This model calculates the uplift in FCF and NPV for a fuel-retail station that offers CO2-offsets at the point of sale, alongside selling fuel. The rationale, and the different models that could be employed are outlined in our recent deep-dive research note.
In both models shown above, annual FCF can be uplifted by 15-30%, while fuel retail stations’ NPV can be uplifted by 15-25%, depending on the portion of consumer that purchase the carbon credits.
Gross profits from selling $50/ton carbon credits may be around 3x the typical EBIT margins of retail stations, hence we explore a particular sales model that can at least double fuel retail NPVs.
This model quantifies the economics and carbon-costs of a US-based forestry project, purchasing pasture, and converting it into forest-land over a 40-year period.
Our base case is for a 10% IRR at a $50/ton carbon price. You can stress test the economics by flexing land prices, capex, opex, growth rates, timber prices, pre-commercial thinning rates and other more granular details.
This model indicates the economics of a typical utility-scale solar project, as a function of a dozen economic inputs: capex costs per MW, power prices, solar insolation, panel efficienccy, curtailment, opex, DD&A, loan metrics and tax rates.
Our base case calculationsshow utility scale can be extremely economic on a standalone basis, with 10% levered returns achieved at 4-7c/kWh input prices.
However, it is interesting to note how quickly the economics deteriorate: by c3-5c/kWh in areas where solar penetration is already high; and by 5-7c/kWh in less sunny locations.
Molten Carbonate Fuel Cellscould be extremely promising, generating electrical power from natural gas as an input, while also capturing CO2 from industrial flue gases through an electrochemical process.
We model competitive economics can be achieved, under our base case assumptions, making it possible to retrofit units next to carbon-intensive industrial facilities, while also helping to power them.
Our full modelruns off 18 input variables, which you can flex, to stress test your own assumptions.
This model shows the full-cycle cost of storing a kWh of electricity, across ten different technologies that have been proposed to backstop renewables.
The model allows you to flex input assumptions, such as the costs of each battery, its useful life and the frequency of charge/discharge cycles.
Pumped storage currently screens as most economical for backstopping renewables, by a factor of 3x, under our base case assumptions.
Backstopping solar also looks about 3x easier than backstopping wind, as smaller batteries are needed, and costs are a function of system size.
Covered storage technologiesinclude pumped storage, compressed air storage, lithium ion batteries, redox flow batters, four other battery types, flywheels and ultra-capacitors.
This data-file models the economics of constructing a new fuel-cell power project, generating electricity from grey, blue or green hydrogen, based on technical papers and past projects around the industry.
A dozen input variables can be flexed in the model, to stress test economic sensitivity to: hydrogen prices, power prices, carbon price, distribution costs, conversion efficiency, capex costs, opex costs, utilization and tax rates.
Indicative inputs, and sensible ranges, are suggested for each of these input variables in the data-file.
Economics continue to look more challenged for hydrogen power, compared with simply decarbonizing or carbon offsettingnatural gas power. Our base case estimate is a 24c/kWh incentive price for blue hydrogen power.
This data-file models the economics of constructing a new gas-to-power project, using simple or combined cycle gas turbines, based on technical papers and past projects around the industry.
A dozen input variables can be flexed in the model, to stress test economic sensitivity to: gas prices, power prices, carbon price, gas distribution costs, conversion efficiency, capex costs, opex costs, utilization and tax rates.
Indicative inputs, and sensible ranges, are suggested for each of these input variables in the data-file.
Sensitivity to utilization rates is particularly interesting, as requisite power prices could be doubled if gas is marginalized as a ‘backup fuel’ to renewables; the model seems to support a role for gas in baseload generation.
This simple, illustrative modelfor an LNG project’s economics, facilitates stress-testing of economic assumptions, and their impact on IRRs and NPVs.
The InputsOutputs taballows you to flex key variables such as: LNG sales price, Capex/tpa, Opex/mcf, Utilization, Thermal Efficiency, LNG shipping distance, LNG tanker rates, and liquids cuts.
A base LNG case project is likely to earn a c7% real, unlevered IRR. The economics are most sensitive to gas pricing and capex; and somewhat less sensitive to the other variables.
This short model compares different options for decarbonising diesel, either by substituting it with renewable diesel, or by offsetting its CO2 with carbon credits from reforestation.
We conclude that offsetting the CO2of diesel fuel could cost 60-90% less than purchasing advanced biofuel, at current pricing. Economically justified premia for biofuels are calculated.
Please download the model to interrogate numbers and run your own scenarios. For more information on our input assumptions, please see our biofuels overview data-file.
We model the economics of powering an oil platform from shore, using cheap renewable power instead of traditional gas turbines. This can lower upstream CO2 emissions by 5-15kg/bbl, or on average, around 70%; for a base case cost of $50-100/ton.
Our numbersare derived from reviewing technical papers, plus ten prior projects (mostly in Norway), which are tabulated in the data-file, including capex figures (in $M and $/W) where disclosed.
The costs of CO2 abatementcan be flexed by varying inputs to the model, such as project size, gas prices, power prices and carbon prices.
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