iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations

Vanfretti, Luigi; Rabuzin, Tin; Baudette, Maxime; Murad, Mohammed Ahsan Adib

doi:10.1016/j.softx.2016.05.001

Cited by 58 publications

(31 citation statements)

References 2 publications

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“…Finally, we compare with the simulations performed by (Vanfretti et al, 2016) of equivalent models using the domain-specific simulation tool PSS/E. On a computer slightly faster than the one used for this paper the first two scenarios run in 5 s, respectively 4 s. We conclude that the Dymola DAE mode performance is competitive against the industry state of the art.…”

Section: Doimentioning

confidence: 91%

“…All simulations in this section were run in Dymola 2019 FD01, with default settings if nothing else is specified, and using Visual Studio 2015 for model compilation. An ordinary Windows 7 (64-bit) laptop computer (Intel Core i7-6820HQ, 16 GB RAM) has been used for all experiments, including the reproduction of the Rkfix2 experiments (h = 0.01 s), reported by (Vanfretti et al, 2016). As mentioned above, the Dassl tolerances have been tuned to give comparable numerical errors between the two solvers.…”

Section: Efficiency Experimentsmentioning

confidence: 99%

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DAE Solvers for Large-Scale Hybrid Models

Henningsson¹,

Olsson²,

Vanfretti

2019

Linköping Electronic Conference Proceedings

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We present a strategy for DAE mode simulations of large-scale Modelica models with state events. DAE solvers can be orders of magnitudes faster than traditional ODE solvers when simulating models with large algebraic loops. Such loops are common in, for example, power grid models. Central for our DAE mode approach is the accurate and efficient treatment of state events. Adapting, extending, and optimizing results known in the literature to the Modelica context resulted in a DAE mode implementation first released in Dymola 2019 and 3DEXPE-RIENCE 2019x. The implementation is verified by efficiency experiments featuring OpenIPSL power grid models. The run times for these models are competitive with domain-specific, state-of-the-art simulation tools.

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Section: Doimentioning

confidence: 91%

Section: Efficiency Experimentsmentioning

confidence: 99%

DAE Solvers for Large-Scale Hybrid Models

Henningsson¹,

Olsson²,

Vanfretti

2019

Linköping Electronic Conference Proceedings

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show abstract

“…A potential solution is provided by multi-domain modeling languages. For instance, there exist several libraries for the Modelica [6] language that target energy-related domains, such as power systems [7,8] or buildings [9], which in combination allow the modeling of hybrid thermal-electrical distribution systems (and thus satisfying KP1 and MR1). It has also been demonstrated how such models can be utilized for standard optimization approaches (satisfying KP2), see for instance [10].…”

Section: Simulation Of Coupled Heat and Power Networkmentioning

confidence: 99%

Combined Optimal Design and Control of Hybrid Thermal-Electrical Distribution Grids Using Co-Simulation

et al. 2020

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Innovations in today’s energy grids are mainly driven by the need to reduce carbon emissions and the necessary integration of decentralized renewable energy sources. In this context, a transition towards hybrid distribution systems, which effectively couple thermal and electrical networks, promises to exploit hitherto unused synergies for increasing efficiency and flexibility. However, this transition poses practical challenges, starting already in the design phase where established design optimization approaches struggle to capture the technical details of control and operation of such systems. This work addresses these obstacles by introducing a design approach that enables the analysis and optimization of hybrid thermal-electrical distribution systems with explicit consideration of control. Based on a set of key prerequisites and modeling requirements, co-simulation is identified as the most appropriate method to facilitate the detailed analysis of such systems. Furthermore, a methodology is presented that links the design process with the implementation of different operational strategies. The approach is then successfully applied to two real-world applications, proving its suitability for design optimization under realistic conditions. This provides a significant extension of established tools for the design optimization of multi-energy systems.

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“…Python scripts were used to automatically generate the Modelica records. The scripts consist of a modified version of the toolset used to get the Nordic 44-bus system simulation results published in (Vanfretti, Rabuzin, Baudette, & Murad, 2016) and (Vanfretti et al, 2017).…”

Section: Load Change Event Simulationsmentioning

confidence: 99%

Coalesced Gas Turbine and Power System Modeling and Simulation using Modelica

Aguilera

Vanfretti

Bogodorova

et al. 2019

Linköping Electronic Conference Proceedings

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This work reports how the multi-domain physical modeling and simulation Modelica language has been employed to create a benchmark power grid and gas turbine model within the ITEA3 OpenCPS project. The modeling approach is not only shown to be useful to test the functionalities of the OpenCPS toolchains, but it also could give rise to potential applications in power system domain studies where the widely-accepted turbinegovernor models are not rich enough to represent the multi-domain system dynamics.

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iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations

Cited by 58 publications

References 2 publications

DAE Solvers for Large-Scale Hybrid Models

DAE Solvers for Large-Scale Hybrid Models

Combined Optimal Design and Control of Hybrid Thermal-Electrical Distribution Grids Using Co-Simulation

Coalesced Gas Turbine and Power System Modeling and Simulation using Modelica

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