Speaker
Description
CANCELLED
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An accurate simulation of gas networks has been the objective of the last decades in numerical analysis, provided that this could later bring improvements on the operation of the network and reduced costs. However, when considering real-world application networks, simulating the gas network becomes computationally expensive due to the scale, complexity, and dynamic nature of the system. In this work we consider the isothermal Euler equations for ideal gas flow with nonlinear damping. Due to the computational cost, we employ a three-level model hierarchy for the optimization: the full model, the linearized model, and the reduced-order model. The full model ensures an accurate representation of the system. The linearized model simplifies the system by capturing its essential dynamics, offering a balance between computational efficiency and fidelity. Additionally, Space Mapping techniques were used to improve the linearized model with respect to the input-output structure. Finally, the reduced-order model employs proper orthogonal decomposition (POD) to retain the system features while reducing the computational cost.
With the isothermal model hierarchy the next step is to develop a controller for the network that can anticipate the demand from the consumers, but also respond to varying demands. For this reason, we develop a MPC strategy that includes constraints in state variables along the network. Using the hierarchy, we look to minimize the computational effort without compromising the accuracy required for practical applications and offer an effective framework for handling complex, high-cost simulations and controller design. We present the current results of this investigation.
