Industrial application of optimization with Modelica and Optimica using intelligent Python scripting

Dietl, Karin; Yances, Stephanie Gallardo; Johnsson, Anna; Åkesson, Johan; Link, Kilian; Velut, Stéphane

doi:10.3384/ecp14096777

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…Modelica power-plant models have been presented by severalp ower-plant providersa nd operators,s uch as ABB, [68] EDF, [69] and Siemens. [70] In academia, Casella et al [71,72] used the object-oriented approacht os imulate organic Rankine cycle (ORC) and IGCC systems dynamically using the ThermalPower library developed by Casella and Leva. [73] Tr app et al [74] also developed dynamic models for IGCC systems with precombustion CO 2 capture.…”

Section: Combined Cycle Modelmentioning

confidence: 99%

Dynamic Simulation of Fixed‐Bed Chemical‐Looping Combustion Reactors Integrated in Combined Cycle Power Plants

2016

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Chemical‐looping combustion (CLC) is a promising and efficient method for power generation with in situ CO2 capture. In this work, we focus on high‐pressure fixed‐bed CLC reactors integrated with combined cycle (CC) power plants. Specifically, the dynamic nature of fixed‐bed chemical‐looping reactors and the many kinetically controlled reactions necessitate the use of dynamic modeling to evaluate power plant performance, efficiency, stability, and feasibility under transient operation. We present a dynamic model for an integrated CLC–CC power plant and transient analyses of the integrated plant performance. A network of dynamically operated fixed‐bed reactors fed with natural gas comprises the CLC plant component. A dynamic model is developed and tuned to match the performance of a commercial combined cycle power plant. The transient variations of the integrated plant in terms of power, temperature, and pressure profiles are presented. The simulation results show that despite the inherent batch‐type operation of the CLC reactor, the operation of the combined cycle is relatively unaffected, and there are small oscillations of approximately 2 % around the desired steady‐state conditions.

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Section: Combined Cycle Modelmentioning

confidence: 99%

Dynamic Simulation of Fixed‐Bed Chemical‐Looping Combustion Reactors Integrated in Combined Cycle Power Plants

2016

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“…Modelica environment is used as a GUI and develop and import an initial prototype of a reusable and extensible manufacturing process model component library into the Modelica environment. Modelica provides simulation capability for optimization; some researchers have reported the application of Optimica, a JModelica effort for dynamic optimization (Dietl, et al, 2014). Optimica extends Modelica with language constructs that enable formulation of dynamic optimization problems based on Modelica models.…”

Section: More On Related Workmentioning

confidence: 99%

Modeling and optimization of manufacturing process performance using Modelica graphical representation and process analytics formalism

2015

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This paper concerns the development of a design methodology and its demonstration through a prototype system for performance modeling and optimization of manufacturing processes. The design methodology uses a Modelica simulation tool serving as the graphical user interface for manufacturing domain users such as process engineers to formulate their problems. The Process Analytics Formalism, developed at the National Institute of Standards and Technology, serves as a bridge between the Modelica classes and a commercial optimization solver. The prototype system includes (1) manufacturing model components’ libraries created by using Modelica and the Process Analytics Formalism, and (2) a translator of the Modelica classes to Process Analytics Formalism, which are then compiled to mathematical programming models and solved using an optimization solver. This paper provides an experiment toward the goal of enabling manufacturing users to intuitively formulate process performance models, solve problems using optimization-based methods, and automatically get actionable recommendations.

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“…(Ruggaber and Brembeck, 2021;Gonzalez, et al, 2017;Andrén, et al, 2015) demonstrate how various variants of Kalman filters can be implemented for state and parameter estimation, also exploiting the directional derivatives defined by the FMI 2.0 standard. The combined usage of Modelica, FMI and the scripting environment has been proven to be successful for optimal start-up of power plants in offline mode (Dietl et al, 2014). For rapid testing and deployment of the state estimators without any need for scripting environment, the estimation algorithm can also be embedded according to the FMI standard as a Functional Mockup Unit (FMU), as shown in (Brembeck et al, 2011), (Bonvini et al, 2014), (Laughman and Bortoff, 2020).…”

Section: Introductionmentioning

confidence: 99%

[Industrial paper] Digital Twin Applications Using a Cloud Native Modelica Platform

Kumar¹,

Narasimhan²,

Rajendran³

et al. 2022

Linköping Electronic Conference Proceedings

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This paper showcases how Modelica technology can be leveraged for real-time applications using a cloud native simulation platform, Modelon Impact™. The platform allows for real-time, two-way communication of data, from the IoT connected plant to a physical model and, from the physical model to a dashboard for plant monitoring and control. The communication relies on open standards and REST-API, which makes it possible to implement digital twins for various applications, such as plant monitoring, predictive maintenance, fault isolation or controls. The paper describes a state estimation workflow where data is transmitted back and forth to the simulation platform via Message Queuing Telemetry Transport (MQTT) and where Node-Red is used for the end-user interface.

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Industrial application of optimization with Modelica and Optimica using intelligent Python scripting

Cited by 7 publications

References 4 publications

Dynamic Simulation of Fixed‐Bed Chemical‐Looping Combustion Reactors Integrated in Combined Cycle Power Plants

Dynamic Simulation of Fixed‐Bed Chemical‐Looping Combustion Reactors Integrated in Combined Cycle Power Plants

Modeling and optimization of manufacturing process performance using Modelica graphical representation and process analytics formalism

[Industrial paper] Digital Twin Applications Using a Cloud Native Modelica Platform

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