2019
DOI: 10.3384/ecp19157491
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DAE Solvers for Large-Scale Hybrid Models

Abstract: 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 releas… Show more

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Cited by 15 publications
(9 citation statements)
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“…This minimizes the number of states events that can arise during simulation. State events require reinitialization of the differential-and-algebraic equation model, and thus, degrade simulation performance [32]. Therefore, noEvent helps avoiding such events, improving simulation performance.…”
Section: Modelica Implementationmentioning
confidence: 99%
See 1 more Smart Citation
“…This minimizes the number of states events that can arise during simulation. State events require reinitialization of the differential-and-algebraic equation model, and thus, degrade simulation performance [32]. Therefore, noEvent helps avoiding such events, improving simulation performance.…”
Section: Modelica Implementationmentioning
confidence: 99%
“…The power system model, shown in Fig. 5, was implemented using Modelica language and the OpenIPSL [33,34] in Dymola [32,35] in order to study the performance of the proposed automatic re-synchronization controller. The controller architecture was placed inside the DER generator model (G22) at the distribution network, as shown in Fig.…”
Section: Power System Modeling and Simulation Set-up Implementationmentioning
confidence: 99%
“…In the latter case, the loops of the original model are considered as blocks inside the optimization loop, and are solved in full each outer iteration. Compare DAE mode versus ODE mode for dynamic simulation (Braun, Casella and Bachmann, 2017;Henningsson, Olsson and Vanfretti, 2019). To keep the system of equations as small as possible we here choose the latter alternative.…”
Section: Causality Of the Data Assimilation Optimization Modelmentioning
confidence: 99%
“…At the same time, efforts have been made to ease a wide adoption by both development of automatic conversion methods for creation of standard test cases (Razik, Dinkelbach, et al 2018;Gómez et al 2019) and computation time improvements (Francesco Casella, Leva, and Andrea Bartolini 2017;Braun, Francesco Casella, and Bachmann 2017;Henningsson, Olsson, and Vanfretti 2019), for example through the use of DAE-mode integration. However, fundamental performance barriers remain on these two fronts, hampering the full operational use of generalpurpose Modelica tools to handle simulations involving national-or continental-scale grids; this motivated for instance the development of a mixed C++/Modelica approach by RTE (Guironnet et al 2018).…”
Section: Introductionmentioning
confidence: 99%