District energy systems: Modelling paradigms and general-purpose tools

Schweiger, Gerald; Heimrath, Richard; Falay, Basak; O’Donovan, Keith; Nageler, Peter Josef; Pertschy, Reinhard; Engel, Georg P.; Streicher, Wolfgang; Leusbrock, Ingo

doi:10.1016/j.energy.2018.08.193

Cited by 63 publications

(33 citation statements)

References 28 publications

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“…A similar comparison was conducted by Schweiger et al [11] for energy systems at district scale. They conclude that acausal modeling is well suited for representing the structure of physical systems and that acausal modeling is convenient for rapid prototyping.…”

mentioning

confidence: 70%

“…The utilization of tools based on causal and acausal modeling approaches is investigated using a keyword analysis on Scopus. The candidates were identified based on the knowledge of the authors and the relevant literature such as [5,4,11,13]. We have only considered those languages that have listed more than 50 publications with the respective keyword on Scopus since 2000.…”

Section: Utilization Of Causal and Acausal Languagesmentioning

confidence: 99%

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Modeling and simulation of large-scale systems: A systematic comparison of modeling paradigms

Schweiger

Nilsson

Schoeggl

et al. 2020

Applied Mathematics and Computation

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A trend across most areas where simulation-driven development is used is the ever increasing size and complexity of the systems under consideration, pushing established methods of modeling and simulation towards their limits. This paper complements existing surveys on large-scale modeling and simulation of physical systems by conducting expert surveys. We conducted a two-stage empirical survey in order to investigate research needs, current challenges as well as promising modeling and simulation paradigms. Furthermore, we applied the analytic hierarchy process method to prioritise the strengths and weakness of different modeling paradigms. The results of this study show that experts consider acausal modeling techniques to be suitable for modeling large scale systems, while causal techniques are considered less suitable.

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confidence: 70%

Section: Utilization Of Causal and Acausal Languagesmentioning

confidence: 99%

Modeling and simulation of large-scale systems: A systematic comparison of modeling paradigms

Schweiger

Nilsson

Schoeggl

et al. 2020

Applied Mathematics and Computation

Self Cite

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“…A large number of different software types is being used in these investigations. Finite difference methods (FDM) used by TRNSYS [18,26] and IDA-ICE [27][28][29][30] are widely adopted, due to their ability to account for variable ground surface temperatures [31,32]. In some recent approaches, these can even be combined with probabilistic analysis [33].…”

Section: Introductionmentioning

confidence: 99%

Energy Pile Field Simulation in Large Buildings: Validation of Surface Boundary Assumptions

2019

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As the energy efficiency demands for future buildings become increasingly stringent, preliminary assessments of energy consumption are mandatory. These are possible only through numerical simulations, whose reliability crucially depends on boundary conditions. We therefore investigate their role in numerical estimates for the usage of geothermal energy, performing annual simulations of transient heat transfer for a building employing a geothermal heat pump plant and energy piles. Starting from actual measurements, we solve the heat equations in 2D and 3D using COMSOL Multiphysics and IDA-ICE, discovering a negligible impact of the multiregional ground surface boundary conditions. Moreover, we verify that the thermal mass of the soil medium induces a small vertical temperature gradient on the piles surface. We also find a roughly constant temperature on each horizontal cross-section, with nearly identical average values when either integrated over the full plane or evaluated at one single point. Calculating the yearly heating need for an entire building, we then show that the chosen upper boundary condition affects the energy balance dramatically. Using directly the pipes’ outlet temperature induces a 54% overestimation of the heat flux, while the exact ground surface temperature above the piles reduces the error to 0.03%.

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“…The FMI (Blockwitz et al, 2012;FMI, 2014) is a standard that enables co-simulation by providing a common interface to couple black box simulators. We focus on FMI based co-simulation, because of its adoption in various fields in industry and academia (Brem-beck et al, 2011;Schweiger et al, 2018a;Bünte et al, 2014;Engel et al, 2018;Sanfilippo et al, 2018;Schweiger et al, 2018b) as well as increasing citations among scientific papers (see Figure 2).…”

Section: Introductionmentioning

confidence: 99%

Functional Mock-up Interface: An empirical survey identifies research challenges and current barriers

Schweiger¹,

Gomes²,

Engel³

et al. 2019

Linköping Electronic Conference Proceedings

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Co-simulation is a promising approach for the analysis of complex, multi-domain systems, that leverages mature simulation tools of the respective domains. It has been applied in many different disciplines in academia and industry, with limited sharing of findings. With the increasing adoption of the FMI standard, researchers have set to work on surveying the scattered knowledge on co-simulation in academia. This paper complements the existing surveys by taking on the social and empirical aspect, corroborating, and prioritizing, previous findings. We focus on understanding the perceived research challenges, and the current barriers, based on expert assessment. One of the main barriers pointed out is the limited support for discrete event and hybrid co-simulation.Co-simulation yields multiple advantages: Figure 1. Example master algorithm.

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District energy systems: Modelling paradigms and general-purpose tools

Cited by 63 publications

References 28 publications

Modeling and simulation of large-scale systems: A systematic comparison of modeling paradigms

Modeling and simulation of large-scale systems: A systematic comparison of modeling paradigms

Energy Pile Field Simulation in Large Buildings: Validation of Surface Boundary Assumptions

Functional Mock-up Interface: An empirical survey identifies research challenges and current barriers

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