A hybrid approach for high precision prediction of gas flows

Abstract

About 23% of the German energy demand is supplied by natural gas. Additionally, for about the same amount Germany serves as a transit country. Thereby, the German network represents a central hub in the European natural gas transport network. The transport infrastructure is operated by transmissions system operators (TSOs). The number one priority of the TSOs is to ensure the security of supply. However, the TSOs have only very limited knowledge about the intentions and planned actions of the shippers (traders). Open Grid Europe (OGE), one of Germany’s largest TSO, operates a high-pressure transport network of about 12,000 km length. With the introduction of peak-load gas power stations, it is of great importance to predict in- and out-flow of the network to ensure the necessary flexibility and security of supply for the German Energy Transition (“Energiewende”). In this paper, we introduce a novel hybrid forecast method applied to gas flows at the boundary nodes of a transport network. This method employs an optimized feature selection and minimization. We use a combination of a FAR, LSTM and mathematical programming to achieve robust high-quality forecasts on real-world data for different types of network nodes.

Generative deep learning for decision making in gas networks

“…MohamadiBaghmolaei et al (2014) present a NN combined with a genetic algorithm for learning the relationship between compressor speeds and the fuel consumption rate in the absence of complete data. More often, ML has been used in fields closely related to gas transport, as in Hanachi et al (2018), with ML used to track the degradation of compressor performance, and in Petkovic et al (2019) to forecast demand values at the boundaries of the gas network. For a more complete overview of the transient gas literature, we refer readers to Ríos-Mercado and Borraz-Sánchez (2015).…”

Study on the Coupling Effect of Stress Field and Gas Field in Surrounding Rock of Stope and Gas Migration Law

“…This kind of disaster seriously threatens the safety of production, and it is also the focus of many scholars. Over the years, various coal-mining countries have done a lot of research on the mechanism and prevention technology (Gas drainage) of gas disasters and also achieved some research results [1][2][3][4][5][6][7][8][9]. According to the existing research results, it can be known that the stress redistribution of surrounding rock caused by mining has great influences on the development of cracks in the roof and overlying strata, gas desorption, and seepage in coal seams.…”