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Accelerating fossil gas independence in Europe

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Achieving European Gas Autarky is Economically Compelling and Strategically Viable

Europe can reduce its reliance on imported natural gas by half without significantly increasing total energy costs. This is achieved by switching industry and home heating to electricity and biomass. However, even with less gas, global price spikes can still drive up electricity bills due to how energy markets are priced.

The transition away from fossil fuels is often framed as a binary choice between climate goals and energy security. While decarbonization efforts aim to lower emissions, sudden geopolitical shifts have transformed gas imports into a primary economic vulnerability. Policymakers are now debating whether Europe should pursue "autarky," a state where gas demand aligns strictly with domestic production capacity.

Previous research has often treated the phase-out of gas as a consequence of carbon pricing. Some studies also focus on isolated sectors like power generation. This approach fails to capture the complex, interconnected reality of an energy system. A new study from researchers at the Technische Universität Berlin addresses this gap. They model the entire European energy system as a single, coupled entity. Their findings reveal that the path to independence is economically rational.

The limitations of fragmented gas modeling

Current understandings of gas reduction often rely on case studies. These look at localized alternatives or model sectors in isolation. This is problematic because gas supplies account for roughly 20% of European energy. Reducing that consumption is a systemic overhaul, not a marginal adjustment. Many existing Large-scale Sector-Coupled Energy System Models (ESMs) have historically treated the industrial sector as an "exogenous" variable. This means they treat industrial gas demand as a fixed requirement that the model cannot change.

The authors argue that this oversight distorts the perceived cost of transitioning. If a model cannot "see" how gas scarcity drives up its value, it cannot accurately calculate the optimal order for switching sectors. Furthermore, many Integrated Assessment Models (IAMs) lack sufficient spatio-temporal resolution. This is the ability to track changes across specific geographic locations and granular time intervals. Without this, the true cost of "scarcity rent" (the economic value generated by a limited resource) remains hidden.

Co-optimizing the European energy grid

To overcome these blind spots, the authors utilize the PyPSA-Eur model. This is an open-source, sector-coupled, linear energy-system model. Rather than imposing fixed targets, the researchers implement a mechanism that iteratively tightens a cap on the total fossil gas supply. They start at 450 bcm/a (billion cubic meters per annum) and descend in 25 bcm increments until they reach zero.

The architecture of this model rests on three key technical pillars:

  1. Endogenous Industrial Heat: The authors represent industrial heat demand across four distinct temperature bands. These range from <100°C to >500°C. This allows the model to decide whether a factory should switch to an electric boiler, a heat pump, or hydrogen.
  2. Spatio-Temporal Granularity: The model operates at a 3-hourly temporal resolution across 50 geographic nodes. This is critical for capturing "Dunkelflaute" events (extended periods of low wind and solar output). These events dictate when gas-based backup generation is actually required.
  3. Load-Following Constraints: To avoid overestimating heating flexibility, the authors constrain residential and urban heating technologies to be "load-following." Specifically, they implement this as a bound on the partial load of the technology. This prevents the model from assuming a heat pump can perfectly smooth out demand. It forces the model to account for the fact that heating assets are sized for peak loads.

The economics of independence

The study finds that cutting import reliance is remarkably affordable. Moving from "Today's Demand" to a "No-LNG" scenario (limiting imports to pipelines) increases total system costs by only ~5 bne/a. This represents a cost increase of less than 1%. Even reaching the "Autarky" scenario (matching domestic production) only increases system costs by approximately 16 bne/a [Figure 2a]. This is a manageable increase of less than 2%.

The most efficient way to achieve these cuts is through the electrification of low-temperature industry heat (<500°C) and reducing gas use in bulk power generation [Figure 2b]. As gas supply is constrained, the model shows a shift toward renewable power, heat pumps, and biomass [Figure 2c]. Interestingly, if long-term gas prices settle at 30 e/MWh or higher, the autarkic state becomes the cost-optimal long-term equilibrium .

Figure 4
Figure 3: Technology roll-out in cost-optimal No-LNG and Autarky scenarios relative to early 2020s uptake trends. Wind combines both on- and offshore installation. Note that solid biomass and electric options already supply heat to industry. The present figure refers only to the additional heat supply needed to displace demand currently met by gas. In both cases, no consistent trend has been observed over the past years. National Energy and Climate Plan (NECP) targets for 2030 are from [54, 55]. For 2030 projections of gas-displacing industry electricity and biomass usage, we compare 2020 versus 2030 sector usage in [54]. Both numbers are only reported for FR, ES, LU, DK and so underrepresent real continent-wide expansion plans.

However, there is a catch regarding consumer protection. The authors demonstrate that even when gas accounts for a tiny fraction of the electricity mix (less than 8%), it dominates the "marginal electricity price." This is the price set by the most expensive generator needed to meet demand at a specific moment. Because of how electricity markets are structured, gas prices anchor electricity prices through the opportunity cost of battery dispatch .

Figure 5
Figure 4: System cost under different fossil gas supply constraints and global gas market prices. These prices are exogenous to the system and do not include a scarcity rent, unlike in Fig 2 b . The gas price range of 24.6-49.1 e /MWh represents where LNG market prices may settle in the long term. Model runs are in steps of 50 bcm (see small markers), and the long-term market equilibrium is derived from quadratic interpolations between them. The minimum of each parabola refers to the level of gas consumption where the value of gas to the system coincides with its price (i.e. the scarcity rent is zero), interpretable as the consumption where the model would settle under idealised market conditions. The total system cost includes investment, and therefore points on the parabolas to the right of the optimum represent costs for an energy system that is slow to adapt to changes in the price signal. Throughout, the model assumes a carbon price of 100 e /tCO2.

Consequently, a 1 e/MWh rise in global gas prices can increase consumer costs by ~8.7 bne/a .

Figure 6
Figure 5: Distribution of electricity marginal prices across networks under different fossil gas supply constraints. Each violin shows the distribution of electricity marginal prices at low-voltage (consumer) buses, with every bus-snapshot pair contributing one sample. Its /u1D466 -position is given by the network-wide load-weighted gas price, which rises with scarcity as consumption decreases; the right-hand labels give the corresponding gas consumption and gas share of the electricity mix. The red line shows the fuel-only short-run marginal cost of combined-cycle gas turbines (CCGT), with slope set by their efficiency ( /u1D702CCGT ≈ 0.58 ). Each network has around 146,000 bus-snapshot pairs.

Assessing the modeling trade-offs

The authors acknowledge several technical limitations. The use of a "brownfield" model—one that includes existing, already-built infrastructure—introduces a slight bias toward using current assets. Since existing gas boilers are often inexpensive to operate initially (low CAPEX), the model might slightly underestimate the urgency of retiring them.

Additionally, the study relies on a single weather year (2024) to represent climate variability. January 2024 contained a significant cold spell. The authors note this might make heat pumps appear slightly less economically attractive than they would be in a temperate year. Finally, the model uses wholesale electricity prices. These do not capture the full complexity of retail consumer bills, such as local grid tariffs, taxes, and utility margins.

The verdict: A strategic imperative

The evidence suggests that achieving gas autarky is a highly viable strategy. The cost of building a self-sufficient system is significantly lower than the financial burdens Europe has faced due to gas price volatility since 2022. The primary obstacle is not economic feasibility, but the speed of technological deployment. To reach autarky by 2035, Europe would need to double its current installation rates for wind, solar, and heat pumps .

Figure 3
Figure 2: European energy system transformation pathways as annual fossil gas supply is constrained to different values ( /u1D465 -axis). A fixed carbon price of 100 e /tCO2 is assumed throughout. The vertical shaded areas indicate consumption levels between 2020 and 2025 (Today's Demand), vertical lines highlight the European annual domestic production capacity of 200 bcm ( Autarky scenario) and domestic production plus pipeline imports from Azerbaijan and North Africa to 275 bcm ( No-LNG scenario). a Total system cost with and without spending in carbon markets. b Gas allocation by sector. Industry heat < 500°C groups the three heating bands < 100°C, 100-200°C and 200-500°C, building heat includes residential and service sector heat for rural, individual urban and district demands. Steam-methane reforming with carbon capture is not enabled in the model. c Shares of supply mix by sector. Note that the slice of industry heat demand shown here refers only to the share currently supplied by gas. Further note that the model natively works in TWh. To represent gas-related quantities in billion cubic meters (bcm), we chose a unit conversion factor of 10 as conventions differ around this value.

If the goal is to protect consumers, simply reducing gas imports is insufficient. Because gas prices continue to leak into electricity prices via marginal pricing mechanisms, policymakers must act. They should consider structural reforms, such as decoupling bulk renewable generation from marginal prices. This will ensure that energy independence actually results in price stability. Code and data for the model are reportedly available; see the paper for the canonical link to the GitHub repository.

Figures from the paper

Figure 1
Figure 1 — from the original paper
Figure 2
Figure 1: a Map of European gas infrastructure and supply pathways. b Supply and consumption split by country and sector. Consumption data from Eurostat [10, 11]; supply data from [12]; industrial site locations from [13, 14].
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#energy system modeling#gas decarbonization#electrification#European energy security
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