Towards a space mapping approach to dynamic compressor optimization of gas networks

The goal of this paper is to present an efficient approach for dynamic compressor optimization in gas networks based on a space mapping approach. For the fine space a non-linear isothermal gas flow model is employed, whereas for the coarse-space model an algebraic model is applied. To solve an optimization problem with the nonlinear model is expensive. Nevertheless we desire to bring as much nonlinear effects into the optimization process as possible. The mathematical formulation and algorithmic aspects of a space mapping technique are developed. A framework in which such can be achieved for compressible isothermal gas flow is presented. Computational results and comparison between different approaches are presented. The results demonstrate that such a multi-level approach provides more accurate results efficiently.