The planning and operation of electricity systems with high shares of variable intermittent renewable energies (VRE) require a solid understanding of weather impacts, which are becoming increasingly influenced by climate change and associated extreme events. However, there is a lack of standardized methodologies for identifying extreme events and systematically assessing climate change impacts on power systems. This study addresses this gap by applying a residual load (RL)-based framework that integrates climate projections with indicators of a VRE-dominated future power system, enabling the systematic detection and analysis of extreme events. RL is defined as the difference between electricity demand and VRE generation. The proposed RL-based framework assesses climate-change impacts on power systems and identifies extreme events under future climate scenarios. This is achieved through a multi-annual analysis combining a decarbonization pathway with moderate and strong climate-change scenarios. The analysis evaluates changes in specific RL indicators across geographical scales, including the EU, and Austria as a country case. In Austria, stronger climate change shifts peak periods of residual load (PPRL) towards summer, indicating a growing influence of heatwaves. At the same time, PPRL frequency increases to up to six events per year, while maximum event durations decrease from 46–53 to 33–34 days. At the EU level, PPRL events are less frequent (1–2 per year) and shorter (around 10 days, with maximum durations of 20 days). This highlights the importance of strong interconnection within the European power system, as cross-border exchanges can support regions and countries during extreme-event periods.

This study investigates weather-driven stress events in the Austrian and Central European power system by combining an in-depth energy system analysis of two historical years with a climatological assessment of event likelihoods. The year 2017 exemplifies a pronounced dark doldrum period, characterised by persistently low wind and solar capacity factors, while 2022 represents an heatwave-induced hydropower drought with prolonged high temperatures, reduced precipitation and decreased river flows. Droughts of electricity infeed from variable renewable energy sources are identified using multiscale moving average capacity factors and a multi-threshold framework, enabling a power-systemrelevant definition of thresholds. To assess the future occurrence of similar events, percentile-based meteorological thresholds derived from historical conditions are applied to a subset of the CMIP6 climate model ensemble across different Global Warming Levels. Results indicate a decline in dark doldrums (up to $-77 \%$) and an increase in heatwave-related events (up to $\boldsymbol{+} \mathbf{1 6 3 \%}$) at GWL- $\mathbf{4. 0}{ }^{\circ} \mathrm{C}$, signalling a shift in system stress.

Renewable and electrified energy systems are highly weather-dependent, making them vulnerable to climate change. Energy system modeling therefore requires high-quality data that captures the spatiotemporal complexity of climate conditions. We present SECURES-Energy, an open-access dataset providing hourly electricity demand and supply data for Europe at the national level from 1981 to 2100. Historical data are derived from ERA5 reanalysis, while future projections use two EURO-CORDEX scenarios (RCP 4.5/RCP 8.5). The dataset includes onshore and offshore wind, solar photovoltaic (PV), and hydropower generation, as well as all electricity demand components such as heating, cooling, and mobility. Results indicate no consistent trends for solar PV and hydropower across Europe. Offshore wind declines by up to -4%/-3% by 2035-2064 and -6%/-9% by 2071-2100 relative to 1981-2010. Cooling demand rises sharply (up to +80%/+149% by mid-century; +129%/+317% by end-century), while heating demand falls (-19%/-24% by mid-century; -25%/-40% by end-century). These findings highlight substantial climate-driven shifts in future electricity demand and supply.

The study evaluates mitigation and adaptation measures for the energy supply sector in South Westphalia (SWF) under the Clean Energy Transition Scenario (CETS) by 2050. It assesses electricity, district heating, and hydrogen systems under both normal (2032) and extreme heat-wave (2046) weather conditions, based on climate scenario SSP5-8.5. Results show that SWF’s transition relies heavily on national electricity imports but benefits from significant local PV (7,003 MW) and wind (3,250 MW) expansion. Despite high growth in electricity demand (up to 146%) grid capacity remains sufficient to manage renewable variability. The district heating sector becomes highly electrified, mainly through heat pumps and electric boilers, with biomass and waste CHP supplying base load. Hydrogen production adapts flexibly to electricity prices using electrolysers and storage. Overall, weather extremes do not significantly stress the system, thanks to strong grid integration and flexible technologies.

As the energy systems increasingly rely on variable renewable energy sources (VRES), their sensitivity to weather grows, introducing uncertainty and risks. Climate change further intensifies these challenges by affecting supply, demand and resilience of infrastructure. The ROBINE1 project aims to develop climate indicators for severe weather events at the regional level and assess the impact of climate change on Austria's future energy system. This work exemplifies "desert days" indicator and illustrates the projected demand and supply changes by 2040, considering 20-year periods during which climate models predict an average increase in global warming levels (GWLs) of 2 degrees C, 3 degrees C, or 4 degrees C compared to pre-industrial levels. Results show a significant rise in desert days, especially in eastern regions. The changes in supply side various between regions, particularly for wind. While electricity demand increases, demand for heating and e-mobility decreases in 2040, leading to a slight overall drop.

The energy sector faces constant challenges due to the anticipated green transition and the underlaying change of climate. To be able to assess potential risks during the transition towards renewable energy sources, we present ROBINE-AT, an impact-oriented climatological dataset for Austria, consisting of 41 hazard maps for the Global Warming Levels 1.0 °C (corresponding to 2001–2020), 2.0 °C, 3.0 °C and 4.0 °C. The maps cover potential hazards for Austria’s energy system due to various impacts, including heat and cold stress, wind, extreme precipitation, floods, droughts, humidity, lightning strikes, and wildfires. The data is based on six localized and bias-adjusted climate projections of the CMIP5 and CMIP6 generation. With a diverse set of indicators and a high spatial resolution of 1 km, ROBINE-AT provides an innovative blueprint for assessing climate hazards, targeting regions with complex mountainous terrain such as Austria. Additionally, insights into climate impacts on the energy sector are provided, enabling tailored risk assessments by combining the hazards with custom exposure and vulnerability data.

This study develops a reproducible method for estimating the cost-efficient flexibility potential of a local or regional energy system. Future scenarios that achieve ambitious climate targets and estimate the cost-efficient flexibility potential of demonstration sites were defined. Flexible potentials for energy system assessment are upscaled from the demonstration sites in Eskilstuna (Sweden) and Lower Austria (Austria). As heat pumps (HPs) and district heating (DH) are critical for future heat demand, these sites are representative types of DH networks in terms of size and integration with the electricity grid. In both regions a TIMES model is used for energy system optimization, while for upscaling, Eskilstuna uses the building-stock model ECCABS, whereas Lower Austria uses a mixed integer linear programming optimization model, and the BALMOREL power system model. According to the modeling, HPs will dominate Eskilstuna’s heating sector by 2040. In Lower Austria, DH becomes more prevalent, in combination with wood biomass and HPs. These findings are explained by the postulated technological-economic parameters, energy prices, and CO 2 prices. We conclude that future electricity prices will determine future heating systems: either a high share of centralized HPs (if electricity prices are low) or a high share of combined heat-and-power (if electricity prices are high). Large-scale energy storage and biomass can be essential solutions as may deliver increased cost-effectiveness, if available and under certain conditions.

The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is highly connected, so that a pure country-based modelling is not expedient and at least the whole European Union (EU) area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21st century. Thus, we have developed the aggregated European wide climate data set SECURES-Met that has a temporal resolution of one hour, covers the whole EU area and other selected European countries, has a reasonable size but considers the high spatial variability.

In recent decades, renewable energy has stepped out of its niche as a key option for decarbonising the energy supply. It has gained attention in energy system modelling as well as in real-world energy sector developments. This chapter aims to describe past developments in the energy system modelling of renewable energy and related energy infrastructure prerequisites. Illustrative snapshots are provided, offering a chronological survey of energy system models with a focus on renewable energy and the main related thematic fields. Geographically, these snapshots refer to Europe and illustrated topics of interest as well as approaches used in corresponding model-based assessments. That journey offers fruitful insights on how the energy policy debate has emerged as well as how energy system modelling has advanced to provide substance and support decision making in accordance with emerging policy needs.

District heating can help to integrate renewable generation within the electricity domain and thus reach climate and energy goals by providing flexibility services and stabilizing the electricity grid. To determine the economic viability of such flexibility services, this work presents a profitability analysis of a central heat pump and/or combined heat and power unit within a biomass-based district heating network, conducted with a mixed-integer linear optimization model. Subsequent business model development for district heating utilities is conducted using the Business Model Canvas and the Odyssey 3.14 approach. Business model development and innovation are crucial to make use of the existing flexibility potential. The results show that the district heating utility's profitability as annual net profit increases in comparison with the status quo of biomass heat-only boilers when an additional heat pump is installed that can operate both in spot and balancing markets. Furthermore, all use cases including governmental support (for the heat pump, the combined heat and power unit or for both) prove to be economically favorable. The innovated business models indicate additional value for increased customer segments, thus enabling additional revenue streams for the district heating utility which can therefore promote the provision of flexibility in district heating.

<p><strong>Motivation</strong></p> <p>With increasing decarbonisation and electrification of the energy system, the electricity system's vulnerability to extreme weather events is becoming a focus of energy system planning and operation. This requires intensified collaboration between the domains of climatology and energy system modelling for an accurate portrayal of the effects of climate change on future energy systems. In this study, we construct a consistent data set for Europe's future electricity generation and demand components (covering NUTS3-NUTS0 level) using current climate models, including hydropower generation, which is frequently absent in comparable data sets.</p> <p><strong>Method</strong></p> <p>The methodological approach combines climate and energy system modelling. Parameters like temperature, wind speed, radiation, and precipitation are processed to derive weather-dependent electricity generation and demand profiles in hourly resolution for Europe until 2100. On the electricity generation side (wind, solar, hydro run-of-river, hydro storage), technology-specific processing steps are conducted to generate electricity generation profiles from climate data, e.g. the combination of wind speed levels with power curves of turbines. On the electricity demand side, the impacts of electrification and changing temperature (e.g., increased cooling demand during heat waves) are assessed. We model various scenarios to evaluate the effect of different shares of renewable electricity generation and different grades of climate change impacts. Therefore, projections for the future energy system in two decarbonisation scenarios (DN and REF) are combined with two RCP pathways (RCP4.5 and RCP8.5).</p> <p>The following weather-dependent generation and demand profiles are generated:</p> <ul> <li>E-heating, e-cooling, and e-mobility charging demand (dependent on temperature)</li> <li>Photovoltaics generation (dependent on radiation, losses dependent on temperature)</li> <li>Wind generation (dependent on wind speed)</li> <li>Hydro generation (dependent on hydro inflow)</li> </ul> <p><strong>Results and conclusions</strong></p> <p>From the processed climate data, we receive hourly profiles for electricity demand and supply for all European countries, which are used as inputs for the energy system modelling. The dataset allows for the systematic identification of critical situations in the electricity system (e.g., high demand and low renewable generation), which can pose a risk to supply security.</p> <p>Figure 1 shows as an example the distribution of the annual wind, hydro run-off-river (RoR), and photovoltaics (PV) generation, as well as electricity demand for e-cooling and e-heating in the 30 weather years surrounding the modelled year 2050. We observe a higher standard deviation in hydro generation than in the other two generation technologies, which is especially high in the RCP8.5 scenario. The demand shows relatively low variations between years, again stronger in the RCP8.5 scenario.</p> <p><img src="" alt="" /></p> <p><em>Figure 1: Annual wind, hydro run-of-river (RoR), and photovoltaics (PV) generation, as well as electricity demand for cooling and heating in the 30 weather years around 2050 in one RCP4.5 and one RCP8.5 scenario for Austria. The energy system projections are based on two scenarios for the year 2050: DN (RCP4.5) and REF (RCP8.5).</em></p> <p>The climate and energy data sets for the whole of Europe in hourly resolution until 2100 will be made available for open access in the course of the project SECURES.</p> <p><strong>Funding</strong></p> <p>The project SECURES is funded by the Climate and Energy Fund (Klima- und Energiefonds) under project number KR19AC0K17532.</p>

the aim of this work is to assess the energy transition and decarbonization of the heat demand and supply in the residential and service sector of the Austrian state Lower Austria for urban and rural areas up to 2050 by incorporating the contribution of flexibility options, i.e., sector coupling, demand side management (DSM) and storage technologies. For this purpose, the heat Lower Austria TIMES (HLA-Times) energy model was developed. The results show that decarbonization of the heating sector in Lower Austria is possible in 2040 being the use of fossil fuel already marginal in 2035. The use of biomass and the impact of sector coupling (heat pumps and CHP) will be fundamental.

In June 2018, an ambitious target has been set in Austria for the domestic expansion of electricity generation from renewable energy sources (RES) by the Austrian Climate and Energy Strategy: The goal is to cover the total national electricity consumption, measured by yearly balance, with RES. With this goal, the country's power system is facing a significant transformation. Not only the necessary expansion rate of RES, but also safeguarding system stability, and preserving security of supply are major challenges that need to be tackled in the coming years. A high share of electricity generation from hydro, wind and PV is expected to lead to considerable, weather-related fluctuations in power supply. System flexibility is required to compensate short-to long-term (seasonal) differences between generation and consumption. This paper aims for assessing short-to long-term flexibility needs of the Austrian electricity system by 2030, which is intended to rely, almost exclusively, on RES and the use of flexibility options for meeting those needs. For this purpose, a high-resolution power and district heating model is used for the calculation of two distinct scenarios. Flexibility needs and coverage are quantified for these scenarios for different timescales, namely: daily, weekly, monthly and annually.

With the continued digitization of the energy sector, the problem of sunken scholarly data investments and forgone opportunities of harvesting existing data is exacerbating. It compounds the problem that the reproduction of knowledge is incomplete, impeding the transparency of science-based targets for the choices made in the energy transition. The FAIR data guiding principles are widely acknowledged as a way forward, but their operationalization is yet to be agreed upon within different research domains. We comprehensively test FAIR data practices in the low carbon energy research domain. 80 databases representative for data needed to support the low carbon energy transition are screened. Automated and manual tests are used to document the state-of-the art and provide insights on bottlenecks from the human and machine perspectives. We propose action items for overcoming the problem with FAIR energy data and suggest how to prioritize activities.

The principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) have been put forward to guide optimal sharing of data. The potential for industrial and social innovation is vast. Domain-specific metadata standards are crucial in this context, but are widely missing in the energy sector. This report provides a collaborative response from the low carbon energy research community for addressing the necessity of advancing FAIR metadata standards. We review and test existing metadata practices in the domain based on a series of community workshops. We reflect the perspectives of energy data stakeholders. The outcome is reported in terms of challenges and elicits recommendations for advancing FAIR metadata standards in the energy domain across a broad spectrum of stakeholders.

With the continued digitization of the energy sector, the problem of sunken scholarly data investments and forgone opportunities of harvesting existing data is exacerbating. It adds to the problem that the reproduction of knowledge is incomplete, impeding the transparency of science-based evidence for the choices made in the energy transition. We comprehensively test FAIR data practices in the energy domain with the help of automated and manual tests. We document the state-of-the art and provide insights on bottlenecks from the human and machine perspectives. We propose action items for overcoming the problem with FAIR and open energy data and suggest how to prioritize activities.