Thread by @FrLomb

Planning highly renewable power systems involves compromise across diverse stakeholders. Is it possible to balance techno-economic feasibility with social and political goals?

Read our new @Joule_CP study w @bryn_pickering @EmyColomboPOLI @stefpf 👇

bit.ly/2QkEBSL

Contested decisions include where to locate generation and transmission capacity. Yet, it is common to use a single-result cost-minimising energy system model to inform planning. This neglects alternatives that e.g. avoid problematic concentrations of capacity[..]

We develop a method that generates a variety of spatially-explicit, alternative system configurations which can be used to balance techno-economic feasibility with social and political goals - building on ideas from @etrutnevyte @jfdecarolis @fneum_ @nworbmot

The application of the method to Italy reveals trade-offs like where to site wind farms, hidden in conventional methods. The cost-optimal solution would entail a heavy and unfair share of wind farms in Sardinia, likely leading to local opposition. But many alternatives exist ✌️

PV☀️is a must-have in all examined systems, often complemented by batteries, whilst wind💨expands together with synthetic-gas turbines, all of which must notably increase to replace bioenergy’s firm capacity [...]

Interestingly, replacing firm capacity is a lot easier for highly-interconnected, central regions✨, which can act as a buffer taking advantage of close PV and syngas turbine capacity and wind farms located further away and connected via transmission lines & syngas pipelines[..]

As a result of broader interest for other EU countries wondering what to do with gas infrastructure❓: syngas turbines can contribute to balancing but always with a minor role compared to today’s use 👎 Additional investment into gas infrastructure now is not a good idea [...]

As an example of the alternatives unveiled by SPORES 🙌: see massive concentration of wind and methanation (in Sardinia, the island on the lef) in cost-optimal case, against one with low wind concentration!

Our approach can be applied to other national systems, as well at district & continental scales. It is now implemented in a branch of the open-source #Calliope framework, and soon part of new release with full user documentation!

Ah, one last takeaway: weather ⛈️does dramatically change results if looking only at what's cost-optimal, but #SPORES do allow identifying configurations that are close to optimum regardless of weather conditions! Next step? resilient-SPORES !⚡️