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REVIEW 2 major objections 6 minor 76 references

A mix of long-duration hydrogen and thermal storage enables large-scale electrified heating in a renewable European energy system

T0 review · 2 major / 6 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read Electrified heating with heat pumps quadruples Europe's need for long-duration electricity storage.

desk verdict Useful, transparent scenario study; the headline LDES quadrupling is conditional on inflexible heat demand, so treat it as a model envelope and require a flexibility sensitivity before publication. read the letter →

arxiv 2505.21516 v2 pith:AZABW6QG submitted 2025-05-21 physics.soc-ph econ.GNq-fin.EC

Felix Schmidt , Alexander Roth , Wolf-Peter Schill This is my paper · ORCID
classification physics.soc-phecon.GNq-fin.EC
keywords long-durationelectricitystoragehydrogencavernthermalenergyheatpumpsheatingelectrificationweathervariabilitycapacityexpansionsectorcoupling
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Across 78 historical weather years in a fully renewable European power system, adding heat pumps for $80\%$ of building heat demand more than quadruples the average optimal amount of long-duration electricity storage (LDES), from $37$ to $168$ TWh. The paper isolates why: about $75\%$ of the increase is a leverage effect, in which winter heating load amplifies the energy deficit during renewable scarcities, and about $25\%$ is a compound effect, in which exceptional cold spells hit periods of low wind and sun. Adding long-duration thermal storage (pit storage) in district heating networks cuts the extra LDES requirement by about one third on average, and in the coldest year in the sample, 1962/63, it reduces a $400$ TWh hydrogen-storage requirement by $155$ TWh. The result matters because it shows that demand-side weather variability, not just supply-side variability, drives storage needs, and that hydrogen caverns and thermal pits are complements rather than substitutes.

What carries the argument

The argument is carried by a scenario decomposition inside a sector-coupled capacity-expansion model of 28 European countries at hourly resolution. Three runs are compared: no electrified heat; heat pumps with each weather year's actual heat demand and heat-pump efficiency; and heat pumps with the long-run mean hourly demand profile. The difference between the second and third runs isolates the compound effect (year-specific cold spells), and the difference between the third and first runs isolates the leverage effect (seasonal load). A second co-optimization adds long-duration pit thermal storage in district heating networks, parameterized with a conservative $61\%$ of energy remaining after 90 days, and compares it with a hydrogen cavern cycle whose round-trip efficiency is about $30\%$.

What would settle it

Re-run the capacity expansion for 1962/63 under a rolling-horizon or stochastic dispatch instead of perfect foresight; if optimal LDES stays near $400$ TWh the clairvoyance assumption is not driving the headline, and if it falls sharply the capacity numbers are partly an artifact of perfect foresight.

Watch

Extended reading notes

Core claim

The paper's central claim is that electrified space and water heating with air-source heat pumps transforms the long-duration storage problem in a fully renewable Europe: average optimal hydrogen-cavern storage capacity rises more than fourfold, from $37$ to $168$ TWh, a $273\%$ increase, and the spread across weather years widens from a standard deviation of $10$ TWh to $66$ TWh because heat demand itself is weather-dependent. The increase is decomposed into a leverage effect ($75\%$), from seasonal heating load amplifying the winter renewable deficit, and a compound effect ($25\%$), from cold spells coinciding with renewable droughts; the sharpest case is 1962/63, the coldest European winter in the sample, which needs $400$ TWh of LDES without thermal storage. Co-optimized pit thermal storage in district heating networks, which can hold heat for a season despite conservative loss assumptions, reduces the extra LDES need by $36\%$ on average while leaving a residual storage need above the no-heat case. The paper therefore argues that LDES and LDTS should be deployed together, with regulatory frameworks supporting both.

Load-bearing premise

The headline numbers rely on the assumption that each weather year is optimized with perfect foresight, that heat demand is an exogenous, inflexible load served only by a single type of air-source heat pump with no building retrofits, and that district heating has no heat sources beyond large heat pumps.

Editorial extensions

If this is right

  • A European grid with $80\%$ heat-pump electrification and no long-duration thermal storage needs on average $168$ TWh of hydrogen cavern storage, and up to $400$ TWh in a worst-case weather year.
  • Weather-year variance in optimal LDES capacity grows from a standard deviation of $10$ TWh to $66$ TWh once heating is electrified, so single-year studies can badly misestimate storage needs.
  • Pit thermal storage in district heating networks can cut the additional LDES requirement by about one third on average, but cannot eliminate it: even full district heating leaves LDES above the no-heat level.
  • Long-duration storage capacity concentrates in Germany under decentralized heat pumps; adding district-heating storage spreads the infrastructure across Europe and reduces German cavern dependence.
  • Cost and efficiency improvements in pit thermal storage beyond the base case reduce LDES further, with the remaining bound set by country-level district heating potential, not by storage economics.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If buildings were retrofitted or heat pumps were operated flexibly, the $273\%$ LDES increase would likely shrink, since a large part of the load is treated as immovable; the paper's magnitude should be read as an upper bound for a single-technology rollout.
  • The leverage/compound decomposition suggests that policies flattening winter heat demand, such as retrofits and hybrid heat pumps, could substitute for part of the cavern investment that renewable-drought forecasting alone would not avoid.
  • Because LDTS only serves heat while hydrogen can serve many end uses, the complementarity result would persist in a stochastic setting, but the optimal mix could shift toward hydrogen when perfect foresight is relaxed.
  • Extending the analysis to post-2050 climate scenarios, with warmer average winters but possibly more extreme cold spells, would test whether the 78-year historical distribution brackets future demand-side weather risk.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 6 minor

Summary. The paper investigates how electrified heating with heat pumps affects optimal long-duration electricity storage (LDES) in a fully renewable European power system, using a sector-coupled linear optimization model (an extension of DIETER) across 78 weather years. The main finding is that 80% electrified heating more than quadruples the average optimal LDES energy capacity, from 37 TWh to 168 TWh, with 75% of the increase attributed to a 'leverage effect' and 25% to a 'compound effect' of cold spells coinciding with renewable scarcity. The paper also finds that long-duration thermal storage in district heating networks reduces LDES needs by about 36% on average, and discusses the geographic distribution of storage and policy implications.

Significance. If the quantitative claims hold, the paper makes a useful contribution by quantifying demand-side weather variability as a driver of long-duration storage needs, an aspect often neglected in supply-focused LDES studies. The use of 78 weather years, the transparent extension of the open-source DIETER model, and the provision of code and data repositories are strengths. The leverage/compound decomposition is a simple but effective way to isolate seasonal versus episodic demand effects, and the policy-relevant finding that thermal storage can substantially mitigate, but not eliminate, LDES requirements is plausible and well-illustrated. However, the headline magnitudes rest on assumptions that are not fully stress-tested, particularly the treatment of heat pumps as an inflexible exogenous load.

major comments (2)
  1. [Sections 2.1, 2.2, 4.1.4, 4.1.6] The model treats decentralized heat pump electricity demand as an exogenous, inflexible time series with only 1.5-hour buffer storage. This assumption is load-bearing for the headline result, because the leverage effect (Section 2.2) arises precisely from the fixed winter peak of this load. Real heat pumps offer flexibility through building thermal mass, hot water tanks, and pre-heating, and the paper's own reference [35] demonstrates power-sector benefits of such flexibility. The paper discloses the simplification in Section 3.2 but does not test its impact. I request a sensitivity analysis that allows some share of heat demand to be shifted over hours to days (e.g., larger buffer, price-sensitive operation, or building-mass pre-heating) for at least the four weather years used in Section 2.5, and a report of how the 'more than quadruple' figure and the 75/25 decomposition change. Without this, the magnitude of the central claim remains an artifact of the inflexibility assumption.
  2. [Abstract and Section 2.1] The stated percentage increase is arithmetically inconsistent. The text reports average LDES capacities of 37 TWh (No Heat) and 168 TWh (Decent), an increase of 131 TWh. That is an increase of 131/37 = 354%, not 273%. The phrase 'more than quadruple' in the abstract is consistent with 168/37 = 4.54, but the percentage number should be corrected, or the baseline for the 273% figure should be clarified. This error appears in the abstract, Section 2.1, and the caption of Figure 1.
minor comments (6)
  1. [Section 2.3] The phrase 'reduces the additional LDES requirements from electrified heat by 60 TWh (36%) on average' is ambiguous: 60 TWh is 36% of the total Decent LDES capacity (168 TWh), but only about 46% of the additional 131 TWh. Please clarify whether the 36% refers to total or additional LDES requirements.
  2. [Section 4.2.2] The text states 'We provide details on our approach in SI.XX.' — this is an unresolved placeholder that should be replaced with the actual section reference.
  3. [Introduction] There is a typo in the sentence 'In conclusion, the the previous literature on heat electrification and LDTS is largely focused on local energy systems'; the duplicate 'the' should be removed.
  4. [Author affiliations] The affiliation 'Divison of Applied Mechanics and Energy Conversion' contains a typo; it should be 'Division'.
  5. [Section 2.5 and Figure 5] The upper panel of Figure 5 reports 'LDES requirement vs baseline' ratios, but the text says LDTS 'reduces LDES needs by another 19-35%' without clearly defining the baseline for the word 'another'; please specify whether this is relative to the base case or to another reference.
  6. [Table 1] The scenario name 'Decent' is unusual; consider renaming it to 'Decentral' or another term that is less likely to be confused with the English adjective, to improve readability.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the headline numbers are outputs of an open, externally parameterized optimization model, and the 75/25 decomposition is an explicit scenario-difference accounting identity rather than a fitted result.

full rationale

The paper's central claims — that electrified heating more than quadruples optimal long-duration electricity storage, that this increase decomposes into 75% leverage and 25% compound effects, and that long-duration thermal storage reduces LDES needs by 36% — are all outputs of a linear cost-minimizing capacity expansion model (DIETER) driven by exogenous weather, demand, and cost data. No parameter is fitted to reproduce these headline numbers, and no equation defines the target result in terms of an assumed value of that same result. The 75/25 decomposition is constructed explicitly as an accounting identity across three scenario runs: 'No Heat', 'Decent - Mean' (long-run mean heat demand and COP), and 'Decent' (year-specific heat demand). Section 2.2 states that the leverage effect is the difference between the Decent - Mean and No Heat scenarios and the compound effect is the residual from year-specific heat demand; this is a transparent decomposition of a model output, not a self-fulfilling definition. The self-citations that appear are not load-bearing circularity: the DIETER model reference [54] attributes use of an open-source, previously published model; the 1.5-hour decentralized heat-pump buffer storage assumption cites co-author work [35] as an input parameter, and the paper's Limitations section explicitly acknowledges the simplification of inflexible heat demand and perfect foresight. These are modeling-envelope assumptions that affect the magnitude of results, not devices that force the conclusions by construction. No uniqueness theorem from the authors' prior work is invoked, and no known empirical result is merely renamed. The skeptic's concern about heat-pump flexibility is a legitimate sensitivity/robustness limitation, but it is not circularity: the model does not assume the quadrupling result, it computes it from exogenous inputs. Therefore no specific circular reduction can be exhibited, and the appropriate finding is no significant circularity.

Assumptions & free parameters 4 free parameters · 8 assumptions · 0 invented entities

The headline numbers are scenario outputs resting on a long chain of exogenous parameters and modeling simplifications. Most inputs come from the literature, but the 80% electrification share, the district heating potential, the LDTS efficiency assumptions, and the perfect-foresight deterministic setup are load-bearing. No new physical entities are introduced.

free parameters (4)
  • Electrified heat share = 80% of residential and commercial heat
    Scenario assumption at the upper end of JRC projections (Section 4.3); directly scales all headline LDES numbers and is not varied in the main analysis.
  • District heating potential share = country-specific, about 32% on average
    Optimistic 2050 DH scenario from Fallahnejad et al. [71] constrains how much LDTS can substitute for LDES (Section 2.3 and SI.2.1).
  • LDTS 90-day energy retention = 61%
    Base-case standing-loss assumption from Zeyen et al. [33]; central to the computed 36% LDES reduction (Section 4.1.6).
  • LDTS charge/discharge efficiency = 90%
    Assumed allowance for district heating network losses; affects LDTS economics and substitution potential (Section 4.1.6).
assumptions (8)
  • domain assumption Each weather year is optimized with perfect foresight as a deterministic problem.
    Section 3.2: the authors note this leads to ideal but unrealistic storage operation and likely underestimates the relative value of LDES.
  • domain assumption Linear cost-minimizing model abstracts from discrete capacity decisions, economies of scale, and non-convex operational constraints.
    Section 4.1: DIETER is a linear model, so integer unit-commitment constraints are absent, which can affect storage and generation portfolios.
  • domain assumption Heat demand is an exogenous, inflexible load served by a single air-source heat pump type; no building efficiency improvements are included.
    Sections 3.2 and 4.1.6: this biases electricity demand and LDES needs upward relative to a system with flexible heat pumps or renovated buildings.
  • domain assumption District heating is aggregated at country level and supplied only by large-scale air-source heat pumps; waste heat and solar thermal are excluded.
    Sections 3.2 and 4.1.6: authors state this is conservative and could understate LDTS substitution.
  • domain assumption Electricity and hydrogen transmission capacities are fixed to TYNDP 2022 and TYNDP 2024 reference grids.
    Sections 2.5 and 4.1.1: interconnection is not co-optimized; sensitivity tests show limited effect on LDES requirements.
  • domain assumption Historic weather years (1940 to 2018) represent future 2050 conditions; only heat and hydro time series are de-trended.
    Section 4.2.2: no climate-change adjustment is described for wind and solar capacity factors or heat pump COP.
  • domain assumption Hydrogen imports are limited to long-term baseload contracts with plus or minus 10% hourly flexibility, and industrial hydrogen demand is flat.
    Sections 4.1.4 and 4.1.5: constrains hydrogen supply and affects how much cavern storage is needed.
  • domain assumption Pit thermal storage thermodynamics are simplified, neglecting electricity demand during discharge for temperature lift.
    Section 3.2: authors note this could reduce the cost advantage of thermal storage against hydrogen storage.

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Cite this review

Pith. "Pith review of A mix of long-duration hydrogen and thermal storage enables large-scale electrified heating in a renewable European energy system." pith.science (2026). https://pith.science/paper/AZABW6QG

@misc{pith2026250521516,
  author       = {Pith},
  title        = {Pith review of: A mix of long-duration hydrogen and thermal storage enables large-scale electrified heating in a renewable European energy system},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/AZABW6QG}},
  note         = {Machine review of arXiv:2505.21516}
}
read the original abstract

Hydrogen-based long-duration electricity storage (LDES) is a key component of renewable energy systems to deal with seasonality and prolonged periods of low wind and solar energy availability. In this paper, we investigate how electrified heating with heat pumps impacts LDES requirements in a fully renewable European energy system, and which role thermal storage can play. Using a large weather dataset of 78 weather years, we find that electrified heating significantly increases LDES needs, as optimal average energy capacities more than quadruple across all weather years compared to a scenario without electrified heating. We attribute 75% of this increase to a leverage effect, as additional electric load amplifies storage needs during times of low renewable availability. The remaining 25% are the result of a compound effect, where exceptional cold spells coincide with periods of renewable scarcity. Furthermore, heat pumps increase the variance in optimal storage capacities between weather years substantially because of demand-side weather variability. Long-duration thermal storage attached to district heating networks can reduce LDES needs by on average 36%. To support and safeguard wide-spread heating electrification, policymakers should expedite the creation of adequate regulatory frameworks for both long-duration storage types to de-risk investments in light of high weather variability.

Figures

Figures reproduced from arXiv: 2505.21516 by the authors.

Figure 1
Figure 1. Long-duration electricity storage requirements in scenarios with different electrified heat demand levels Optimal long-duration electricity storage capacities by weather year. Gray dots represent optimal capacities in the No Heat scenario. Dark-red dots represent optimal capacities in the Decent scenario. Light-red crosses represent optimal capacities in the Decent - Mean scenario, in which weather-year specific hea… view at source ↗
Figure 2
Figure 2. LDES trajectories with and without electrified heat in selected weather years LDES trajectories shown against daily deviations in heat demand from long-run mean (bright red - mid) and 24-hour rolling renewable availability (green - low). The gray area represents the storage trajectory in No Heat. The darker red area shows the additional storage level in Decent - Mean, and the lighter red addition represents the incr… view at source ↗
Figure 3
Figure 3. LDES requirements without and with district heating thermal storage left: distribution of LDES capacities across weather years under Decent and District & Decent scenarios; center: distribution of LDTS capacities in District & Decent scenario across weather years (center); right: 1962/63 daily electricity sector balance for Decent scenario (upper) and District & Decent scenario (lower). The introduction of LDTS only… view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: Geographical impact of adding long-duration thermal storage in 1962/63 (a) Share of district heating heat demand covered by LDTS; (b) Change in LDES capacity when introducing LDTS; (c) Change in PEM electrolysis when introducing LDTS; (d) Change in H2 turbine capacity …
Figure 5
Figure 5. Figure 5: LDTS sensitivity results Sensitivity of LDTS parameters. The x-axis varies heat losses from the base case to almost no losses in energetic terms, expressed as energy remaining after 90 days in storage. The y-axis varies the assumed investment costs of LDTS by multiplyi…

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Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.