Economic and policy requirements for the deployment of Power to Methane (P2M) for grid-scale energy management

Biological power to methane, where CO 2 and renewable H 2 are biologically converted to synthetic methane gas, could deliver strategic benefits including provision of a gaseous fuel that is compatible with existing infrastructure, increased energy security, a mechanism to recycle CO 2 to displace the extraction of fossil carbon, enabling the storage of renewable energy, and provision of a vector for transportation and storage of hydrogen. This study shows that the technology is currently economically viable under very limited conditions given current UK and EU policy and economic frameworks. Three key policy and economic modifications are needed for broader deployment; i) international emissions allowance schemes should be structured such that recycling of carbon gases are encouraged, ii) ready access to low cost of capital funding mechanisms for technologies that can deliver multiple energy and environmental benefits, and iii) revenue is generated from all value propositions which, in the case of Power to Methane, includes the service of enabling of long-term energy storage. This study indicates that minimum revenues of £ 2.50 ( € 2.80) / kWh to £ 10 ( € 11.30) / kWh for enabling energy storage would be sufficient to deliver positive Net Present Values given the conditions and assumptions made.


Background
International responses to mitigate climate change are currently focused on reducing reliance on fossil fuels and increasing the proportion of energy generated using renewable sources, predominantly using Intermittent Renewable Energy Sources (IRES) such as wind and solar PV.In 2020 renewable energy accounted for 37.5 % of electricity consumed across the EU with wind and solar contributing 36 % and 14 % of this total, respectively (European Commission, 2022a).Increasing proportions of IRES require additional grid flexibility such as large-scale energy storage to match supply/demand profiles (Brouwer et al., 2014, Golling et al., 2020, Salem, 2023).In the UK, during the period from March 2020 to July 2020 power grid balancing costs were £718 million, which is 39 % higher than the National Grid expected in this period (OFGEM, 2020).
Although technologies such as lithium-ion batteries are suitable for a number of applications on the power grid, they are not suitable for longer duration storage applications (Eriksson and Gray, 2017;Albertus et al., 2020).Storage technologies including redox flow batteries, sodium sulphur batteries, compressed air storage, hydrogen storage and synthetic natural gas may be technically capable of delivering large-scale, long-term energy storage (Azzuni and Breyer, 2018).However, long-term storage technologies face challenges in attracting the investment needed to commercialise, leading to delays in short to medium term deployment and subsequent delays in the roll out of the large increase in IRES generation needed by the mid-2030s (BEIS, 2022a).
In parallel, economies that have relied heavily on fossil natural gas to provide industrial and domestic heating (e.g.Germany, Italy, France, UK) are challenged with finding alternative fuels that can be developed and deployed at reasonable costs in relevant timescales.Whilst hydrogen infrastructure development is likely to meet some of this requirement in industrial and urban hubs (Terlouw et al., 2019), it is unlikely to meet all heat and fuel requirements.Trials for the addition of hydrogen to local gas networks are already underway (e.g.HyDeploy, H21 Leeds City Gate), however, infrastructure conversion costs incurred for addition of hydrogen at more than 20 % by volume are high (Sadler et al., 2017, Jaworski et al., 2020).Even with efforts to electrify heating through the use of technologies such as heat pumps, methane demand in the UK is expected to remain between 60 and 70 TWh per year until at least 2030 (BEIS, 2021) whilst in Germany demand for methane for power generation is set to increase from 53.37 TWh in 2015 to 141.06 TWh in 2050, largely as a result of the country's decision to halt all nuclear power generation (Bothe et al., 2018).Overall European gas demand between 2010 and 2030 had been predicted to increase from 5930 TWh to 6280 TWh (Honore, 2014) although recent EU initiatives such as "Fit for 55" and "REPowerEU" (European Commission, 2022b) have introduced more urgency to reduce fossil fuel use.Academic and industrial reviews indicate that biologically derived and synthesized methane will be required to play a major role in gas grid operations beyond 2050 (Speirs et al., 2018;Navigant, 2019;Sulewski et al., 2023), while providing significant support to the development of renewable energy storage infrastructure (Moioli and Schildhauer, 2023).A technology that enables renewable energy storage and delivers a gas synthesized from recycled CO 2 would, therefore, appear to have considerable relevance over the next several decades.

Current progress
The concept of "Power to Gas" (P2G) provides a potentially elegant solution whereby renewable electrical energy is converted to hydrogen gas through water electrolysis (Green Hydrogen).Several studies have established the potential for P2G technology to provide long term, seasonal storage capability e.g., Strbac et al. (2012), Blanco and Faaij (2018), Golling et al. (2017), Sterner and Stadler (2019).A complementary approach is Power to Methane (P2M) where part or all of the hydrogen gas produced is combined with a carbon source such as CO 2 and converted to a synthetic methane gas that is fully compatible with existing infrastructure and appliances, therefore significantly reducing the storage and transportation costs associated with a hydrogen only system.Several microbial species (hydrogenotrophic methanogens) have the ability to utilise hydrogen in combination with carbon dioxide to produce methane and water (Savvas et al., 2017;Rusmanis et al., 2019), as summarised in Eq. (1).
(1) Such biological P2M, or biomethanation processes are currently at research / early commercialisation stages and have the advantage over thermochemical systems of operating at low pressures (0-10 bar), low temperature (mesophilic or thermophilic), can operate on an intermittent basis, and can accommodate a number of contaminants in the gas feed.Coupling the process with carbon capture technologies deployed at larger CO 2 emitters such as thermal power plants, chemical plants and biological CO 2 producers including larger breweries and biogas plants (Collet et al., 2017;Hidalgo and Martín-Marroquín, 2020) therefore provides a route to recycling CO 2 whilst, at the same time, integrating the management of power and gas grids.IEA (2019b) states that the utilization of captured CO 2 has the potential to become part of a circular carbon economy, providing new opportunities to generate economic revenues in addition to the value in mitigating climate change.

Literature and motivation
Studies specifically focussing on the application of P2G or biomethanation to integrate power and gas grids indicate that even a limited deployment of P2G technologies could appreciably reduce future gas prices (Clegg and Mancarella, 2015;Ikäheimo et al., 2022) and provide carbon savings (Liu et al., 2019), therefore contributing towards the EU International Energy Strategy (European Commission, 2022b).As such these technologies are a potentially desirable feature of future energy infrastructures.However, within current economic and policy frameworks it is not straightforward to attach an economic value to the multiple benefits that biomethanation may bring.Determining the financial viability of premarket renewable energy and sustainable technologies is the subject of increasing amounts of research.However, it is a challenging area involving many uncertainties, with assumptions having a large impact on overall results (Centi et al., 2020;Barahmand and Eikeland, 2022), meaning that conclusions being fed through to industry and policy makers can be inconsistent.
To date, a common conclusion of techno-economic studies relating to P2G or biomethanation is that whilst some niche market applications may be cost competitive, e.g.vehicle fuel (Ajanovic and Haas, 2019) and oxygen production (Ding et al., 2021), uncertainties are large (Brynholf et al., 2022).Broader economic viability and widespread deployment of the technology is very challenging unless there is a change in existing policy frameworks and associated economic conditions (Gustafsson and Anderberg, 2020;Glenk and Reichelstein, 2019, Liu et al., 2017, Chiuta et al., 2016) and full economic value is attributed to all of the services delivered (Michailos et al., 2020;Morgenthaler et al., 2020).
Previous studies identified that decoupling the relationship between natural gas and electricity price (Lux et al., 2019) and the availability of low-cost electricity is critical to reducing Operational Expenditure (OPEX) (Vo et al., 2018;Welch et al., 2021;Grahn et al., 2022), with Michailos et al. (2020) identifying that electricity was the major operating cost (72 -86 % of OPEX) of P2G systems.Therefore, allowing for changes over time for both gas and electricity prices, as opposed to including fixed costs for these key variables would improve study conclusions.Deployment of grid scale P2G systems requires large up-front Capital Expenditure (CAPEX) largely associated with electrolyser costs (Devaraj et al., 2020;Michailos et al., 2020), and the cost of raising capital for emerging technologies can itself be significant (Steffen, 2020) and should also be considered in techno-economic studies.The link between policy and finance also provides uncertainty.For example, climate and energy policy makers assume that the market for renewable energy finance conforms with the efficiency market hypothesis, however, this is not the case (Hall et al., 2017), and regulatory risks such as changing subsidies, tax exemptions or policy can directly impact on revenues (Leisen et al., 2019).TEA's may also, therefore, seek to consider how future changes in policy may change value propositions and sources of revenue.
Therefore, to better understand the policy interventions that might contribute towards viability of biomethanation there is a requirement to undertake a techno-economic analysis for the deployment of biomethanation that incorporates i) revenues from a full range of value propositions associated with system functions, ii) system capital costs including cost of capital, and iii) operational costs and revenues that accommodate changes in value over time (e.g. of key variables such as electricity and gas prices), therefore reducing uncertainty and more accurately reflecting economic viability.
Various methods for undertaking techno-economic appraisals of emerging technologies have been presented including multidimensional models (Gustafsson and Anderberg, 2020), risk-based approaches (Gargalo et al., 2016), and a framework aligned with the ISO 14040 standards for life cycle assessments (Zimmermann et al., 2020).In general, all are attempting to effectively accommodate and clearly communicate the uncertainties associated with all aspects of undertaking early-stage techno-economic appraisals.The motivation for this study is therefore to provide a clearer indication of the economic viability of biomethanation, or the policy conditions required to achieve viability, by undertaking a techno-economic study where uncertainty has been accommodated as clearly as possible through following one of these methods.

Research aims and objectives
The aim of this study is therefore to undertake a techno-economic assessment (TEA) of the deployment of biological Power to Methane (P2M) technology and to use results to assess whether significant policy changes are required in order to achieve financial viability.The objectives of the study are to: V. Bendikova et al.
• Present the existing and emerging value propositions that P2M could deliver if integrated into energy grids and give an estimate of potential revenues associated with them, incorporating changes of value over time for key variables including electricity and gas prices.• To estimate capital, cost of capital and operating costs of the proposed systems, incorporating changes of value over time.• To determine what economic values could be attributed to value propositions that have not been previously considered in literature.• To suggest changes to policy frameworks that would improve the competitiveness of the technology given current economic conditions and frameworks.

Contribution
The study brings two novel aspects.Firstly, this study uses time variable data for major parameters including gas price, electricity price and carbon price, based on UK Government predictions within three broader economic scenarios (Reference conditions, low fossil fuel price conditions and high fossil fuel price conditions).Results therefore more accurately reflect the range of anticipated economic conditions compared to using static or linearly varying estimates for one or more of these parameters.Secondly, the study considers the contribution that power to methane could make to the future storage of renewable energy as a value proposition, therefore introducing a so far neglected additional revenue source into the economic assessment of the technology.
The structure of the economic evaluation is summarised in Fig. 1.Each element is described in detail in the Method section.

Method
The method applied follows as closely as is practicable that suggested by Zimmermann et al. (2020) whereby the techno-economic assessment is undertaken within a similar framework to Life Cycle Assessment.The overall structure of the economic analysis is described in Fig. 1.

The goal of the study
The overall goal of the study is to investigate the economic viability of integrating biological power to methane (biomethanation) technology into a regional or national power infrastructure to deliver several value propositions, and to indicate where policy and/or regulatory adjustments may be required to allow economic potential to be realised.The intended audiences for the study are advisors to energy policymakers and potential investors in the technology.Should these stakeholders consider that the value propositions that biomethanation could bring are desirable within a broader energy infrastructure, this study will assist with the evaluation of policy and regulatory adjustments required, and the risks and returns associated with the investments needed to deploy the technology.

Scope of the study 2.2.1. Nature of the system
The study assesses the economic performance of a biological power to methane (biomethanation) plant integrated within the UK energy Fig. 1.Summarised structure of the presented economic analysis.
V. Bendikova et al. system that establishes a linkage between power and gas grids.A detailed numeric evaluation of the technology itself is described in Patterson et al. (2017).A 5 MW (Nominal) electrolyser is considered to be the minimum size that could be reasonably replicated on a modular basis depending on feedstock availability and grid requirements on a local basis.This would produce approximately 2079 kg (23,125 m 3 ) of H 2 / day which would require approximately 12,014 kg CO 2 (6522 m 3 ) / day to biologically produce approximately 4075 kg (6028 m 3 ) / day of synthetic methane (e-methane).Operating parameters related to the biomethanation system are summarized in Supplementary Information 1 (SI1).
Many studies in this field only consider operating P2G or P2M systems that utilize excess or constrained renewable electricity (largely to capitalize on temporary low electricity prices).This study is based on connection to the power grid and the near-continuous operation of the system on the basis that economies will commonly be working towards a high proportion of RE supply, and that the majority of electricity input from grid connection will therefore be renewable.This approach is compliant with UK policy (Department for Transport, 2023) and EU Policy (European Union, 2018) for the production of renewable fuels where only the renewable electricity proportion within the grid attracts subsidy (discussed further in 2.2.4).The upcoming EU RED III is in final stages of revision and it is not yet clear what specific rules apply to P2G systems.The prospect of utilising very low-cost electricity, if available, is further explored as part of the Uncertainty Analysis (Section 2.4).

Description of investigated business cases
The economic analysis focuses on four Business Cases that reflect the technology's practical and economic potential in the context of current and future energy markets and relevant policy instruments.The system boundary of each Business Case is summarised in Fig. 2 (A-D).
Business Case 1 is considered relevant for large, centralised natural gas users with subsequent large CO 2 emissions, e.g., a gas fired power station.It is assumed that the biomethanation facility (including H 2 production) is owned and operated by a third-party company.Captured CO 2 is purchased from the industrial facility and combined with hydrogen from electrolysis to produce synthetic methane that is then utilised to partially meet the fuel demand within the same industrial facility (Fig. 2A), creating a closed loop circular system.Cash flow income for the biomethanation plant is the revenue from the sale of produced methane to the industrial plant and the sale of oxygen, the coproduct of the electrolysis process.Methane retuned to the industrial plant partially meets its energy requirement and displaces the requirement to purchase an equivalent amount of fossil methane.
Business Case 2 produces methane that is utilized as a vehicle fuel with two different points of sale.BC2.1 (Fig. 2B) includes utilization of Fig. 2. Biomethanation system boundary and end use Business Cases (BC) considered in the study.
V. Bendikova et al. compressed methane as vehicle fuel at the production site, where as BC2.2 (Fig. 2C) proposes that compressed methane is added to the gas grid for transmission to a vehicle refuelling facility.For both BC2.1 and BC2.2 revenue is generated from the sale of methane, sale of oxygen, and from sale of Renewable Transport Fuel Certificates (RTFCs), discussed further in Section 2.2.4.
Lastly, Business Case 3 produces methane that is compressed, added to the gas grid and utilized for space heating (Fig. 2D).Revenue sources are from the sale of methane and the sale of oxygen.No subsidy mechanism is included in this model.

Estimation of capital costs (CAPEX) and operating costs (OPEX)
The list of capital items and their respective estimated financial values (Gorre et al., 2019;Goulding et al., 2019;Michailos et al., 2021;IEA, 2020) included in calculations is provided in Supplementary Information 2 (SI2).Any salvage value was assumed to be fully offset by decommissioning costs and was therefore not considered.The list of Operational costs (OPEX) estimations is summarised in Table 1 and described in detail below.
Electricity is required to drive the electrolytic production of hydrogen and to operate the biomethanation plant (primarily for mixing and heating) and associated equipment.The UK industrial retail price for electricity (BEIS, 2020a(BEIS, , 2020b) is used within the economic modelling as an operational expenditure.To reduce model uncertainty as far as is practicable the electricity price included in the calculations varies annually according to predicted prices as described in the Scenario Description (Section 2.4.2).Year 1 values modelled are between £110 (€123.75)/ MWh for the Low Fossil Fuel Price Growth scenario and £127 (€142.88)/ MWh for the High Fossil Fuel Price Growth scenario, with Reference conditions having an electricity price of £117 (€131.63)/ MWh (Table 1).
A cost of £7.64 (€8.60) £/ m 3 for deionised water has been included (Michailos et al., 2020).The modelled system required an input of approximately 30,353.4m 3 of water per year.
Stack Replacement is anticipated to be required approximately every 10 years.As such, one stack replacement is included within the 20-year project timeframe.A stack cost of £545.3 / kW (€613.82/ kW) is included based on IEA (2020) expectations that PEM electrolyser costs will reduce due to technology innovations and by economies of scale.
An allowance of 2 % of CAPEX has been made for the provision of labour, general plant maintenance and insurance.

Estimation of revenues
The UK industrial retail price for natural gas (BEIS, 2020a(BEIS, , 2020b) is used as a proxy for the sale price of synthetic e-methane produced at the biomethanation plant.This provides revenue in all Business Cases as the gas is sold to third parties for end use.The value included in the calculations varies annually according to predicted natural gas prices as described in the Scenario Description (2.4.2), however, Year 1 values modelled are between £ 15 (€16.88)/ MWh (Low Fossil Fuel Price Growth Scenario) and £ 30 (€33.75) / MWh (High Fossil Fuel Price Growth Scenario) with Reference conditions including a gas price of £ 21 (€23.62)/ MWh (Table 1).In the case of business cases BC1 and BC3 that produce e-methane for heat, no incentives were applied to the economic model.
Business cases BC2.1 and BC2.2 that produce e-methane as a vehicle fuel incorporate income from the sale of Renewable Transport Fuel Certificates (RTFCs) which can be claimed and traded under the Renewable Transport Fuel Obligation scheme (RTFO) in the UK.Methane receives 1.9 RTFC per kg.Additionally, it is assumed that produced e-methane derived from captured waste CO 2 and renewable energy would be categorised as a Renewable Fuel of Non-Biological Origins (RFNBO) within the RTFO and would therefore be eligible for double reward (3.8 RTFCs) per kilogram of supplied e-methane (Department of Transport, 2021).In the model only e-methane produced from the proportion of estimated RE in the grid (which is utilised to operate the biomethanation system including electrolysers) contributes to the revenue from RTFCs.Eq. 2 depicts the method of calculating the number of RTFCs per kilogram of e-methane per year: where M is a volume of e-methane per year in kg, 3.8 is a multiplier (Department of Transport, 2023), RE ratio is the predicted ratio of Renewable electricity in the grid per year (BEIS, 2022).The maximum buyout price (i.e. the maximum value that RTFCs will achieve) is set at £0.5 (€0.56) / RTFC (£0.8 (€0.89) / RTFC for development fuels), however, a conservative market value of £0.35 (€0.39) per RTFC has been assumed in this study.
Oxygen is produced as a co-product of hydrogen via the electrolysis of water.At multi megawatt scale oxygen is produced in masses where its recovery and use should be economically viable.Co-location of biomethanation systems in industrial hubs where oxygen could be utilised in industrial processes such as oxy-combustion or enhanced aerobic wastewater treatment would provide direct markets for oxygen.Literature values for revenues from sale of oxygen vary greatly from £44.40 / t (€50 / t) (Rosenfeld et al., 2020), £71.10 / t (€80 / t) (Breyer et al., 2015) to £133.30/ t (€150 / t) (Guilera et al., 2018).In the case of this study a relatively conservative value of £70 (€78.75)/ t in line with other power to gas studies (Michailos et al., 2020) has been used.In business models BC2.2 and BC3 where gas is exported to the gas grid, an additional value proposition arises.As the system provides a change of energy vector (from power to gas) it enables long term (seasonal) storage of surplus RE as synthetic gas in the national gas grid or in associated gas storage facilities.Market mechanisms for medium to long term energy storage are still under development and there is no clear indication of potential revenues specifically relating to the potential to store energy via power to gas routes.In Section 3.3 this study separately investigates the magnitude of revenues that would need to be generated from providing the service of changing energy vector / enabling energy storage so as to achieve economic viability, as defined in Section 2.3.

Consideration of carbon dioxide within the model
Availability of CO 2 is a potential market limitation.CO 2 is both a potential operational cost where CO 2 may have to be purchased from an industrial facility, and a potential source of revenue as the biomethanation operator could charge the industrial facility for the disposal / recycling of the CO 2 .The following paragraphs describe the approach taken to integrate this complexity into the model.
Capturing CO 2 represents a cost to the CO 2 producer, reflecting the investment and operating costs of carbon capture technology.All Business Case models assume that the biomethanation plant operator incurs costs associated with purchasing the CO 2 feedstock.Carbon pricing, an instrument that captures the external costs of GHG emissions, can act as an incentive to capture CO 2 and use it (or sell it for use) in the manufacture of products or services, provided this is the cheapest compliance strategy for the emitter.Carbon pricing systems are currently operating in different regions; however, in most cases, the carbon price is currently too low to support the deployment of relatively nascent technologies, including CO 2 use applications.Furthermore, the cost of using captured CO 2 as a feedstock for products or services is often too high relative to other compliance strategies, such as CO 2 storage or simply paying the carbon allowance price.Therefore, to reflect the minimum price at which carbon utilisation may compete with other compliance strategies, this study includes a purchase price of captured CO 2 of £47 (€52.88)/ t CO 2 , which is equal to the minimum selling price to cover levelized carbon capture costs derived from a relatively mature post-combustion carbon capture technology such as liquid absorption (IEA, 2019a).No further consideration of the CO 2 generating industrial process is required.This CO 2 purchase price is static over the modelled timeframe (20 years).
Having purchased CO 2 from the producer at a cost equivalent to the levelized cost of carbon capture, the presented research then applies the "polluter pays" principle and includes a gate fee for the treatment of the CO 2 at the biomethanation facility.For the purposes of this study this "Gate Fee" value is set as equivalent to the predicted EU emissions allowance price which, in Year 1 of the model has a value of £42.70 (€46.50)/ tCO 2 , increasing annually to £52.80 (€59.40)/tCO 2 by year 20 (BEIS, 2020a(BEIS, , 2020b)).This study assumes that in all Business Cases equivalent savings on avoided carbon emission allowances can be realised on captured and recycled CO 2 , therefore providing an economic incentive for CO 2 producers to recycle their waste gas.It should be noted that in the EU this assumed position relating to carbon emission savings would require some policy adjustment.At present, emission allowances are accrued on surplus carbon leaving a facility via any route, not just carbon that is emitted to atmosphere.Under the existing framework surplus carbon producers would therefore be subject to carbon capture costs, carbon allowance costs, plus any costs associated with the disposal of the carbon (whether it be storage or recycling to other uses).There may be little incentive to undertake carbon recycling since CO 2 utilization is currently not considered a primary driver for industrial carbon capture in the UK (BEIS, 2018), in addition to the low market value of carbon emission allowances.A policy adjustment where carbon allowance liabilities are incurred at the point of emission to atmosphere (or as close as is practicable to it where emissions are distributed, such as domestic boilers), and not where carbon is being made available for recycling or long-term storage should be considered.
Table 1 summarises specific costs, revenues and/or savings associated with each Business Case.

Basis for economic assessment
The profitability criterion was chosen to analyse viability of projects.The economic viability of proposed business models was calculated via a dynamic Excel model based on the Net Present Value method (NPV) as an indicator of profitability.The foundation of the NPV model is outlined in Eq. 3 and consists of the sum of future net cash flows over the project's lifetime, discounted to its present value.The investment decision will be economically feasible if projects have positive or zero NPV, considering chosen assumptions.
where NPV is the net present value of the project, R t is net cash flow for each year, n is the number of years, i is the discount rate and t is time in years.
Levelized Cost of Methane (LCOM) (Eq.4) was also calculated and indicates the lifetime unit cost of produced methane, hence enabling comparison of alternative Business Cases.LCOM reflects a minimum required retail price at which methane can be sold for a project to break even.

MWh of methane produced in year n
(1 + i) t (4) where c is the costs in each year, t is the number of years and i is the discount rate.
In addition, to determine the impact of policy (i.e., RTFCs and carbon "gate fee") and of additional revenue from co-products, these cashflows are deducted from LCOM results to reflect the cost of e-methane thus quantifying an Average Minimal Selling Price (AMSP) of produced gas.

Discount rate estimate
The discount rate is a fundamental driver in making investment decisions in the private sector.The final discount rate is affected by several factors such as risk profile of the project and the time value of money.It is often company's Weighted Cost of Capital (WACC) that is set as a proxy for a discount rate.However, for emerging renewable energy technologies data on finance structures and expected rates of return are very limited (Steffen, 2020).Given this lack of empirical data the detailed calculation of WACC is omitted from this study.Instead, a discount rate of 10 % is assumed based on the UK national average WACC of 8 % (Grantthornton, 2019) and 2 % added risk premium due to the higher-risk investment profile of a project involving new technologies and markets.

Uncertainty analysis
Uncertainties associated with data and assumptions included in the calculations are substantial due to the novel nature of the technology, its limited industrial track record, and temporal variations in future market conditions (e.g.energy prices).An uncertainty analysis is used to help generate an understanding of uncertainty in input data, financial assumptions, and state of technology development (Van Der Spek et al., 2020) and the effect that these may have on results.For this study a two-tier uncertainty analysis was employed as indicated in Fig. 1.Firstly, a one-way sensitivity analysis was completed (described further in Section 2.4.1) which gives an indication of the level of influence that an individual model parameter has on the calculated NPV result.Secondly, an economic scenario analysis was completed (described further in Section 2.4.2) where several economic parameters are varied at the same time, thus giving an indication of the impact of wholly different economic conditions on calculated NPV.

One-way sensitivity analysis
A one-way sensitivity analysis was applied where one model parameter was varied at a time under the assumption of the independence of remaining parameters, with the aim of establishing the models' sensitivity to changes in each parameter.Costs for CAPEX, electricity, purchased carbon dioxide and water, revenues from e-methane, carbon dioxide "gate fee", oxygen and RTFCs, and the discount rate applied were all varied individually between − 50 % to +50 % of the Reference values and the subsequent change in NPV calculated.This allowed the identification of input parameters that have the largest influence on the result (calculated NPV) and can inform the requirement to strengthen model certainties by seeking more accurate data for key model inputs, or further understand the effect of the uncertainty via a scenario analysis.

Availability of low-cost renewable electricity.
The potential impact of the future availability of very low-cost electricity on the viability of the biomethanation process was separately investigated by the inclusion of a scenario where all electricity driving the electrolysis and biomethanation process was sourced from low cost wind turbine generation.To realise the lowest possible electricity price that can be consistently delivered (i.e.not based on temporary excess electricity availability), it was assumed that the renewable generating facilities were owned and operated by the same entity that operates the biomethanation facility and electricity was therefore provided at a production cost of £0.02 / kWh (€0.023 / kWh) (Irena, 2020).

Economic scenario analysis
As the second tier of the sensitivity analysis an economic scenario analysis was included to assess the effect of changing multiple input variables simultaneously.The model parameters i) Purchase price of electricity, ii) the sale price of e-methane and iii) "gate fee" charges for treatment of CO 2 were adjusted using the proxy values of the predicted variations in i) retail electricity prices for industry, ii) retail natural gas prices for industry, and iii) carbon prices for the UK electricity supply sector, respectively, as described by BEIS (UK Government) in their Energy and Emissions predictions (BEIS, 2020a(BEIS, , 2020b)).As such the analysis incorporated changes in value over time for these model parameters.In order to account for a degree of uncertainty in electricity, gas and carbon prices the BEIS projections include three Scenarios; (i) Referencebased on central estimates of economic growth and Fossil Fuel (FF) price changes, taking into account the impact of planned UK policies, (ii) Low Fossil Fuel (FF) Price Growthas per the Reference scenario but taking into account the impact of lower FF prices, and (iii) High FF Price Growthas per the Reference scenario but taking into account the impact of higher than expected FF prices, each including annual growth variations for electricity, natural gas and carbon prices.These annual changes in prices for the three parameters (electricity, gas and carbon prices) are then simultaneously included in the economic calculations to provide the most accurate representation of anticipated economic conditions possible (as opposed to static or linearly changing data for each parameter).Year 1 values for electricity, natural gas and carbon for each Scenario are shown in Table 1 and the changes in the values for the parameters are visualised in Supplementary Information 3 (SI3).

CAPEX and OPEX
Fig. 3 shows the itemized breakdown of initial capital expenditure (CAPEX).Because electrolyser and biomethanation infrastructures are the same for each Business Case, the only variance in CAPEX costs is a result of post-production / end use equipment.Fig. 4 shows the itemized OPEX breakdown by BC in Year 1 under reference economic conditions.First year total annual OPEX ranges from £ 6.59 million (€7.41 million) for BC1 to £ 6.74 million (€7.58 million) for BC2.1.As has been identified in other studies, the amount of electricity required to produce hydrogen via electrolysis and the cost per unit of electricity jointly contribute to highest proportion (approximately 90 %) of total OPEX.BC1 indicates marginally lower OPEX than remaining BCs due to a lower gas compression requirement (as limited storage or transport of gas is required).

Revenue and savings analysis
Fig. 5 summarizes sources of cash inflows in the form of revenues, savings and incentives for each Business Case (BC).
BC1 and BC3 produce e-methane utilised for heat generation with an estimated market value of £ 481,902 (€542,140) in a Year 1 that represents a cost saving opportunity in BC1 and revenue for BC3.Substantial revenue of £ 393,218 (€442,370) per year arises in both models from sale of Oxygen.Furthermore, estimated Carbon 'gate fee' revenue of £ 187,085 (€210,47) in Year 1 accounts for approximately 20 % of total cash inflows for BC1 and BC3.
BCs utilizing e-methane as a vehicle fuel, BC2.1 and BC2.2, demonstrate notably different revenue profiles from BC1 and BC3.Based on the assumption that the e-methane manufactured from the proportion of hydrogen generated using renewable electricity in the UK grid mix would qualify for RTFCs, revenue from the sale of RTFCs becomes dominant and accounts for around 44 % of the total.Sale of e-methane, assuming a cost equivalent to natural gas, accounts for 25 % of revenue.As a consequence, the significance of the revenue generated from carbon treatment 'gate fee' is lower at approximately 10 % for BC2.1 and BC2.2.
The NPV results for each Business Case are presented in Fig. 6.This shows that for all Business Cases, regardless of end use of the e-methane, when electricity at industrial retail price is used and Reference economic conditions are applied, the NPVs are negative and therefore, based on the assessment criterion described in the Methodology, are not economically viable.
Levelized Cost of e-methane (i.e., cost of supplying synthetic methane to the market) ranges from £ 355-372 / MWh (Fig. 7).Fig. 7 also depicts the contribution of the revenue / savings of carbon 'gate fee', oxygen sales and RTFCs to the Levelized Cost of e-methane for all BCs under Reference economic conditions.On average, subtracting the carbon 'gate fee' lowers LCOM by 2.5 % indicating the minor effect that carbon pricing as a market-based policy instrument currently has on technology LCOM.On the other hand, for business cases BC2.1 and BC2.2, subtracting revenue from the sale of RTFCs decreases LCOMs by 22.6 % and 22.4 %, respectively hence indicating the significant importance and market reliance on the RTFO policy scheme.Subtracting revenue raised from the sale of Oxygen decreases LCOMs in all business cases by average of 5 %.

Sensitivity analysis
A one-way sensitivity analysis for all for business cases was completed.The effect of varying the value of each parameter (CAPEX, Electricity Price, Price of Captured Carbon, etc) by +/-50 %, (x axis) on the NPV results (y axis) for each of the four Business Cases is illustrated in Fig. 8 (A-D).Each model parameter is represented by a line on the graphs.Parameters that exhibit steeper gradients have more influence over the calculated NPV than those with less steep gradients.
For all investigated BCs electricity price has the steepest gradient and therefore ranks as the most dominant model parameter impacting on the calculated NPV.For example, Fig. 8A shows that for Business Case 1 a 50 % reduction in electricity price increases the NPV by 45.5 %.Whilst it is not possible to fully predict long term variations in electricity prices, governments do undertake a degree of predictive modelling of energy prices in order to inform current and future policy decisions.In this study Reference condition NPV results (Fig. 6) include time variable  predicted electricity prices published by BEIS according to their Reference economic conditions, and therefore represent a concerted effort to reduce uncertainty as far as is practicable.The effect of deviating away from this Reference economic condition is further investigated in the Scenario Analysis.
Sensitivity analysis results also show that the applied discount rate, a typical market factor, also has a significant impact on the NPV.For example, Fig. 8A shows that for Business Case 1 a 50 % reduction in the discount rate results in a 29 % change in NPV.The trend is the reverse of what may normally be expected (i.e. a higher discount rate results in a higher NPV) due to the effect of calculating NPV using negative cashflows, as reported in Cifuentes (2016).Although not specifically calculated in this study (due to lack of empirical data), the discount rate can be considered as being closely linked to the cost of capital which in itself can vary significantly depending on the finance mechanism available.Project finance structures with higher equity to debt ratio have generally higher cost of capital reflecting risk tolerance by different types of investors.Based on this result access to lower cost financial mechanisms is likely to greatly enhance the financial viability of early market renewable technologies.
In all business cases the variation of CAPEX had the next largest impact on NPV.Potential reduction in capital costs, particularly for electrolysers, could therefore significantly improve financial viability in the future.For business cases based around the provision of vehicle fuel (BC2.1,Fig. 8B and BC2.2, Fig. 8C) the value of the RTFC also had an appreciable effect on NPV.This highlights the importance of having a stable and relatively predictable subsidy mechanism to encourage investment in high capital, innovative technologies.

The impact of very low electricity prices
Previous results identify electricity costs as the parameter with the highest contribution towards total OPEX and contributes the greatest uncertainty to NPV.Therefore, further investigation was conducted under the assumption that using captive renewable electricity produced by the same organisation that owns / operates the biomethanation system would limit exposure to market price variations and allow electricity to be supplied at production cost of £0.02 / kWh (€0.023 / kWh).Fig. 9 depicts model NPV results for all BCs with captive electricity production under Reference economic conditions.Fig. 9 shows that although BC1and BC3 still have a negative NPVs and are therefore still considered to be economically non-viable, they are considerably closer to zero than those that included grid-based electricity at standard industrial cost.BC2.1 and BC2.2, where emethane is utilized as a vehicle fuel, reach positive NPV of £6,853,703 (€7,710,416) and £6,966,913 (€7,837,777) as a result of lower OPEX and an increase in the RTFC qualifying product to 100 % (as all energy utilised is renewable), therefore achieving positive economic viability.

Economic scenario analysis
An economic scenario analysis where three model variables; i) electricity price, ii) natural gas price (as a proxy for e-methane market price) and iii) EU Carbon Allowance price, are simultaneously varied was completed.Table 2 provides a summary of key economic indicators (NPV, LCOM and AMSP) for all Business Cases under different economic scenarios (Reference FF Price, Low FF Price and High FF Price) based on the expected economic growth and price of fossil fuel as defined in BEIS (2020a) (2020b).Both industrial price grid electricity and very low-cost captive electricity are also considered.
NPV results for all Business Cases and Economic Scenarios using grid electricity have negative values indicating that all options remain economically non-viable based on the assumptions made.Where captive, very low-cost renewable electricity (wind) is utilised to power the process a large increase in NPV can be seen, although NPVs for nonvehicle fuel (i.e.unsubsidised) end uses remain negative.Vehicle fuel utilisation cases BC2.1 and BC2.2 have positive NPVs under all economic conditions, suggesting that under these relatively limited set of conditions the system might be attractive to investors.
Furthermore, the required AMSP of e-methane to break-even after revenue for sale of oxygen, carbon "gate fee" and deduction of relevant subsidies, was calculated.For cases that utilise standard industrial cost grid electricity the AMSP ranges from £ 247 / MWh (€278 / MWh) (BC2.2Low FF Price scenario) to £ 357 / MWh (€402 / MWh) (BC3 High FF Price scenario), which are between 10 and 15 times higher than the average price of UK natural gas in 2020 of £ 23 (€25.8)/ MWh (BEIS, 2022b).Average wholesale gas prices in the UK in 2021 were approximately £ 51 (€57.4)/ MWh although in early 2022 wholesale prices had increased to a maximum of over £ 100 (€112.5)/ MWh (Intercontinental Exchange, 2021).Results suggest that lower costs or additional revenue are required to allow the investigated technology to compete based on recent market conditions.
Where business cases utilise very low-cost captive renewable electricity sources the AMSPs range from £ 98 (€110) /MWh for BC1 to £ 101 (€114) / MWh) for BC3.Positive NPVs for production of vehicle fuel mean that AMSPs are < 0 (i.e.sale of gas adds to profit).As per the NPV values, this suggests that under very limited market conditions (i.e.availability of very low cost electricity) the technology may be approaching economic viability based on the assumptions made in this study.
Based on the above analysis it is evident that the sale of oxygen and emethane, even including an incentive for vehicle fuel use, are unlikely to be sufficient to warrant a decision to invest unless electricity is available at cost price or lower on a consistent basis.Higher carbon prices alone are also unlikely to radically change the economic viability of the process, although may serve as an incentive for CO 2 producers to explore recycling routes.However, when configured as described in this study, the technology also delivers services to the energy sector including grid synchronisation and the provision of contingency and flexibility reserves.Commercial agreements with power grid operators for provision of grid services have traditionally been on a relatively short-term basis with income generated being unpredictable, and therefore may not dramatically increase the overall financial viability of the technology.
However, the provision of energy storage services has the potential to provide a consistent and predictable long-term income.Power to gas / biomethanation as described in this study is a technology that enables the storage of renewable energy as methane gas.This can be readily stored at a range of pressures, and many countries have well developed methane (natural gas) distribution systems.In addition to the direct use of synthetic methane in the short to medium term, synthetic methane may in the future also represent an efficient vector for storing and transporting renewable hydrogen on a regional basis.The following section therefore investigates the potential for including the enabling of renewable energy storage into the biomethanation business plan and its potential impact on financial viability.

Potential effect of energy storage on economic assessment and policy proposal
BC2.1 (gas to grid for vehicle fuel production) and BC3 (gas to grid for heating purposes) are both connected to the gas grid network and therefore can enable regional or national energy storage.Two variables, i) energy storage service fee (or the service fee for changing the energy vector), and ii) the percentage of e-methane produced that qualifies for energy storage, were varied until a positive NPV was achieved, therefore Fig. 9. Summary of NPV model results for all BCs with on-site generated renewable wind electricity under Reference economic conditions.
V. Bendikova et al. giving an indication of the minimum values for these variables that would deliver economic viability under Reference economic conditions, based on connection to grid electricity (i.e.industrial cost electricity).The energy storage service fee considered ranged from £ 2.50 / kWh (€ 2.80 / kWh) to £ 25 / kWh (€28.12 / kWh).At the time of writing no clear regulatory framework relating to the eligibility of the technology for future energy storage payments exists.Variables such as the percentage of renewable electricity being utilised and the origin of CO 2 are likely to play a role in any future framework, however, the details are not known.As such relatively low volumes ranging from 2.5 % to 15 % of total output were considered as qualifying for energy storage income.
Table 3 shows the combinations of energy storage charge and percentage of eligible product gas that achieves a positive NPV for BC2.1 based on the use of grid (industrial cost) electricity and reference economic conditions.To reach positive NPV a minimum of 2.5 % of the total e-methane output would need to qualify for energy storage with a minimum charge of £ 10 / kWh (€11.30/ kWh).Alternatively, £ 2.50 / kWh (€2.80 / kWh) represents the minimum energy storage service charge when a minimum volume of 10 % of the total e-methane output qualifies as achieving energy storage.
Results for BC3 (Table 4) indicate that to reach positive NPV the minimum required revenue for energy storage service is £ 2.50 / kWh (€2.80/ kWh) with 12.5 % of e-methane output qualifying as achieving energy storage.The minimum required volume of e-methane qualifying as delivering energy storage service for a positive NPV would be 2.5 % at a minimum charge of £ 12.50 / kWh (€14.10 / kWh).
The above results indicate that biomethanation of renewable hydrogen and CO 2 to produce methane gas could be financially viable providing that value is attached to the service of enabling energy storage.A value in the order of £ 2.5-12.5 / kWh (€2.80 -14.10 / kWh) appears to be the threshold for delivering positive NPVs based on the conditions modelled and assumptions made.This would only represent part of the cost attributable to energy storage using P2M (or P2G) as investment in gas grid connected storage facilities would be required to  provide capacity to store gas for time periods of weeks or months.Quantification of these additional gas grid costs associated with building and operating this storage capacity is not within the scope of this study.
It is noted that costs for battery storage of electricity have been estimated to be US$143 -US$248 / kWh in 2030 (Cole et al., 2021) and that revenue from provision of fast reserves in the UK range from approximately £ 50 -£ 70 / kWh based on UK National Grid market data (Regen, 2019).This suggests that there is economic scope for power to methane, coupled with investment to increase gas grid connected methane storage facilities, to compete with other energy storage technologies and potentially feature as part of a future integrated energy network.

Conclusion and policy implications
Biomethanation can deliver strategic benefits including production of a synthetic methane to increase energy security, a mechanism to recycle CO 2 therefore displacing extraction of additional fossil carbon, integration of power and gas grids, the potential to store renewable energy as a gas, and the provision of a low cost hydrogen carrier.Based on the economic evaluation presented, the following conclusions can be made: 1. Power to methane is economically viable in current market conditions where electricity can be provided at production cost of £0.02 / kWh (€0.023 / kWh) and where produced methane is utilised as a vehicle fuel (therefore attracting Renewable Transport Fuel subsidy).2. Cost of capital has a significant impact on the overall viability (NPV) of the system.Measures to encourage access to low-cost finance for early to market technologies that are capable of delivering strategic benefits should be available to encourage investment in these technologies.3. Biomethanation changes the energy vector from power to a gas, therefore linking power and gas grids in a way that enables storage of renewable energy.Policy development is required to enable value to be attributed to this service.Under the conditions modelled and assumptions made, this study suggests that values of £2.50 -12.50 / (€2.80 -14.10) / kWh would be sufficient to achieve positive NPVs even where only 2.5 -15 % of e-methane qualifies as stored renewable energy, retail electricity prices are considered and no other subsidy is included (BC3).Gaining value for this service would transform the economic viability of P2G technologies.
4. Changes to the carbon market are required to encourage the efficient re-use of CO 2 .At present there is little / no economic benefit for CO 2 producers to export their CO 2 for re-use as exported carbon still incurs emission allowance costs.Emission penalties should be payable where carbon is released to atmosphere (or as close as is practicable for distributed emissions), not where carbon is recovered and recycled.This is key to establishing a global carbon management system.The long term ability for recovered CO 2 to qualify as a recycled product within policy is also required.
Whilst it is not feasible to predict or test all potential scenarios, further methodological improvements are possible to reduce uncertainty and improve accuracy.Access to more contemporary data, particularly for CAPEX and OPEX, would improve accuracy, and uncertainty analysis could be streamlined by making more use of statistical methods similar to Monte Carlo analysis.For technologies that deliver multiple and circular products and services such as CO 2 recycling, development or incorporation of more suitable indicators (e.g.storage characteristics, number of cycles achievable) may complement traditional measures such as NPV.Finally, communication of uncertainty in results in technoeconomic type studies needs universal improvement, and if possible, standardisation.

Funding information
The authors acknowledge that this study has been produced by them independently of funding support.The content of the study is not a reflection of the viewpoint of organisations that have contributed funding.Funding support for the completion of this study was provided by: European Regional Development Funding (ERDF) as administered by the Welsh Government SMART Expertise Programme through the SMART Circle project (Reference: 122016/COL/003) led by the University of South Wales.
European Regional Development Funding (ERDF) as administered by the Welsh European Funding Office (WEFO) through the Beacon Plus project (Reference: c80851).
Department for Business, Energy and Industrial Strategy (BEIS), Energy Storage Cost Reduction Competition, Biological Integration of Electricity and Gas Grids for Low Cost Energy Storage, Project Reference CR201.

Fig. 5 .
Fig. 5. Itemised streams of sources of Revenues and / or Costs savings in a Year 1 by BC.

Fig. 6 .
Fig. 6.NPV results for all BCs under Reference economic conditions.

Fig. 7 .
Fig. 7. Cumulative effect of carbon gate fee/ savings, revenue from Oxygen, and RTFCs on LCOMs by BC.

Fig. 8 .
Fig. 8. One-Way Sensitivity Analysis for each Business Case showing the magnitude of change in NPV as each model input is varied individually between +/-50 % of Reference value.

Table 1
Model Parameters including OPEX and Revenues / Savings per Economic Scenario.
Note: a Prices vary annually according to the Scenario (BEIS, 2020a, 2020b).Refer to Supplementary Information 3 for a visualisation of how these variables change V.Bendikova et al.

Table 2
Key economic indicators for alternative business cases under different economic scenarios.

Table 3
Effect of energy storage service by volume and price on NPV -Scenario analysed: BC2.1, grid electricity, Reference economic condition.

Table 4
Effect of energy storage service by volume and price on NPV -Scenario analysed: BC3, grid electricity, Reference economic condition.