Scoping parameterisation of energy transition options AND of the reasons for wanting one: PART 2 of 2

CONTENTS:

PART 1: A cheeky aim;????? An energy transition in six sections and 60 numbers?;????? Introducing the sections;????? SECTION A – Option priorities;????? SECTION B – Option Considerations;????? Costs;????? Energy Storage;????? Energy Distribution;????? Electrification;????? The stubborn third;????? Steel;????? Cement;????? Meat;????? Shipping;????? Aviation;????? Recycling;????? Scale and materiality;????? Scalability issues – the CCS example;????? Technical readiness levels;?????

PART 2: SECTION 1: Demand Reduction DRd;????? SECTION 2: Renewables Rnw (plus related energy storage, long distance distribution, recycling & demand management);????? SECTION 3: Nuclear Nuc (plus energy storage, plus long distance distribution, plus FNR reprocessing plus geological repositories, plus security, insurance and decommissioning);????? SECTION 4 CCS (New energy projects with geological carbon capture or DAC and a component of uncaptured scope-1 emissions);????? Health warning;????? Having a go – first stab straw man;????? Summary;????? References

Continued from Part 1: https://www.dhirubhai.net/pulse/scoping-parameterisation-energy-transition-options-reasons-waters-esype%3FtrackingId=R1dooqZzQzmhEzhve6c6KA%253D%253D/?trackingId=R1dooqZzQzmhEzhve6c6KA%3D%3D

PART 2:

SECTION 1: Demand Reduction DRd

So now we move from the wide ranging (and far from exhaustive) overview of selected key concepts relevant to an energy transition, and on to how we engage in high-level parameterising of the four most often proposed key routes for fossil fuel downshift – demand reduction, renewables with storage, nuclear, and fossil energy with carbon capture. ?We begin this parameterisation exercise with demand reduction (DRd), as shown in Figure 31.

We recall that as per Figure 2, we begin with some level of primary energy demand “SQ” the status quo empowered by fossil fuels. In Figure 31 we define “W” – a “cost” of implementing demand reduction, of which some key approaches are listed in the figure and discussed in previous sections pertaining to section “B” in Figure 3.? That cost being something that encompasses financial, environmental, and socials costs, recognising that to do so is hard – but assuming for a minute that some consistent method of doing so across all the energy routes is possible.?

So we would include, for example, the costs of national grid updates to facilitate electrification, costs of improving energy efficiencies of things everywhere, costs of new electric rail construction, the costs of cycleways and associated interconnectivities, the installation and associated disruption costs of new district heating networks.? Also things like the development of longer lasting products, and recycling pathways, new urban, residential, and commercial developments that are less private car-centric, and so on.?? All these things helping to reduce energy demand but having a very real cost.?? Clearly it is difficult to amalgamate so many different costs under one category and variable, and some routes will be more expensive than others – but various “scenario” sensitivities can be explored.

The next parameter we define is “D”, which is the chance demand reduction can meet all of the remaining primary energy demand after demand reduction has been achieved – i.e. SQ-DRd.?? This is a bit of a nonsense, as we know that as long as there are humans on the planet, there will be some demand for energy and demand deduction will never reduce it to zero.?? As long as humanity persists then, the chance of D is zero percent, but we retain it here for consistency with the other energy routes. The concept of “SQ-DRd” is however an important one we will return to – as it captures the sense that demand reduction will inevitably form a key part of any energy transition – to different degrees in different places assuredly, but important at infrastructure levels everywhere.? ?That means the energy demand we are looking to meet with all other routes is no longer SQ, but this quantity, “SQ-DRd”.

Note that to simplify things and avoid a need for totalling up in absolute terms the value of SQ or DRd, we can undertake a scoping exercise that sets SQ to some arbitrary initial value such as 100 and estimate the values of DRd (and also Rnw, Nuc, and CCS) relative to that initial value.?

The next parameter we consider is “d”.? This is in contrast to big “D”, rather the chance that demand reduction can meet 10% or more of SQ.?? This is our effort to catch “scalability”.? We are interested in capturing the probability that a given route – in this case DRd, can contribute to downshift of the fossil fuel SQ to levels that are approaching something substantial and meaningful.?

Parameter “E” is a variant of parameter “D” – the chance of wholly meeting SQ via the chosen route, after any demand reduction, but adding a dimension of timescale.? That timescale is set as two half-lives as defined in the half-life parameter “δ” of Figure 2.? As however “D” is 0% for demand reduction, so too is it 0% for “E”.? That is to say, short of human extinction, demand reduction will not on any timescale ever totally replace energy demand.

The next three variables relate to cost, starting with “F”.? Again, these are probabilities.? “F” is the chance that demand reduction routes in all their diversity, with cost “W” will form the cheapest route to downshift fossil fuel use and attacking “SQ”, compared to the other routes, with equivalent costs “X” for Rnw (renewables plus storage), “Y” for Nuc (nuclear), and “Z” for CCS.? Bearing in mind this incorporates not just the financial costs, but the environmental and social costs, however they are captured in an analysis.?? There is also implicit in any estimate of cost an element of timescale, which when required can again be considered by default as two half-lives or 2δ, but it is possible to propose any desired timescale here as long as it is applied consistently for all the routes.?

The reason we want to know this, is that for any of the routes, where the chance of any one route meeting SQ-DRd is not 100%, there will by implication be at least two routes involved for attacking SQ, and to help decide which routes have priority, it will be in the first assessment a case of focussing on doing the cheapest ones first. So this is where the variable “F” helps us decide priority.

This is also why we need variables “G” and “H”.? That is to say, the chance of being the 2nd or 3rd cheapest?of the four options DRd, Rnw, Nuc and CCS.? Again, it helps us decide the gross priority for deployment, in the event that more than one pathway proves necessary to attack SQ and SQ-DRd. Of course, the reality will be more nuanced where there are very special local conditions that facilitate unusually cheap application of one route over another – the objective here is to provide a gross framework “overview” to help guide general prioritisation and associated policy formulation and investment.? Especially state and taxpayer investment.? Private investment is freer to take the gambles wherever the whim takes it.? Not public money.? Note that the chance of being the most expensive route for attacking SQ and hence the least attractive one, also falls out of the calculation 1-(F+G+H).?

SECTION 2: Renewables Rnw (plus related energy storage, long distance distribution, recycling & demand management)

The parameterisation for renewables (Rnw - Figure 32) follows pretty much the same pattern as for DRd, except that for all the routes that are not demand reduction, we assume the latter will be present in some form as an indispensable part of the energy transition.? “Rnw” itself represents the energy supplied by renewables and their associated components, noting as per the previous section that we may in a scoping exercise choose to set SQ to 100 and estimate DRd, Rnw, Nuc, and CCS in relative terms against that value.

So once more, we include variables for the chance of Rnw wholly meeting SQ-DRd (“J”) and doing so within two half-lives 2δ (“K”), and the chance of meeting 10% of SQ-DRd or more (“j”) as a scalability threshold. Similarly we estimate the cost of any renewables energy contribution “X” and the chance?of it (from the four options) being the cheapest option (“L”), 2nd or 3rd cheapest (“M” and “N” respectively), and by inference chance of being the most expensive (1-(L+M+N)). Once again the cost “X” involving financial environment, and social elements, however they are consistently integrated across sectors.

The key thing to notice about “Rnw” however is that is not just related to solar panels, dams, wind turbines, and geothermal power stations.? It is also related to all the elements of energy storage and long-distance distribution (including e-fuel and power transmission options as per Figure 14), the recycling of all those elements, and demand management strategies (e.g. industrial collocation close to renewable energy sourcing).?? These are just some of the things that work together to make “Rnw” work.? Once again, it is difficult to come up with a single value for ?X or Rnw, as with W and DRd, given the diversity of different renewable components – but each of these terms can be assigned their own formulae as desired, as long as it is done transparently and auditably.

SECTION 3: Nuclear Nuc (plus energy storage, plus long distance distribution, plus FNR reprocessing plus geological repositories, plus security, insurance and decommissioning)

The parameterisation for nuclear (Nuc - Figure 33) follows the same pattern as for Rnw.? “Nuc” itself represents the energy supplied by nuclear and its associated components, noting as per the previous section that we may in a scoping exercise choose to set SQ to 100 and estimate DRd, Rnw, Nuc, and CCS in relative terms against that value.

So once more, we include variables for the chance of Nuc wholly meeting SQ-DRd (“P”) and doing so within two half-lives 2δ (“Q”), and the chance of meeting 10% of SQ-DRd or more (“p”) as a scalability threshold. Similarly we estimate the cost of any nuclear energy contribution “Y” and the chance of it (from the four options) being the cheapest option (“R”), 2nd or 3rd cheapest (“S” and “T” respectively), and by inference chance of being the most expensive (1-(R+S+T)). Once again, the cost “Y” involving financial environment, and social elements, however they are consistently integrated across sectors.

As for the renewables, we include not just the costs of the power generation facilities, but all the other things that would need to happen to make this option viable.?? That would then include things like:

1.?????? Nuclear fuel mining and processing

2.?????? Energy facility construction & operation (i.e. reactors etc)

3.?????? Any energy storage requirements, related to a nuclear plant operating at full capacity to maximise economics, but by inference doing so at times when there might not be demand for energy

4.?????? Any implied long distance power transmission or e-fuel networks (or heat networks – with long-distance being a relative term for each commodity)

5.?????? Fast neutron reactor reprocessing (FNR) development routes to help transmutate waste and reduce the amount and half-lives of any unprocessible waste, while simultaneous providing addition energy.

6.?????? The costs of any geological repositories built to accommodate any high-level waste not dealt with through other routes.

7.?????? The costs of radioactive material security from accident, terrorism and nuclear proliferation.

8.?????? The costs of state cover of insurance as insurer of last resort given that unlike other routes insurance companies are not in general willing to cover some categories of accident.

9.?????? The cost of decommissioning.

It should be stressed that in each of the four categories the most prominent costs are captured, and I am not attempting here in this article to give an exhaustive list for every option. Every route, for example will have costs related to raw material mining and processing, decommissioning at end of life, or issues of security and insurance. I mention these in particular for nuclear because they are bigger and more important considerations relative to the other routes.?

The other elephant in the room for nuclear, is a variety of “incipient” technologies that may or may not go further.?? These include such things as fast neutron reactors for processing nuclear waste, thorium based molten salt reactors, small modular reactors, and of course fusion.?

The extent to which each of these is captured in an analysis of “Nuc” and “Y” and the other associated variables, will vary with analyst, but the technological readiness levels of each as per Figure 30, and the R&D and development costs of any technologies as yet unproven, will need to be incorporated in any cost estimations and the chances of success for the other variables in Figure 33.?

That is to say, as long as the analysis is transparent, it doesn’t matter what is included, but there is a need to avoid “having the cake and eating it”.? I.e. if we reduce the costs of waste due to new technologies and increase the amount of energy producible due to new technologies, we also have to adjust the chances of success and include any development costs. It can be easier and simpler in that respect to stick with the more robustly known fission technologies.

?SECTION 4 CCS (New energy projects with geological carbon capture or DAC and a component of uncaptured scope-1 emissions)

The parameterisation for CCS (Figure 34) follows the same pattern as for Rnw and Nuc, but with some additional elements.? “CCS” itself represents the energy supplied by fossil fuel elements with associated capture and its associated components, noting as per the previous section that we may in a scoping exercise choose to set SQ to 100 and estimate DRd, Rnw, Nuc, and CCS in relative terms against that value.

So once more, we include variables for the chance of CCS wholly meeting SQ-DRd (“U”) and doing so within two half-lives 2δ (“V”), and the chance of meeting 10% of SQ-DRd or more (“u”) as a scalability threshold. Similarly we estimate the cost of any CCS assisted energy contribution “Z” and the chance of it (from the four options) being the cheapest option (“ζ”), 2nd or 3rd cheapest (“η” and “θ” respectively), and by inference chance of being the most expensive (1-(ζ+η+θ)). Once again, the cost “Z” involving financial, environment, and social elements, however they are consistently integrated across sectors.

Under the banner of carbon capture (CCS) we include geological storage and direct air capture for completeness.?

The reason that we have additional parameters to consider for CCS is that unlike DRd, Rnw, and Nuc, there are very clear ongoing scope-1 emissions associated with the option.? All the options have related scope 2 and 3 emissions as long as hydrocarbons remain a significant part of the energy system, but only CCS has scope-1 emissions implicitly embedded in it.?

It is not so much a route for removal of COx (i.e. CO or CO2) from the atmosphere. In reality in an energy provision context, the best that can be hoped for is as a route for the discounting of new COx additions to the atmosphere.?? In that context natural carbon capture routes for removal of COx are not considered here, since we are dealing with routes for tackling SQ, i.e. energy provision, rather than COx removal per se.? Given the longer timescales required for natural routes to take effect, they are treated as a separate standalone avenue rather than one paired with energy provision.??

The additional CCS parameters as shown in Figure 34 then relate to quantifying this component of uncaptured scope-1 emissions, as it will have impact on associated costs and hence “Z”.? We start from a position of looking at the energy generating facilities and estimating their emissions without any capture as “CCS0”.?

We then want to estimate the percentage that are permanently captured from the atmosphere as “CCS1”.? Note this implies that an amount 100%-CCS1=“CCS3” will still be released at some point to the atmosphere.? We also have to include a relative amount “CCS2” that describes the % of CCS1 emissions that are negated by using CCS for enhanced oil recovery and then combusting the oil recovered.? Note that CCS2 may well be more than 100% - i.e. the use of CCS for EOR might totally negate any level of CCS capture.?

This net capture figure as a % is captured in the term “CCS4”, where CCS4 = (CCS1-(CCS2*CCS1)).? Note that if CCS2>100% then CCS4 has a negative value, and the net capture of the CCS process is less than zero. I.e. emissions end up being > CCS0 - meaining it is not effectively capturing anything and not assisting with emissions reduction. Instead it is effectively making things worse than if no CCS took place and defeating its “raisons d’etre” relating to options A & C in Figure 2.

There are quite a few misconceptions relating to what CCS1 – the percentage of emissions permanently captured in CCS, actually is.? This process is described in Figure 35.?

The carbon capture percentage is emphatically not just that which occurs at the emitting facility.? That can be quite good – better than 95% and is described in Figure 35 as parameter “A” and in Figure 34 we call it “CCSi”.? Next we have to take the COx from the emitting facility or direct air capture plant to its final storage place.? That is described as “B” in Figure 35 and “CCSii” in Figure 34.? In general this isn’t much of a problem, as there will not be much leakage or loss during distribution and interim storage, en route to the final destination.?

The biggest issue is typically the parameter described as “C” in Figure 35, i.e. “disposal efficiency”.? In Figure 34 we call it “CCSiii”.? It relates to the percentage we can actually emplace in the site of storage relative to what we would want/design to transport there.? The amounts that can’t be stored are typically vented to the atmosphere (Abdulla et al., 2021; Robertson & Mousavian, 2022), so this is a very real issue.?

The thing about geological CCS resource is that the COx it gets there through boreholes.? It is one thing to estimate how much the various rocks and their saline fluids might be able to absorb volumetrically IF you can get the COx to it.?? It is quite another to know how reliably a limited number of boreholes through which all the COx has to travel might reach those volumes. That is often the biggest problem and as well as the relative porosity and permeability of the rocks involved and the geometry of permeability pathways, it can sometimes be related to the dynamics of various injection performances used to assist that access, as well as a variety of other well completion issues.? The projects that have greatly underperformed relative to expectation have often failed at this “C” stage.? That greatly impacts the value of CCS1 and hence what is released to the atmosphere, CCS3 - which will in turn impact costs “Z” of any CCS related energy. More so as time goes on and GHG emission punitive measures increase.

The last component of CCS is “CCSiv” in Figure 34, which corresponds to elements of “D” in Figure 35 – the concept of a CCS “cage”.?? This tries to assess how much of the CCS capture will eventually re-release to the atmosphere.?? This could be via long term “leakage” from the geological site.? It could also be via uses of the COx that ultimately release it back to the atmosphere.?? If we use it in fizzy drinks, or use it to produce e-methanol, or any other materials that are ultimately combusted, it is eventually released back to the atmosphere.?? The CO2 has been monetised but not captured.?? As stated previously, a big difference between the two.?

Note that the emissions generated by enhanced oil recovery are resolved out of “D” in Figure 35 and not treated in CCSiv but instead in the already described separate term “CCS2”.? This approach better covers the not infrequent scenario where any usage in enhanced oil recovery (EOR) results in later oil usage emissions that exceed those captured.

Health warning

Just to reiterate as per the opening section of the article, that what follows is not intended as any wider “magic” template.? Other people’s spreadsheets are always fairly opaque.? It is really just an exercise in going through the framework which I’ve established so far - with some sample numbers to satisfy myself that a generic exercise of parametrisation like this can help progress things.? This, in terms of assisting focus and diffusing difference that is easier to tackle when localised to particular parameters.?

The sample numbers are very much a first go, and the purpose of the exercise is not actually for others to agree with them, but to better identify which things they differ on.? Therein lies a map for more targeted progress on issues of dispute. ?Some disputes will be fairly reconcilable and best left as agreeing to differ.? Others will lend themselves to more constructive study and resolution.? Differentiating the two types is of its own right perhaps helpful.?

Having a go – first stab straw man

I don’t seriously expect anyone to rigorously inspect each of Figure 36 through to Figure 40, but they are there for completeness’ sake, as a reference to describe each parameter for each section in a bit more detail, and the input chosen in this “first stab”.? More relevant is Figure 41 which collates a summary of the inputs at each section.?

The question to ask is not whether you agree with every input.? No two of us will agree completely, and many of us will differ dramatically.? The question to ask at this stage is whether the exercise of parameterising the problem at hand to produce the table in Figure 41 would give a good first idea of where we agree and differ, and hence where to take any further discussions.

That said, you can I think get an overview of where my views lie from Figure 41. I’ve identified climate as the most urgent problem driving a need for change, with a likelihood of 98% of it being necessary.? As designation of a desired period of two half lives to “quarter” the status quo, I’ve set that to 50 years – much slower than many would like, but already optimistic accepting a degree of realpolitik as to how fast things will go compared to how fast we want them to go.? As for the required proportion of the status quo for downshift "destination", I’ve set this as 0.2 in line with IPCC guidelines (IPCC, 2015). That is to say, we are by virtue of this parameter being set at 0.2 and not 0, discussing a downshift of fossil fuel related energy, not a total disappearance of it.

Going down the table, you can see I’ve given renewables and nuclear only a 1 in 20 (5%) chance of being able to supply the status quo amount of fossil fuel energy provision after demand reduction is applied.? That’s probably optimistic, but what is telling you is that as well as demand reduction I envisage at least two other routes being required.? To do the same thing within two half lives of 50 years I’m even harsher – setting that at 1 in 100 for each of renewables and nuclear.? Again suggesting a need to look, on top of demand reduction, at more than just renewables.?

In the third section down the table the scalability issue is addressed, and you can see I consider all three of demand reduction, renewables, and nuclear as highly likely of being capable of supplying 10% of the status quo energy demand - and that in contrast, I consider CCS assisted fossil fuel combustion energy approaches as being highly unlikely to meet that threshold. It reveals my penchant for demand reduction, renewables, and nuclear as the big-ticket players most likely to make a difference.?

As we go down the list to the bottom three sections, we can see that I envisage demand reduction as most likely to be the cheapest option going forward, renewables as the next cheapest, and then nuclear after that.?? Bearing in mind still that “cost” and “cheap” involves financial, environmental, and social considerations. CCS being the only one of the four with associated ongoing scope-1 emissions and having issues on the scalability front, bumps it into the expensive bracket.

Note though, that in assigning probabilities to these things, we do not preclude the possibilities of the improbable happening.

So likely you will take issue with many of those numbers, and I’m not pretending I would be unhappy tweaking a few of them – it’s a very subjective exercise – but it does give immediately a very real sense of my perception of an energy transition with which to seed any discussions.?

That “map” of views is the primary objective.? It tells you where I would focus efforts.? ?Primarily on demand reduction, next on renewables, but keeping nuclear alive at some level.? CCS I would not see as pivotal to the goal.? ?That is not the same thing as saying it can never be useful in any place for any application, just that in my view for the climatic fossil fuel downshift priority I identified in my inputs to Figure 2 and repeated in Figure 36, it does not play a meaningful role at a scale of significance.

Note of course that what these tables don’t say is which renewable options, or which energy storage options, or which nuclear options, or which energy distribution options, I favour.? There is however nothing to stop each of sections 1 to 4 (i.e. DRd, Rnw, Nuc, CCS) being treated with similar approaches and increased levels of resolution.? But that’s for another day… (or lifetime…)

Summary

It is apparent to most of us that any goal of energy transition of fossil fuels creates a wide spectrum of views on an immensely complex topic.? Including the reasons motivating any need for change.?

There will at the end of the day be the situation where some views are irreconcilable and that brings limited value in continuing exchange.? There are however some fairly simple over-riding things which dictate any one person’s view of an energy transition.?? First the likely reasons for it, which might be climate driven, supply constraints driven, or other environmental concern driven (e.g. air quality).? We can capture from each person their perception of how likely each problem is to require a need for change – which implicitly accepts that not everyone will always be certain of something, just aware of a risk with certain impact.?

Accepting some non-zero chance of a requirement for change from fossil fuel provision of energy, there is then a fairly limited range of alternatives at a high level that can fit the bill in terms of providing energy with reduced levels of emissions.? The four identified being pretty much it – demand reduction, renewables (with storage), nuclear (with storage), and fossil fuels “lite” in the form of partial capture through CCS.?

We are now in a position to take our Figure 1 "cloaked" version of the A3 workflow, and do the “big reveal” from our elaborations in Figure 2, Figure 3, Figure 31, Figure 32, Figure 33, and Figure 34, to give the full collation as shown in Figure 42.?

There is no “tah-dah” or drum-roll attached to this.? It is a very imperfect attempt.? It is however an exercise to show that with thought we can parameterise our assessments of an energy transition into key variables that facilitate and streamline progressive discussions with others.?? Mainly by identifying the issues of most contention and assessing whether there are constructive ways of addressing those issues.

It's been an involved exercise, but at the very least, I can tell you, it helped me.

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