BESMod - A Modelica Library providing Building Energy System Modules

Wüllhorst, Fabian; Maier, Laura; Jansen, David G.; Kühn, Larissa; Hering, Dominik; Müller, Dirk

doi:10.3384/ecp211869

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…Here, the BuildingControlLib is presented, which allows the modeling and simulation of standardized control functions. (Wüllhorst et al, 2022). Furthermore, Modelon Impact provides a web-based tool for modeling and virtual testing of industrial energy systems (Modelon, 2023).…”

Section: State Of Researchmentioning

confidence: 99%

ThermalSystemsControlLibrary: A Modelica Library for Developing Control Strategies of Industrial Energy Systems

Borst,

Frank,

Theisinger

et al. 2023

Linköping Electronic Conference Proceedings

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The transformation of energy-intensive industries towards greenhouse gas neutrality leads to increasing complexity of industrial energy supply systems. This affects particularly thermal energy systems due to waste heat utilization measures as well as the integration of renewable energy sources and further storage capacities. This complexity is also reflected in the control strategies of such systems, which makes the development of dynamic simulation models for testing them a research field of growing interest. The ThermalSystemsControlLibrary is a novel Modelica library, which aims at standardized modeling of industrial energy supply systems for control strategy development. Based on a generic data model, all components cover physical as well as control modeling and are particularly suitable for testing supervisory control strategies within external frameworks using the FMI standard. The library is validated for an exemplary use case of an industrial energy supply system comparing two different supervisory control strategies.

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Section: State Of Researchmentioning

confidence: 99%

ThermalSystemsControlLibrary: A Modelica Library for Developing Control Strategies of Industrial Energy Systems

Borst,

Frank,

Theisinger

et al. 2023

Linköping Electronic Conference Proceedings

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“…Following current guidelines [6], a typical building energy system consists of: A heat pump and heating rod (HR) connected in series; a space heating storage connected in parallel; a separate DHW storage with an internal heat exchanger connected in parallel; radiators to transfer heat to the rooms; analogue thermostatic valves which control the volume flow through each radiator to ensure thermal comfort; and rule-based controllers. We model this system using the open-source Modelica library BESMod [23]. In here, components, control, and building envelope are modelled in a dynamic, nonlinear fashion:…”

Section: System Modelmentioning

confidence: 99%

Heat Pump Systems with Photovoltaics: Influence of the Control Strategy on the Optimal Design

Wüllhorst

Reuter-Schniete

Maier

et al. 2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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Electrifying the heat supply of buildings is key to mitigate climate change. Inhere, photovoltaic and heat pump systems are promising technologies. Studies indicate that an increase in self-consumption is economically beneficial. Coupling photovoltaic with heat pump systems enables the aspired increase of self-consumption, especially in combination with thermal energy storages. The coupling of the systems is influenced by the control strategies, for which rule-based and model predictive-based approaches exist. Research finds that optimal control methods heavily depend on the system design and vice versa. Contrary to these interdependencies, current design guidelines neglect a possible influence of photovoltaics on the design of the heat pump system. To analyze a possible influence on the optimal heat pump system design, we apply nonlinear, dynamic simulation-based optimization to find the optimal design of the heat pump system for three different cases: no photovoltaic, no supervisory control, and a state-of-the-art supervisory control. The model consists of the whole building energy system, including the building envelope, radiators, a heat pump, a photovoltaic, and a grid connection. The dynamic simulation covers a whole year. To obtain generalizable results, we conduct optimizations for varying boundary conditions, including changes in weather and photovoltaic roof area. Consistent over all boundary conditions, results indicate that cost optimal heat pump system design does not change for current price assumptions. However, maximizing the thermal energy storage is vital to obtain maximal costs savings compared to the case with no photovoltaic system. Thus, for different price assumptions, the optimal design will change.

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“…We develop the BES in Modelica using the Dymola [9] environment. The individual models are generally based on the BESMod library [10]. The library draws on AixLib [11], BuildingSystems [12] and IBPSA (basic library of the previous archives) [13].…”

Section: Building Energy System Simulationmentioning

confidence: 99%

The Impact of Controller Settings in Heat Pumps: Numerical Findings and Experimental Verification

Göbel,

Kevin,

Christian

et al. 2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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In residential buildings, the efficiency of heat pump systems (HPS) significantly depends on the HPS design and operation. In particular, HPS controllers often use ambient temperature-dependent heating curves for operation. The resulting supply temperature serves as the reference variable for the internal controller, which is used to manipulate the compressor speed. Typically, the internal controller has constant parameters for the PI controller, hysteresis, and operational time. While buildings have a highly dynamic, time-variant demand, these dynamics are rarely considered in controller development. This work investigates internal control parameters' sensitivity to the overall HPS efficiency in annual, dynamic simulations and experiments. To consider different supply temperatures, two buildings with underfloor heating and radiators serve as case studies. Based on a validated simulation model, the one-factor-at-a-time sensitivity analysis method determines the controller's influence on the seasonal coefficient of performance (SCOP). Hardware-in-the-loop experiments are conducted for representative periods extracted from annual simulation results for experimental verification. The results for the building with underfloor heating and radiators prove that the control parameter influences the SCOP up to 18.5 % and 4.2 %, respectively. In particular, different control parameters for the optimal operation were determined for both case studies, challenging the constant settings used in the state-of-theart. In addition, we observe a significant increase of 300 % in the avoidable compressor starts in experiments due to poor parameter settings. To ensure maximum efficiency of HPS and significantly reduce the number of compressor starts in any residential building, we recommend integrating adaptive setting of control parameters into the HPS controller.

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BESMod - A Modelica Library providing Building Energy System Modules

Cited by 8 publications

References 12 publications

ThermalSystemsControlLibrary: A Modelica Library for Developing Control Strategies of Industrial Energy Systems

ThermalSystemsControlLibrary: A Modelica Library for Developing Control Strategies of Industrial Energy Systems

Heat Pump Systems with Photovoltaics: Influence of the Control Strategy on the Optimal Design

The Impact of Controller Settings in Heat Pumps: Numerical Findings and Experimental Verification

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