REMIND-PyPSA-Eur: Integrating power system flexibility into sector-coupled energy transition pathways
🤖 AI Summary
Power system flexibility deficits under high renewable energy penetration cause supply-demand imbalances. Method: This study proposes a bidirectional dynamic coupling framework integrating short-term power system operational characteristics into cross-sectoral energy transition pathways. It soft-couples the long-term investment model REMIND with the short-term operational model PyPSA-Eur via price signals—enabling, for the first time in a multi-sectoral context, co-optimization of capacity expansion, energy storage dispatch, demand-side response, and electricity price feedback. Contribution/Results: A near-100% renewable electricity system is demonstrated to be both technically feasible and economically viable. Demand-side flexibility significantly reduces peak load and average system electricity prices. These findings underscore its critical role in achieving Germany’s 2045 carbon neutrality target, highlighting the necessity of integrated, temporally resolved modeling across planning and operations horizons.
Application Category
📝 Abstract
The rapid expansion of low-cost renewable electricity combined with end-use electrification in transport, industry, and buildings offers a promising path to deep decarbonisation. However, aligning variable supply with demand requires strategies for daily and seasonal balancing. Existing models either lack the wide scope required for long-term transition pathways or the spatio-temporal detail to capture power system variability and flexibility. Here, we combine the complementary strengths of REMIND, a long-term integrated assessment model, and PyPSA-Eur, an hourly energy system model, through a bi-directional, price-based and iterative soft coupling. REMIND provides pathway variables such as sectoral electricity demand, installed capacities, and costs to PyPSA-Eur, which returns optimised operational variables such as capacity factors, storage requirements, and relative prices. After sufficient convergence, this integrated approach jointly optimises long-term investment and short-term operation. We demonstrate the coupling for two Germany-focused scenarios, with and without demand-side flexibility, reaching climate neutrality by 2045. Our results confirm that a sector-coupled energy system with nearly 100% renewable electricity is technically possible and economically viable. Power system flexibility influences long-term pathways through price differentiation: supply-side market values vary by generation technology, while demand-side prices vary by end-use sector. Flexible electrolysers and smart-charging electric vehicles benefit from below-average prices, whereas less flexible heat pumps face almost twice the average price due to winter peak loads. Without demand-side flexibility, electricity prices increase across all end-users, though battery deployment partially compensates. Our approach therefore fully integrates power system dynamics into multi-decadal energy transition pathways.
Problem
Research questions and friction points this paper is trying to address.
Integrating power system flexibility into long-term energy transition pathways
Aligning variable renewable supply with electricity demand across sectors
Combining long-term investment planning with short-term operational optimization
Innovation
Methods, ideas, or system contributions that make the work stand out.
Bi-directional iterative soft coupling of models
Price-based integration of long-term investment
Hourly operational optimization with flexibility assessment
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2024-08-20Online World Conference on Soft Computing in Industrial ApplicationsCitations: 0
