highlights • Hardware-in-the-loop (HIL) simulation is increasingly used for building controls. • HIL simulation combines the advantages of pure simulation and field tests. • The agent-based framework for HIL simulation has several distinctive advantages. • An example was used to illustrate the use of the HIL simulation framework. Abstract In general, a hardware-in-the-loop (HIL) building simulation has lower cost and fewer practical limitations (e.g., scheduling issues) than field tests in occupied buildings, while also overcoming limitations of simulations alone by capturing the full behavior of some physical systems, equipment, and components. However, the implementation of an HIL can be difficult due to the scarcity of appropriate tools. This paper presents an agent-based framework for HIL simulation. It can be used for investigation of controller performance via controller-in-the-loop simulations and also HIL for system synthesis. In the latter case, both controllers and major equipment participate in tests to ensure that dynamics of equipment operation are correctly captured in addition to controller performance. The HIL simulation framework presented allows such actual physical parts to be included in the framework while representing others for which behaviors are better known and modeled in simulation models. The mechanism implemented in the framework to synchronize simulations in software with real-time operation of physical equipment is described. As an example, use of the HIL simulation framework is illustrated through a brief study of speed control of the supply fan in the air handling unit of a variable-air-volume building heating, ventilating and air-conditioning system. [ABSTRACT FROM AUTHOR]

In U.S. district heating (DH) systems, steam is the most common heat transport medium. Industry demand for new advanced modeling capabilities of complete steam DH systems is increasing; however, the existing models for water/steam thermodynamics are too slow for large system simulations because of computationally expensive algebraic loops that require the solution to nonlinear systems of equations. For practical applications, this work presents a novel split-medium approach that implements numerically efficient liquid water models alongside various water/steam models, breaking costly algebraic loops by decoupling mass and energy balance equations. New component models for steam DH systems are also presented. We implemented the models in the equation based Modelica language and evaluated accuracy and computing speed across multiple scales: from fundamental thermodynamic properties to complete districts featuring 10 to 200 buildings. Compared to district models with the IF97 water/steam model and equipment models from the Modelica Standard Library, the new implementation improves the scaling rate for large districts from cubic to quadratic with negligible compromise to accuracy. For an annual simulation with 180 buildings, this translates to a computing time reduction from 33 to 1–1.5 h. These results are critically important for industry practitioners to simulate steam DH systems at large scales. • A first study to simulate a steam plant, network, and buildings in closed fluid loops. • Makes complete steam district heating system simulations practical for industry. • Evaluates accuracy and computing speed from thermodynamic property to district scales. • Maintains accuracy while reducing the computing scaling rate from cubic to quadratic. • Time savings from 33 to 1.3 h possible for annual simulations with 180 buildings. [ABSTRACT FROM AUTHOR]