Hardware-in-the-Loop-Simulation of a Building Energy and Control System to Investigate Circulating Pump Control Using Modelica

Schneider, Georg Ferdinand; Oppermann, Jens; Constantin, Ana; Streblow, Rita; Müller, Dirk

doi:10.3384/ecp15118225

Cited by 10 publications

(7 citation statements)

References 9 publications

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“…In addition to TRNSYS, Dymola Modelica and MATLAB Simulink are the other two programs frequently used for simulation in HIL for system synthesis. Schneider et al (2015) presented an HIL test bench for pumps, where models are used for a family dwelling and its HVAC system while the hardware includes a pump and the necessary "quasi-real" hardware to create the desired pump inlet conditions (i.e., temperature and pressure). They implemented a socket-based data interface using the TCP/IP protocol for the communication between Dymola and LabVIEW.…”

Section: Hil Simulation For System Synthesismentioning

confidence: 99%

An agent-based hardware-in-the-loop simulation framework for building controls

Huang

Wang

Brambley

et al. 2018

Energy and Buildings

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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.

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Section: Hil Simulation For System Synthesismentioning

confidence: 99%

An agent-based hardware-in-the-loop simulation framework for building controls

Huang

Wang

Brambley

et al. 2018

Energy and Buildings

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“…Furthermore in the planned field test one communication possibility between agents and devices is via TCP/IP, which means that only few modifications have to be carried out for moving the testing from simulation to a Details on a first version of the routines for the TCP/IP communication can be found in (Schneider et al, 2015). As set up parameters the routines only need an IP-address and a port.…”

Section: Tcp/ip Communicationmentioning

confidence: 99%

Dymola-JADE Co-Simulation for Agent-Based Control in Office Spaces

Constantin

Löwen

Ponci

et al. 2017

Linköping Electronic Conference Proceedings

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This paper presents an application of coupling Modelica under Dymola and JADE to test novel agent-based control for office spaces. The office space with a coupled energy system and weather boundary conditions are modeled in Dymola. The agent platform is programmed in JADE, where the agents communicate with each other to control the technical equipment used to deliver thermal energy to the room. Heating experiments, run for a one room scenario, using a radiator, show better system reaction to the comfort desires of the user compared to a control with a thermostatic valve, while having similar energy consumption. While the agents run in real time, the simulation in Dymola runs faster. We focus on the particularities of the connection for co-simulation to insure smooth transferability of the experiments from simulation to a field test, where the energy system as well as the agent platform would be running in real time.

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“…From this perspective, some works based on the dynamic simulation of the Heating and Ventilation Air Conditioning (HVAC)-building system have been proposed in the literature [6,12]. However, the results obtained through a simulation approach would always be followed by some experimental tests in order to validate assumptions, subsystems models, dynamics timescales, and estimated operative performances [13][14][15]; otherwise, results can be affected by notable errors or correspond to impracticable control actions to be realized in a real system [1].…”

Section: Introductionmentioning

confidence: 99%

“…In other fields, such as automotive and aerospace industries, HiL tests are standard practice and currently their importance is even increasing, due to the onset of advanced driver assistance and automated driving [16]. In the case of building energy systems, with the HiL approach, the experimental campaign is performed in a laboratory environment through an apparatus made of real thermal generators, heat storages and/or any other pieces of equipment, while the real building is replaced by a thermal load emulator controlled by a full energy dynamic simulation [15,[17][18][19]. Other technical units may also be substituted by appropriate emulators, to be integrated with the energy system.…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis of an Air Heat Pump for Heating Service Using a “Hardware-In-The-Loop” System

et al. 2020

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Estimating and optimizing the dynamic performance of a heat pump system coupled to a building is a paramount yet complex task, especially under intermittent conditions. This paper presents the “hardware-in-the-loop” experimental campaign of an air-source heat pump serving a typical dwelling in Pisa (Italy). The experimental apparatus uses real pieces of equipment, together with a thermal load emulator controlled by a full energy dynamic simulation of the considered building. Real weather data are continuously collected and used to run the simulation. The experimental campaign was performed from November 2019 to February 2020, measuring the system performances under real climate and load dynamics. With a water set point equal to 40 °C, the average heat pump coefficient of performance was about 3, while the overall building-plant performance was around 2. The deviation between the two performance indexes can be ascribed to the continuous on-off signals given by the zone thermostat due to the oversized capacity of the heat emission system. The overall performance raised to 2.5 thanks to a smoother operation obtained with reduced supply temperature (35 °C) and fan coil speed. The paper demonstrates the relevance of a dynamic analysis of the building-HVAC system and the potential of the “hardware-in-the-loop” approach in assessing actual part-load heat pump performances with respect to the standard stationary methodology.

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Hardware-in-the-Loop-Simulation of a Building Energy and Control System to Investigate Circulating Pump Control Using Modelica

Cited by 10 publications

References 9 publications

An agent-based hardware-in-the-loop simulation framework for building controls

An agent-based hardware-in-the-loop simulation framework for building controls

Dymola-JADE Co-Simulation for Agent-Based Control in Office Spaces

Experimental Analysis of an Air Heat Pump for Heating Service Using a “Hardware-In-The-Loop” System

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