Uniform framework for the estimation of future values of the techno-economic parameters

[fvdborre]

The reduction of the future investments costs (e.g. 2050 vs 2020) don't seem to follow common logic. Some mature technologies with a high marginal cost (when the CO2-cost is included) have major cost reductions and other technologies with a low marginal cost and exponential growth have no cost reductions.

A similar remark for the projected lifetimes (which can only be retroactively determined and cost reductions may lead to shorter lifetimes instead of longer lifetimes).

A similar remark for the projected efficiencies. Efficiencies tend to stabilize once a technology has been matured. Higher projected efficiencies are often related to the difference between theoretical and practical efficiencies.

The differences may be the result of the different sources that have been used. The non-uniform techno-economic parameters may cause the results will be steered to certain technologies. A uniform framework for the estimation of future values of the techno-economic parameters is needed.

[fneum]

Thanks for sharing this comparison of projected cost reductions. Most of these concerns you would have to carry to the Danish Energy Agency, where we take most of the techno-economic assumptions from.

Because currently, no single database includes all the technologies we want to consider, there cannot be a common logic for technology evolvement, as it is very technology-specific. In this case, we have to rely on data from different sources at the expense of potential inconsistencies.

I also want to highlight that the DEA does a fantastic job with the technology database, without which it would be even more challenging to find consistent assumptions.

We'd be happy to take your suggestions on which other comprehensive sources we could consider in the future, particularly for the ones you do not concur with.

[euronion]

Maybe to add:

• Do you have specific questions on the technologies marked with ? in the first picture?
• Efficiencies can stabilise, that is correct. But they can also improve, even for matured technologies: Optimisation of existing technologies often happens as soon as they are mature and deployment is scaled up. Also our "technologies" represent in reality a mix of many different technologies: From different scales (small to large scale installations), from FOAK, NOAK to modular approaches or different specific technologies like for industrial scale heat pumps, where significant progress and changes are made to the working fluid, leading to gradual efficiency improvements.

We'd be more than happy to adapt a more uniform framework for cost estimations. But as the issue on #109 shows for electrolysis, where we use DEA numbers at the moment, uniform cost estimation is not always the right thing to aim for. So we try to keep a well balanced repo here, happy to receive updates & discuss potential changes to the numbers here!

[fvdborre]

I share your appreciation for the DEA's efforts in collecting valuable data, as our own energy and climate agency faces similar challenges with a small team dedicated to gathering data for a limited set of technologies. The open-source technology database, coupled with PyPSA, holds promise in informing reliable policy decisions, and I recognize the considerable effort involved in managing it.

Given the significant impact a single parameter can have on multi-billion-dollar policy decisions, I am keen on exploring methods to validate the robustness of numerous parameters, particularly those with substantial financial implications. Additionally, I am interested in approaches to estimating parameters that may lack reliability. My posts often aim to initiate discussions for validation or disproval of these suggested methods.

Concerning future projections, I advocate for basing investment cost reductions of low-marginal-cost technologies (e.g., PV, wind, batteries) on learning curves, while high-marginal-cost technologies (e.g., CHP, biogas, fuel cells) may exhibit negligible changes in current investment costs. Moreover, I see no current basis for significant alterations in other parameters like lifetime, efficiency, FOM, and VOM.

While I'm not convinced that the DEA needs to alter its approach, recognizing that they may be collecting data for other purposes, I believe the considerations I've outlined become more crucial in the context of system optimization, where relative differences in cost values among various technologies are paramount. These are initial insights, and I am open to discussing and refining them further.