Technology openess in energy system analyses

This topic is started due to a mailing list discussion and because it was also touched by discussions in the openod meeting (berlin 2020 and before).
I sum up some mails here for the start:
Beginning of the threat was the addition of the reached percentage of “carbon free” energy supply versus the reached percentage of supply from “renewable energy technology” (in this case in GB) (which fired a little bit the old RET vs nuclear debate).
Followed by the request to differ it from an environmental perspective, which was understood as a subjective view on it and then followed by request and highlighting of technology openess: (following parts of two mails):

  1. …Though I believe our models must be technology neutral: I confess that I do have a technology favourite. It is energy efficiency. We represent it poorly. And generally are pretty stuck with a fixation on RET, which is more environmentally damaging

  2. …Modelling every technology with a handful of technical parameters (capital cost, fuel cost, O&M, build time, lifetime, ramp rates, start-up costs etc.) does a disservice to the real world. How will this ever capture the complex of “risk, risk perception and social contract issue[s]” around nuclear that Mark describes below?
    Which model captured the complex of socio-political considerations that has led to huge reductions in new onshore wind additions in the UK and Germany?
    As Mark suggests, the only thing to do is be open and humble about the models and not expect too much from them. And calculate lots of scenarios so that the rest of society is well-informed when it decides what it wants.
    (So the argument for technology neutrality is less about wanting to avoid bias, which can easily creep in via the assumptions anyway, but more an acknowledgement that the models don’t capture significant effects outside the techno-economic domain.)

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I think openness to technology and technological neutrality are goals but not reality. In that sense, I understand Tom’s contribution. Brigitte Knopf and others have investigated this in 2012 or 2013 by comparing models from the direction of RET and energy efficiency. (as far as I remember in
In my opinion, we cannot talk about models being open to technology or technologically neutral if all aspects are not included. (and this is, as Mark and Tom have already written, also the reason why models and assumptions need to be open to be properly assessed).
In different projects, there was also the aim to include more aspects , such as land use,material flow and resources, LCA (e.g. Sim4Nexus, MEDEAS, REEEM,…).which, as far as I can see, was not achieved to the extent originally planned.
At the openmod meeting 2020 the integration of acceptance and participation or even sufficiency through different approaches was discussed. => are behavioural aspects part of technology neutrality? I would rather say no, but ask for other statements. (I see integration of behaviour more as an attempt to model the possibilities/be closer to real developments).

I think the closest to technology neutrality is the interaction of energy system modellers with LCA modellers (@ Chris Mutel: thanks for bringing this always to the openmod meetings).


Hey, thanks for this input. I would like to comment on the “technology neutral approach” in modelling from a technical perspective.

I share the concern that if we don’t have something like social potential of different technologies, besides economic and technical potential, we will continue to miss potential backlashes against diffent technologies such as onshore wind.

However, in my opionion, technology neutral approach means that if we predifened a set of parameters/variables that we will take into account (such as those that I quoted from your post), we as modellers should not exclude some technologies due to some other reasons. So, if we defined that our model would include capital, fuel cost, O&M and lifetime, we shouldn’t exclude nuclear because of some other reason. It could be that it would be not economic to invest in it, but we shouldn’t exclude it beforehand.

In the end, I agree that the best approach to reduce bias is to present several different scenarios that are then open for discussion, contrary to just one ‘optimal’ scenario.

Thanks for your input! I#m still not sure if I find it convincing. Just to clarify: the costs that you would include - do they include all costs around the technology? like for maintanance - does this include assurances (and if no assurance available then reserves for all possible accidents) as well as costs for dismantling? What about society costs for land-use and health?
If this is included I would agree that it is a technology neutral approach. If not I wouldn’t name a cost optimisation technology neutral.
Governments take the results and use them without being informed (or noticing the information) that other costs apart from the model are also relevant.

I’m talking more about the methodological approach. The point is once the modeller decides what she/he wants to include as a part of her/his method, she/he should not decide afterwards which technologies to include and which not. Technology neutrality in my opinion is concerned more with goals of studies. So once we set a goal of the study (e.g. no CO2 emissions), and develop a methodology, we should not pick certain technology options afterwards. Technology choices in a technology neutral approach should arise as a result of the model.

And finally, I absolutely agree with you that our communication with policymakers should be clearer about the limitations of different studies. But that is easier to be said than done considering that policymakers can have very limited understanding of specific subtleties.


Dear all,
I agree with Dominik, that it makes most sense not to exclude any resources a priori from an entire study based on non-modeled factors, such as percieved risk or externalities not captured in modeled costs. Instead of a priori exclusions, one can run a range of different scenarios that exclude these technologies in certain cases, or raise their costs (capex or variable) to reflect potential non-modeled costs, and see how that affects outcomes. One can also use modeling to generate alternatives or other approaches to enumerate multiple candidate portfolios with similar costs, and then either explicitly evaluate them ex post based on non-modeled criteria, or simply present the range of options and allow decision makers/stakeholders/other readers of your work to decide on their own subjective ranking of technically feasible, near-least-cost portfolios. This is the approach I pursue in my work to handle potential non-modeled factors and to be humble about the prescriptive nature of our models. When one excludes resources a priori, one necessarily applies a particular set of judgements and often subjective application of criteria to justify such exclusions. This is fine in principle, if very clearly articulated and explained in the study. But it potentially removes useful information for readers who may not share the same criteria. After all, so much of this is comes down to a multi-objective evaluation using subjective value systems that are non-universal. Just some random musings on this important topic from my Sunday. Best,
Jesse Jenkins
PI, Zero-carbon Energy systems Optimization and Research Laboratory (ZERO Lab)
Princeton University