Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript evaluates the techno-economic competitiveness and future deployment of decentralized heat pumps in Germany towards 2045. Using the RENDER-Building framework, it integrates local heat-source potentials with district-heating and gas-infrastructure constraints, and examines technology uptake, heating costs, expenditures, and CO₂ emissions under three scenarios. The results are further discussed across different building and settlement types. However, several issues should be addressed before publication:

1. The Abstract is too lengthy and should be shortened to highlight the main methods and findings.
2. Please check the consistency of the reported HP capacity. Section 4.2 gives approximately 55 GW by 2045, while Section 4.4.2 and the Conclusions report approximately 52 GW.
3. The definition and implementation of the subsidy term in Equation (2) should be clarified. The variable sub is defined as the “rate of subsidy on the investment”, while the equation appears to multiply the investment expenditure directly by sub. However, the manuscript later states that a 35% subsidy reduces the effective investment cost of heat pumps. Please clarify whether sub represents the subsidy rate or the remaining investment-cost fraction after subsidy.
4. Please provide the value of the discrete-choice parameter β in Equation (1) and briefly explain how it was determined.
5. The relationship between the annual expenditures shown in Figure 17 and the cumulative expenditure differences discussed in the text should be clarified. Figure 17 presents annual CAPEX and OPEX values for selected years, whereas the subsequent discussion reports cumulative expenditure differences over the period 2026–2045. Please briefly explain how the cumulative values were obtained so that the relationship between the figure and the reported cumulative results is transparent.
6. A final language and presentation check is recommended. There are several minor grammatical or typographical issues, for example the duplicated expression “25 billion Euros less CAPEX less” in Section 4.3.
7. In Equation (2), the left-hand side is written as COH, while the text consistently refers to LCOH. Please check and unify the notation.
8. Please check the figure reference in Section 3.3. The HP efficiency (SPF) pathway is shown in Figure A2 rather than Figure A1.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript is interesting and presents a relevant and valuable analysis of the techno-economic competition between decentralized heat pumps, district heating, and gas-based heating systems in the German building stock towards 2045. A particular strength of the manuscript is the combination of the dynamic agent-based RENDER-Building model with spatially resolved environmental heat-source potentials and infrastructure availability constraints. The study addresses an important topic and provides results of interest to researchers and policymakers working on the decarbonization of the building sector. However, several methodological assumptions directly affect the projected competitiveness and uptake of heat pumps and require further clarification and robustness assessment before the conclusions can be considered sufficiently supported. In my opinion, addressing the following points could further improve the scientific clarity and robustness of the manuscript:

1. Equation (2) requires careful clarification. The investment term appears to include IEU x CAP x sub, but “sub” is defined as the “rate of subsidy on the investment.” Therefore, if it denotes a subsidy rate of 35%, multiplying the full investment cost by 0.35 would represent the subsidized portion, not the remaining cost. Perhaps it should be “1 – sub” or “sub” requires a different definition. This point is particularly important because the assumed subsidy directly affects the calculated LCOH.
2. The technology-choice mechanism requires stronger justification, parameter transparency, and sensitivity analysis. The manuscript should provide the numerical value, source, calibration procedure, and interpretation of the discrete-choice parameter β. If these details are presented in the previously published RENDER-Building model, the essential information should nevertheless be summarized in the present manuscript rather than relying entirely on Ref. [8]. I also recommend performing a sensitivity analysis for β to demonstrate the robustness of the projected technology uptake.
3. The heat-pump SPF methodology should be described more clearly and made more physically transparent and reproducible. SPF is one of the most influential assumptions in the paper because it directly affects electricity consumption and LCOH. For example, the resulting factors in Table 1 are not monotonic with heating-system supply temperature; the ASHP adjustment increases from 1.01 for A+ to 1.05 for C/D despite the higher assumed supply temperature. The influence of increasing DHW fractions may explain this behavior, but the current description is insufficient to reproduce or fully assess the calculation.
4. A sensitivity analysis of the key techno-economic assumptions could strengthen the claim that the identified HP deployment is “robust” across the German building stock.
5. The conclusions should more clearly distinguish model outcomes from robust real-world predictions; therefore, I recommend revising the Abstract, Discussion and Conclusions so that the distinction between scenario-based model projections and likely real-world outcomes is consistently maintained.

In conclusion, I recommend a Major Revision.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The paper is generally okay, but some comments can be considered by the authors:

1) The paper’s novelty should be stated more clearly, especially in comparison with the authors’ previous work using the RENDER-Building model.

2) The Methods section should clearly define the scope of the study, including the technologies considered, building types, and system boundaries.

3) The model description relies heavily on the authors’ previous publication. More information should be included here so that readers can understand the main modelling and decision-making processes.

4) A summary table of the main datasets and assumptions would improve readability.

5) The relationship between LCOH and technology adoption needs clearer explanation. The LCOH considers lifetime costs, whereas the technology-choice model appears to consider only one year of energy costs.

6) The conclusion that building energy performance is not a major barrier to heat-pump adoption should be expressed more carefully.

Author Response

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Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

Critical Questions Regarding the Methodology

The Impact of Physical Limitation of Biomass Potential on the Results of the "Gas Focus" Scenario. In Sections 4.2 (lines 541-554) and 4.4.5, the authors rightly note that the demand for biomass and biogas in the model reaches astronomical value (e.g., a total of about 240 TWh by 2045 in the Gas Focus scenario), which contradicts macroeconomic analyses of biomass potential for the entire German economy (200-500 TWh). Since the model does not endogenously limit biomass availability but merely responds to it with a demand-supply curve, the biogas/biomass prices in Table A2 are likely drastically underestimated compared to the market realities in which heavy industry and aviation would compete for this raw material. How does artificially inflating biomass availability (and underestimating its price) distort the economic results (LCOH) for biomass boilers and the Gas Focus scenario? Can the authors conduct a sensitivity analysis (or an additional scenario) in which the supply of biomass for the building sector will be "hardly" limited (e.g. to a maximum of 30-40 TWh) to check whether, in conditions of real raw material deficit, heat pumps (HP) and district heating networks (DH) do not become the only physically and economically viable alternative?

Physical constraints of distribution networks (Grid Congestion) and grid fees. The model accounts for increased grid fees (variants I and II, lines 424-428) as an economic factor. However, installing 11-15 million heat pumps (approximately 40-52 GW of capacity) places a colossal burden on local low-voltage grids (especially in suburban and rural areas, where the model predicts the largest HP increase – lines 610-612). Does the RENDER-Building model account for physical constraints on the capacity of local transformers and networks (so-called grid congestion), which in reality often block or delay the connection of new heat pumps and necessitate costly infrastructure upgrades (these costs do not always fully cover the grid fees paid by consumers)? The absence of this parameter may make the projected adoption of heat pumps in rural areas overly optimistic.

 

The paper's originality lies in its integrated, high-resolution, bottom-up modeling of Germany’s building stock, combining local heat source potentials with infrastructure constraints. It addresses the gap by simultaneously analyzing technology competitiveness, infrastructure availability, and sector dynamics over time, providing detailed insights into regional adoption patterns and transition pathways for decentralized heat pumps. This approach enhances understanding of practical feasibility and resource allocation in decarbonizing building heating systems.

It provides a bottom-up, spatially resolved model of heating technology adoption, including infrastructure constraints and local heat sources, over Germany’s entire transition to 2045. This enables detailed insights into technology competition, regional differences, and realistic transition pathways, going beyond aggregate or static analyses found in prior research.

The authors should incorporate dynamic decision-making processes, capturing behavioral, policy, and socio-economic factors influencing technology adoption, beyond pure techno-economic analysis. Including sector-specific biofuel availability and regional energy price variations would improve accuracy. Controls for short-term shocks, such as sudden policy changes or energy price fluctuations, should be added to reflect real-world investment behaviors. Additionally, modeling interactions between on-site renewable generation (PV, batteries) and heat technologies could enhance understanding of integrated systems. Incorporating sensitivity analyses for key assumptions and uncertainty quantification would strengthen the robustness of the results.

The conclusions align well with the evidence showing decentralized HPs' cost-competitiveness, adoption patterns, and emission reductions across scenarios. The study addressed all main questions through scenario-based simulations, LCOH analyses, and supply-demand modeling, specifically illustrated in Figures 8 and 7 and detailed in Sections 4.4 and 5. The methodology's comprehensive approach supports the findings, though certain assumptions and limitations were acknowledged, ensuring logical consistency.

The references are appropriate, covering relevant recent studies and policies, with some older than five years (e.g., [6], [7], [9]). No evident self-citations are present. They adequately support the analysis and context of the research.

Logical Inconsistencies

No Costs of Adapting Equipment to "Green Gases" and Biofuels (Lines 651-653). The authors state: "It is important to note that the gradual blending of biogenic and other green fuels is assumed to incur no additional costs to the existing equipment." This is a serious logical and technical error. While biomethane admixtures may be somewhat compatible, existing gas boilers cannot costlessly and non-invasively burn hydrogen (hydrogen-ready boilers are required) or high concentrations of SNG. Similarly, older oil installations are not adapted to high biodiesel admixtures (FAME) due to the degradation of materials and filters. Assuming zero CAPEX for modernization artificially lowers the costs of the Gas Focus scenario (line 658), falsifying its supposed cost advantage over heat pump-based scenarios.

Contradiction between "high spatial resolution" and a uniform price for district heating (DH) (Lines 741-742. The main advantage of the work is supposedly its bottom-up, spatial modeling (hectare/building). However, the authors admit that "DH as an energy carrier is represented by a single average price applied uniformly across all networks." District heating is by definition hyperlocal – its production costs and transmission losses vary dramatically depending on building density and the heat source. The use of a single, averaged price for all of Germany completely undermines the conclusions about the "competitiveness" of district heating in specific building clusters. The low adoption of district heating in the model (below 30%) may be merely an artifact of adopting an unrealistic, averaged tariff, and not the result of actual boundary conditions.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have satisfactorily addressed my comments, and I have no further concerns; therefore, I recommend accepting the manuscript in its present form.