Influence of smart meters on the accuracy of methods for forecasting natural gas consumption

Scientific paper - Original scientific paper

• Author: Ivan Smajla
• Author: Daria Karasalihović Sedlar
• Author: Domagoj Vulin
• Author: Lucija Jukić
• Author's institution: University of Zagreb; Faculty of Mining, Geology and Petroleum Engineering; (Department of Petroleum and Gas Engineering and energy)
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mining, Petroleum and Geology Engineering
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Interdisciplinary Technical Sciences

Abstract (english)

In 2019, natural gas accounted for 25.4% of gross inland consumption in the European Union (EU), making it one of the most important energy sources in the EU. The importance of natural gas, together with the ongoing liberalization of the gas market, has made the natural gas sector significantly commercially sensitive. To reduce the risk of financial losses, balance group managers often need to have an accurate forecast of natural gas consumption. An accurate forecast will ensure small deviations between actual gas consumption and reserved gas volumes and transmission system capacity resulting in less balancing energy required, which is sold at a higher price in the final balancing process. This paper researches the optimal number of smart meters and best fitted consumption data distribution in order to achieve satisfactory results in terms of the accuracy by using simple forecasting methods. Beside mentioned, this paper provides accuracy overview of various already available forecasting methods, as well as the selection of input parameters for forecasting short term natural gas consumption. Using the calculated linear temperature dependence together with the lognormal distribution, the consumption of natural gas was simulated for 12 different cases. The simulation showed that, if more than 10 000 smart meters were installed, deviation between average estimated natural gas consumption and the real data would be less than ±2.96 %. In case of 100 000 smart meters installed, deviation would be less than ±1.20 %, but the ‘‘large’’ partly temperature independent consumers must be disregarded.

• Keywords (english): natural gas consumption; forecasting methods; input parameters; smart metering; simulation; lognormal distribution
• Language: english
• Publication type: Scientific paper - Original scientific paper
• Publication status: Published
• Peer review: Peer review - international
• Publication version: Published version
• Journal title: Energy Reports
• Numbering: vol. 7, pp. 8287-8297
• p-ISSN: 2352-4847
• DOI: https://doi.org/10.1016/j.egyr.2021.06.014
• URN:NBN: urn:nbn:hr:169:392564
• Publication: 2021-11
• Document URL: https://linkinghub.elsevier.com/retrieve/pii/S2352484721003760
• Type of resource: Text
• Access conditions: Open access
• Created on: 2022-11-07 08:49:02