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Current natural gas consumption


All our figures are interactive: in the upper right area of each figure you will find buttons to zoom in and out. Individual time series can be shown or hidden by clicking in the legend.

Weekly data on gas savings

The Federal Network Agency assumes that natural gas consumption in Germany will have to fall by at least 20 percent compared to previous years to avoid a gas shortage in the winter of 2022/2023. In September 2022, the Federal Network Agency pointed out repeatedly that the achieved savings of households and businesses were too low, reiterated by President Klaus Müller on Twitter, among others. To avoid a gas shortage situation, absolute savings are the relevant measure, i.e. the actual consumption regardless of the outside temperature and thus the heating demand.

However, the analysis of pure natural gas consumption does not allow any conclusions on saving efforts. This is particularly true for consumption in the residential and commercial sectors, which, compared to that of industrial customers, is strongly dependent on the outside temperature. Only by adjusting for weather can one estimate the extent to which savings by households and businesses are due to changes in behaviour or due to weather influences. For a timely assessment of savings successes, it is therefore of interest to determine weather-adjusted natural gas consumption.

Based on consumption and temperature data from 2018-2021, we use a linear forest method (see methodology box below) to determine a relationship between outdoor temperature and natural gas consumption by residential and commercial customers. On this basis, we estimate the consumption in 2022 that would be expected based on current temperatures if natural gas customer behavior had not changed from recent years. The difference between this "expected" and actual consumption allows conclusions to be drawn on the extent to which conservation efforts in households and businesses have been effective to date. The focus here is on the period beginning in September 2022, or calendar week 36.

The figure shows that the expected natural gas consumption (dotted line) is significantly higher than the actual natural gas consumption. This means that households and commercial customers are currently consuming significantly less gas than would be expected given current temperatures and unchanged behavior.

Using the estimated "expected" consumption, we can specifically decompose the natural gas savings in 2022 into a "weather component" and a "behavior component". As evident in the figure above, 2022 savings vary considerably between weeks compared to the 2018-2021 average. September 2022 (Weeks 35-39) was exceptionally cool, which is reflected in a positive weather component. The expected natural gas consumption in these weeks was higher than the average in previous years. Despite strong behavioral savings, this caused consumption in weeks 37 and 38 to increase compared to the average for the respective weeks in previous years. In October (from week 39), however, unusually mild weather helped to reduce gas consumption and weather-related savings recently exceeded behavioral savings.

In total, residential and commercial natural gas consumption has decreased by about 20 percent since September 2022 compared to the 2018-2021 average consumption. As shown in the figure above, households and businesses actually saved a little more than 20 percent in the interim during the particularly cold month of September. To avoid a gas shortage, these savings successes must continue as temperatures return to colder temperatures later in the heating season.


Compared to an earlier version, we use an improved our forecasting model in this update. Using a "linear forest", a machine learning method, we estimate residential and commercial gas consumption based on average, maximum, and minimum daily temperatures for the current and the last three days. We aggregate data from hundreds of weather stations across Germany using the median to prevent bias from extreme data points, such as from the Zugspitze. In addition, we control for the current calendar month and weekend or public holidays to account for the seasonality inherent in gas consumption (beyond temperature variations) and different consumption behaviour on non-working days.

We train our model using daily data between July 2018 and December 2021. We obtain temperature data from the German Weather Service and gas consumption data from Trading Hub Europe. We validated the quality of the model's prediction against the actual consumption levels between January and June 2018 in order to determine the best performing model. In this way, we compared a range of machine learning models, including a neural network, a LASSO estimator, linear trees, gradient boosting, random forests, and linear forests. A linear forest specification had the lowest mean squared error and thus performed the best.

We use the resulting model to predict consumption in 2022. It is not trivial to determine the cutoff time after which we would expect actual natural gas consumption to deviate from the consumption estimated based on previous years. Comparable publications start forecasting as early as September 2021, when gas prices began to rise at European gas trading hubs. Another approach would be to select the beginning of the Russian war against Ukraine. We only consider households and commercial customers who are usually only affected by wholesale market developments with a long delay. Therefore, we deem it plausible that including training data through to December 2021 will not introduce bias into the forecast.

We compare our forecast with consumption data from the German Federal Network Agency in weekly resolution, as it provides more up-to-date data than the Trading Hub Europe.


Last update: 2022-11-24