A hybrid model spanning hours to decades shows that a fully renewable energy system is achievable, with flexibility key to lowering costs
A successful clean‑energy transition depends on understanding how to balance variable renewable power with the growing electricity demands of transport, heating, and industry. A key challenge is capturing how renewable energy sources like wind and solar fluctuate hour by hour, but this variability also creates new opportunities to align supply with increasingly flexible forms of demand, such as electric vehicles, heat pumps, and other electrified services. Alongside these short‑term dynamics, it is equally important to determine the long‑term infrastructure needed to support a fully decarbonised energy system.
In this research, two powerful models (REMIND and PyPSA‑Eur) are linked and allowed to exchange information repeatedly to determine both what infrastructure should be built and how it would operate each hour of the year. REMIND is a global energy and climate model that looks decades ahead, analysing investments, technology choices, and pathways to net‑zero. PyPSA‑Eur is a detailed model of the European electricity system that simulates real‑time grid behaviour. By combining a model that excels at long‑term planning with one that captures hourly power system dynamics, the researchers create a much more realistic tool for answering these complex questions.
They then test this approach on a Germany case study under two conditions: one with demand‑side flexibility (where electricity use can shift to cheaper hours, such as smart‑charging electric vehicles) and one without flexibility. Their findings show that a fully renewable energy system is technically and economically achievable, that flexible systems perform far better than inflexible ones, and that even with flexibility, electricity prices can vary significantly between sectors, creating political challenges around fair pricing. Both scenarios of the German case study reach net-zero emissions by 2045.
This research gives policymakers a clearer way to design reliable, affordable, fully renewable energy systems by showing how to integrate renewables, manage electrification, use flexibility to reduce costs, understand sectoral price differences, and build markets.
“Models used to inform climate policy have always faced a fundamental trade-off: they either capture the long-term perspective needed for investment decisions, or the hourly detail needed for power system planning, but not both. Our coupling of REMIND and PyPSA-Eur is a first step towards resolving this trade-off for an increasingly electric future energy system.” – Dr Adrian Odenweller, Potsdam Institute for Climate Impact Research
Do you want to learn more about this topic?
The role of grid-forming inverters in enabling high penetration of renewable energy in power systems: standards, ancillary services, current deployment, and future perspectives Ali Q Al-Shetwi et al. (2026)