8877
2022
eng
200
205
conferenceobject
Springer, Cham
1
2022-08-30
2022-08-30
--
Modeling and Forecasting Gas Network Flows with Multivariate Time Series and Mathematical Programming Approach
With annual consumption of approx. 95 billion cubic meters and similar amounts of gas just transshipped through Germany to other EU states, Germany’s gas transport system plays a vital role in European energy supply. The complex, more than 40,000 km long high-pressure transmission network is controlled by several transmission system operators (TSOs) whose main task is to provide security of supply in a cost-efficient way. Given the slow speed of gas flows through the gas transmission network pipelines, it has been an essential task for the gas network operators to enhance the forecast tools to build an accurate and effective gas flow prediction model for the whole network. By incorporating the recent progress in mathematical programming and time series modeling, we aim to model natural gas network and predict gas in- and out-flows at multiple supply and demand nodes for different forecasting horizons. Our model is able to describe the dynamics in the network by detecting the key nodes, which may help to build an optimal management strategy for transmission system operators.
Operations Research Proceedings 2021. OR 2021.
10.1007/978-3-031-08623-6_31
Lecture Notes in Operations Research
yes
publish
urn:nbn:de:0297-zib-82966
Nazgul Zakiyeva
Milena Petkovic
Milena Petkovic
MODAL-Gesamt
Petkovic, Milena
Applied Algorithmic Intelligence Methods
MODAL-EnergyLab
Zakiyeva, Nazgul