Forecasting day-ahead high-resolution natural-gas demand and supply in Germany-Reference-Cited by-同舟云学术

Forecasting day-ahead high-resolution natural-gas demand and supply in Germany

Published:2018-10 Issue: Volume:228 Page:1091-1110
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Chen Ying^ORCID,Chua Wee Song^ORCID,Koch Thorsten^ORCID

Funder

Singapore Ministry of Education Academic Research Fund Tier 1

Institute of Data Science

German Federal Ministry of Education and Research

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference33 articles.

1. Arbeitsgemeinschaft Energiebilanzen e.V. Auswertungstabellen zur Energiebilanz Deutschland 1990 bis 2016. Technical Report, Stand: September 2017; 2017 .

2. Forecasting natural gas consumption;Soldo;Appl Energy,2012

3. An adsorbed gas estimation model for shale gas reservoirs via statistical learning;Chen;Appl Energy,2017

4. A dynamic model of global natural gas supply;Crow;Appl Energy,2018

5. An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power;Qiao;Appl Energy,2017

Cited by 36 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of forecasting strategies and techniques to natural gas consumption: A comprehensive review and comparative study;Engineering Applications of Artificial Intelligence;2024-03

2. Forecasting and Modeling the Dynamics of Large-Scale Energy Networks Under the Supply and Demand Balance Constraint;AIRO Springer Series;2024

3. A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling;Energies;2023-06-15

4. Future outlook and influencing factors analysis of natural gas consumption in Bangladesh: An economic and policy perspectives;Energy Policy;2023-02

5. Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model;Open Journal of Statistics;2023