Diversity of options to eliminate fossil fuels and reach carbon neutrality across the entire European energy system

Abstract Climate change modulates both energy demand and wind and solar energy supply but a globally synthetic analysis of supply–demand match (SDM) is lacking. Here, we use 12 state-of-the-art climate models to assess climate change impacts on SDM, quantified by the fraction of demand met by local wind or solar supply. For energy systems with varying dependence on wind or solar supply, up to 32% or 44% of non-Antarctic land areas, respectively, are projected to experience robust SDM reductions by the end of this century under an intermediate emission scenario. Smaller and more variable supply reduces SDM at northern middle-to-high latitudes, whereas reduced heating demand alleviates or reverses SDM reductions remarkably. By contrast, despite supply increases at low latitudes, raised cooling demand reduces SDM substantially. Changes in climate extremes and climate mean make size-comparable contributions. Our results provide early warnings for energy sectors in climate change adaptation. 

Climate change impacts on planned supply–demand match in global wind and solar energy systems

Climate change is expected to intensify the effects of extreme weather events on power systems and increase the frequency of severe power outages. The large-scale integration of environment-dependent renewables during energy decarbonization could induce increased uncertainty in the supply–demand balance and climate vulnerability of power grids. This Perspective discusses the superimposed risks of climate change, extreme weather events and renewable energy integration, which collectively affect power system resilience. Insights drawn from large-scale spatiotemporal data on historical US power outages induced by tropical cyclones illustrate the vital role of grid inertia and system flexibility in maintaining the balance between supply and demand, thereby preventing catastrophic cascading failures. Alarmingly, the future projections under diverse emission pathways signal that climate hazards — especially tropical cyclones and heatwaves — are intensifying and can cause even greater impacts on the power grids. High-penetration renewable power systems under climate change may face escalating challenges, including more severe infrastructure damage, lower grid inertia and flexibility, and longer post-event recovery. Towards a net-zero future, this Perspective then explores approaches for harnessing the inherent potential of distributed renewables for climate resilience through forming microgrids, aligned with holistic technical solutions such as grid-forming inverters, distributed energy storage, cross-sector interoperability, distributed optimization and climate–energy integrated modelling. Increasing grid penetration of renewables coupled with intensifying climate extremes under climate change presents superimposed risks to future power systems. This Perspective analyses the critical factors influencing the resilience of renewable power systems under climate risks and proposes climate-resilient solutions towards a net-zero future. 

Resilience of renewable power systems under climate risks

We suggest a new methodology for designing robust energy systems. For this, we investigate so-called near-optimal solutions to energy system optimisation models; solutions whose objective values deviate only marginally from the optimum. Using a refined method for obtaining explicit geometric descriptions of these near-optimal feasible spaces, we find designs that are as robust as possible to perturbations. This contributes to the ongoing debate on how to define and work with robustness in energy systems modelling. We apply our methods in an investigation using multiple decades of weather data. For the first time, we run a capacity expansion model of the European power system (one node per country) with a 3-hourly temporal resolution with 41 years of weather data. While an optimisation with 41 weather years is at the limits of computational feasibility, we use the near-optimal feasible spaces of single years to gain an understanding of the design space over the full time period. Specifically, we intersect all near-optimal feasible spaces for the individual years in order to get designs that are likely to be feasible over the entire time period. We find significant potential for investment flexibility, and verify the feasibility of these designs by simulating the resulting dispatch problem with four decades of weather data. They are characterised by a shift towards more onshore wind and solar power, while emitting up to 50% less $CO_2$ than a cost-optimal solution over that period. Our work builds on recent developments in the field, including techniques such as Modelling to Generate Alternatives and Modelling All Alternatives, and provides new insights into the geometry of near-optimal feasible spaces and the importance of multi-decade weather variability for energy systems design. We also provide an effective way of working with a multi-decade time frame in a highly parallelised manner.

Intersecting near-optimal spaces: European power systems with more resilience to weather variability

Challenges resulting from urban density and climate change for the EU energy transition

/pdf/overcoming-the-disconnect-between-energy-system-and-climate-262fpmfg.pdf

Overcoming the disconnect between energy system and climate modeling

The basic principle of operation of silicon sensors with resistive read-out is built-in charge sharing. Resistive Silicon Detectors (RSD, also known as AC-LGAD), exploiting the signals seen on the electrodes surrounding the impact point, achieve excellent space and time resolutions even with very large pixels. In this paper, a TCT system using a 1064 nm picosecond laser is used to characterize sensors from the second RSD production at the Fondazione Bruno Kessler. The paper ﬁrst introduces the parametrization of the errors in the determination of the position and time coordinates in RSD, then outlines the reconstruction method, and ﬁnally presents the results. Three diﬀerent pixel sizes are used in the analysis: 200 × 340, 450 × 450, and 1300 × 1300 µ m 2 . At gain = 30, the 450 × 450 µ m 2 pixel achieves a time jitter of 20 ps and a spatial resolution of 15 µ m concurrently, while the 1300 × 1300 µ m 2 pixel achieves 30 ps and 30 µ m, respectively. The implementation of cross-shaped electrodes improves considerably the response uniformity over the pixel surface.

pdf/high-precision-4d-tracking-with-large-pixels-using-thin-2jdekjsg.pdf

High-Precision 4D Tracking with Large Pixels using Thin Resistive Silicon Detectors

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Overcoming the disconnect between energy system and climate modeling

High-Precision 4D Tracking with Large Pixels using Thin Resistive Silicon Detectors