Simulated and Synthetic Data Generation for Interdependent Natural Gas and Electrical Power System Based on Graph Theory and Machine Learning

The overall objective of this project is to apply recent advances in machine learning techniques and graph theory to investigate practical data-based approaches for producing simulated and synthetic datasets that faithfully represent interdependence between natural gas networks and power grids from mechanistic and human aspects.