ERE2.5 | Bridging the gap: climate science models and renewable energy research
EDI
Bridging the gap: climate science models and renewable energy research
Co-organized by ESSI4
Convener: Giacomo Falchetta | Co-conveners: Anasuya GangopadhyayECSECS, Rajat MasiwalECSECS, Caroline Zimm, Ashwin K Seshadri
Orals
| Thu, 18 Apr, 14:00–15:45 (CEST)
 
Room 0.16
Posters on site
| Attendance Fri, 19 Apr, 10:45–12:30 (CEST) | Display Fri, 19 Apr, 08:30–12:30
 
Hall X4
Posters virtual
| Attendance Fri, 19 Apr, 14:00–15:45 (CEST) | Display Fri, 19 Apr, 08:30–18:00
 
vHall X4
Orals |
Thu, 14:00
Fri, 10:45
Fri, 14:00
A worldwide transition towards “Net zero” requires electrification of diverse sectors over the coming decades. In addition to replacing existing fossil fuel-fired power plants with low-carbon energy resources, especially wind, solar and hydropower, additional capacity will need to be added. Renewable resources vary at a wide range of time scales, from minute-wise, seasonal, to interannual. Different variabilities and their spatio-temporal distribution can have their specific impacts on renewable energy systems, day-to-day operation, strategic planning and the design of “Net zero” pathways. In a changing climate, the availability patterns of renewable energy resources on various timescales are expected to change. Furthermore, considerable uncertainty underlies prediction of long-term changes in the spatio-temporal patterns of renewable resources. While energy demand often has daily and seasonal patterns that also depends on weather, this is also subject to variability and change. Given that the balance between demand and generation of electricity must always be maintained for grid reliability, there is a critical need for interdisciplinary dialogue between the climate science community and energy modeling research groups to explore renewable resource variability, in present and future scenarios, and resulting challenges for electricity grid management worldwide. It is important to identify critical challenges associated with balancing the demand and renewable generation, as well as identify methods and opportunities to address the challenges in the context of a wide range of uncertainties.

Studies may include (but are not limited to):

• Different ways to address the present seasonality of renewable resources and their expected changes in the future
• Uncertainties associated with future resource availability patterns
• Balancing of demand and supply of energy in present and future using different techniques such as bulk energy storage, maintaining an excess of wind-solar capacity, and demand-side management
• Economics and policy implications of the methods to maintain grid reliability
• Spatio-temporal complementarity between the availability patterns of different renewable energy resources
• Methods to maximize techno-economic synergies between different renewable resources and their hybridisation in the context of variability
• Data needs from climate science based modelling, to advance understanding of renewable energy sources

Session assets

Orals: Thu, 18 Apr | Room 0.16

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
Chairpersons: Caroline Zimm, Giacomo Falchetta, Ashwin K Seshadri
14:00–14:05
14:05–14:15
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EGU24-523
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ERE2.5
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ECS
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On-site presentation
Brieuc Thomas, Xurxo Costoya, Maite deCastro, Damián Insua-Costa, Martín Senande-Rivera, and Moncho Gómez-Gesteira

Spain has taken a significant stride towards its goal of installing 1 to 3 GW of floating offshore wind capacity by 2030. This was achieved through the implementation of a Maritime Spatial Planning (MSP) covering 19 designated areas, where it is expected the installation of offshore wind farms in the upcoming years. Therefore, it is of interest analysing the impact of climate change on offshore wind resource in these areas. To achieve a sufficiently high spatial resolution for this study, a dynamic downscaling of a multi-model ensemble from the 6th phase of the Coupled Model Intercomparison Project (CMIP6) was conducted using the Weather Research and Forecasting (WRF) model in the Spanish territorial waters, encompassing the Iberian Peninsula, Balearic Islands, and Canary Islands. Thus, wind data were obtained from the latest climate projections, with a 10-km spatial resolution and a 6-hour temporal resolution. The results were compared, for a historical period from 1985 to 2014, with data from the ERA5 reanalysis database and with observational data from buoys. The results of this validation process showed a great accuracy in the dynamical downscaling performed, generally better than when using data from the Coordinated Regional Climate Downscaling Experiment (CORDEX), which performed dynamical downscaling on data from several CMIP5 climate models. Future projections, from 2015 to 2100, were assessed under the Shared Socioeconomic Pathways (SSP) 2-4.5 and 5-8.5 scenarios. The findings of this study indicate a projected growth in Spain's offshore wind energy potential, especially in the Atlantic Ocean and around the Canary Islands.

Using wind speed data from simulations carried out with the WRF atmospheric model, the offshore wind energy resource was classified in the 19 areas involved in de Spanish MSP. This classification considered the wind power density but also factors such as resource stability, environmental risks, and installation costs. The results reveal significant diversity in wind resource classification within potential offshore wind farm areas, ranging from "fair" (3/7) to "outstanding" (6/7). The most promising areas for offshore wind farm development in the future are situated in the northwest of the Iberian Peninsula and the Canary Islands.

The identification of the most cost-effective solutions in each area involves determining the optimal combination of rated power and the number of turbines and comparing them across different locations to pinpoint the most economical sites for offshore wind energy exploitation. This economic analysis was done for a 25-year near-future period under the SSP 2-4.5 scenario, aligning with the expected operational lifespan of wind farms. This study includes the calculation of the Levelized Cost of Energy (LCOE) index, which gives an indication of the minimal price at which the electricity should be sold in order for the project to be profitable. The results highlight that the LCOE is lower for farms with a higher number of wind turbines featuring increased rated power. While the Canary Islands exhibit the most economically advantageous prices overall, other regions such as Galicia and Cataluña also boast promising areas.

How to cite: Thomas, B., Costoya, X., deCastro, M., Insua-Costa, D., Senande-Rivera, M., and Gómez-Gesteira, M.: Downscaling CMIP6 climate projections to classify the future offshore wind energy resource and calculate the Levelized Cost of Energy of various wind farm designs in the Spanish territorial waters., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-523, https://doi.org/10.5194/egusphere-egu24-523, 2024.

14:15–14:25
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EGU24-8655
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ERE2.5
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ECS
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On-site presentation
Encarni Medina-Lopez, Jasmina Lazic, and Latifa Yousef

Floating offshore solar farms (OSF) are an attractive option for solar energy generation, as they help avoid land competition with other uses. Planning the deployment of OSF requires assessments for site selection, which are primarily based on energy yields, in addition to other considerations. The yields are determined through evaluations using climate and oceanic variables. Uncertainty in these variables can propagate to further uncertainty in yield estimations, which ultimately can lead to significant consequences in the cost of energy. In this work, we propose the development of a novel method to assess the viability of OSF considering insolation uncertainty, with a focus on the United Arab Emirates (UAE) region. Open-source satellite data is utilized to conduct initial site assessments, and produce a set of viable locations based on parameters that include solar irradiance, ambient temperature, sea surface temperature, wind speed and precipitation. Validation of the viable locations will be done through the deployment of meteorological instrumentation, to collect in-situ measurements for a minimum of one year. Machine learning techniques are examined to quantify the uncertainty, followed by determination of impacts on levelized cost of electricity (LCOE) and savings based on uncertainty reduction.

How to cite: Medina-Lopez, E., Lazic, J., and Yousef, L.: Offshore Solar Farm Assessment and Uncertainty Determination for the United Arab Emirates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8655, https://doi.org/10.5194/egusphere-egu24-8655, 2024.

14:25–14:35
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EGU24-6025
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ERE2.5
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ECS
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On-site presentation
Arianna Leoni, Nicolò Stevanato, Angelo Carlino, Andrea Francesco Castelletti, and Matteo Giuliani

Development pathways for Sub-Saharan Africa project a substantial increase in population and living standards and, correspondingly, in the regional energy demand. To accommodate future energy needs, power and energy system communities have been developing least-cost optimization models to support long-term transformational energy system planning and the transition to carbon neutrality at the African continental scale.  

However, these models usually focus on annual or seasonal energy balances and overlook higher time resolution dynamics that can actually lead to short but impactful events when considering the expansion of renewable energy share. Indeed, the variability of renewable generation and power demand can lead to significant risks, including elevated electricity prices, transmission line overload, and power generation deficits. 

In this work, focusing on the Southern African Power Pool, we couple an energy system planning model, OSeMOSYS-TEMBA, and a power system model, PowNet, to obtain higher temporal resolution characterization of the energy system evolution in the future.

 OSeMOSYS-TEMBA is a long-term energy system planning model producing cost-optimal trajectories of capacity expansion for different technologies for all the countries in continental Africa with a seasonal resolution from 2015 to 2070. Yet, OSeMOSYS-TEMBA is not resolved enough to account for power grid reliability under high penetration of renewables, where flexible operations and power grid reliability are crucial, and might substantially affect model projections.

PowNet is a least-cost optimization model running on an annual horizon with hourly resolution and optimizes the dispatch of power from each source as well as the usage of transmission lines, constrained to the power capacity available according to the long-term energy planning provided by the OSeMOSYS-TEMBA model. We assess the difference in generation mix, the impact on transmission lines overloading, power generation deficits in 2030 under three climate policy scenarios: no climate policy, and constrained to 2.0°C and 1.5°C warming constraining emissions to a consistent pathway. 

Results indicate power generation deficits and transmission lines overloading are observed in many countries, especially during the night. These impacts are to be associated with insufficient total power system capacity to meet power demand due to the low time and spatial resolution of the energy system model. Indeed, the increased dependency on variable renewable resources, and a higher resolution demand profile emphasize the need to further expand total capacity, the importance of flexible generation adopting a diverse energy portfolio, and the potential benefits of increasing transmission lines’ capacity. Finally, the storage of unused water for future power generation within the available reservoirs might potentially reduce the power deficit. These results show the importance of the assumptions embedded in the energy system model and motivate methodological improvements to design coupled energy and power system pathways that remain reliable at high spatial and time resolution.



How to cite: Leoni, A., Stevanato, N., Carlino, A., Castelletti, A. F., and Giuliani, M.: From multi-decadal energy planning to hourly power dispatch: evaluating the reliability of energy projections in the Southern African Power Pool, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6025, https://doi.org/10.5194/egusphere-egu24-6025, 2024.

14:35–14:45
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EGU24-1851
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ERE2.5
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ECS
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Virtual presentation
Jan Wohland, Peter Hoffmann, Daniela C.A. Lima, Marcus Breil, Olivier Asselin, and Diana Rechid

Humans change the climate in many ways, for example, by emitting greenhouse gases or by changing land-use. While studies typically investigate the joint effects of human activity, we here isolate the impact of afforestation and deforestation on winds in the lowermost 350 m of the atmosphere to better understand the role of forests in large-scale wind energy assessments. We use vertically resolved sub-daily output from two regional climate models and compare two extreme scenarios from the LUCAS simulations (Davin et al., 2020). Our results show that afforestation lowers wind speeds by more than 1 m/s in many locations across Europe even 300 m above ground and thus matters at wind turbine hub heights. While adapting the parameters in standard extrapolation allows to capture long-term mean winds well, it remains insufficient to compute wind energy potentials as it fails to capture essential spatio-temporal details, such as changes in the daily cycle. We therefore follow an alternative approach that leverages the vertical resolution of the regional climate models to account for wind profile complexity. Doing so, we report strong changes in wind energy capacity factors due to afforestation and deforestation: they change by up to 50 % in relative terms. Our results confirm earlier studies that land use change impacts on wind energy can be severe and that they are generally misrepresented with common extrapolation techniques.

 

References:

Davin, E. L., Rechid, D., Breil, M., Cardoso, R. M., Coppola, E., Hoffmann, P., Jach, L. L., Katragkou, E., de Noblet-Ducoudré, N., Radtke, K., Raffa, M., Soares, P. M. M., Sofiadis, G., Strada, S., Strandberg, G., Tölle, M. H., Warrach-Sagi, K., and Wulfmeyer, V: Biogeophysical impacts of forestation in Europe: First results from the LUCAS Regional Climate Model intercomparison, Earth Syst. Dynam., 11, 183–200, 2020, https://doi.org/10.5194/esd-11-183-2020, 2020

Preprint:

Wohland, J., Hoffmann, P., Lima, D. C. A., Breil, M., Asselin, O., and Rechid, D.: Extrapolation is not enough: Impacts of extreme land-use change on wind profiles and wind energy according to regional climate models, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2533, 2023

How to cite: Wohland, J., Hoffmann, P., Lima, D. C. A., Breil, M., Asselin, O., and Rechid, D.: Impacts of extreme land-use change on wind profiles and wind energy according to regional climate models  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1851, https://doi.org/10.5194/egusphere-egu24-1851, 2024.

14:45–14:55
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EGU24-5810
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ERE2.5
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ECS
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Highlight
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On-site presentation
Irem Isik Cetin, Thomas Frisius, Elke Keup-Thiel, and Diana Rechid

Wind energy has become one of the most important mitigation options for climate change over the last decades. However, variability and availability of wind are also expected to be changed due to climate change. For this purpose, the KliWiSt project has been initiated to determine the influence of climate change on wind energy site assessments in Germany. Within the scope of the project, many aspects of climate change impacts on wind energy have been studied to determine uncertainties about the topic and to develop recommendations for actions. Although there are many studies in literature which evaluate the effects of climate change on wind in the upcoming decades, low wind events are scarcely investigated so far. However, low wind events pose a risk for achieving long term renewable energy targets and ensuring stability of the electricity grids. Wind drought is increasingly becoming a significant phenomenon which determines low wind energy production due to extreme low wind resources.

In this study, we have investigated the frequency of low wind events in Germany due to climate change until the end of the 21st century by using an ensemble of high-resolution regional climate model simulations available from the EURO-CORDEX initiative. We also evaluated the performance of the regional climate models with data from different observation stations and with re-analysis data sets. For our investigation we used thresholds of 2 m/s and 3 m/s for wind speed at 10 m and 100 m – respectively for – calculating “calm wind” climate indices. The threshold is determined as 3 m/s (at 100 m height) for low wind events since most of the wind turbines starts wind energy production at this value (“cut in” wind speed). We used two different benchmark data sets (ERA5 and CERRA) to determine historical variation of “calm days” over Germany and to evaluate the performance of the high-resolution regional climate models. Moreover, seasonal, annual, and spatial distributions of low wind events are investigated for Germany where the country has already a high installed wind energy capacity and ambitious renewable energy targets. The study aims to determine trend and frequency of low wind events in the past and future at different terrain conditions at different time scales from different regional climate models. The anticipated results of the study and the project are expected to give insight for policy makers and stakeholders from the renewable energy sector.* 

*This study is part of the project "The influence of climate change on wind energy site assessments (KliWiSt)" which is funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK).

How to cite: Isik Cetin, I., Frisius, T., Keup-Thiel, E., and Rechid, D.: Investigation of low wind events over Germany from high resolution regional climate models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5810, https://doi.org/10.5194/egusphere-egu24-5810, 2024.

14:55–15:05
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EGU24-6374
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ERE2.5
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Virtual presentation
M. Yolanda Luna, Javier Díaz-Fernández, Alonso García-Miguel, Carlos Calvo-Sancho, Ricardo Castedo, José J. Ortega, Pedro Bolgiani, Mariano Sastre, and María Luisa Martín

The wind resource in the Iberian Peninsula has been analyzed using wind climate projections from the XX century to the end of the XXI century of the SSP5-8.5 scenario obtained from the MRI-ESM2.0 global climate numerical model. Six-hour wind speed and direction are seasonally grouped and from them, both the production of electrical power and the intensity of wind energy have been estimated throughout the temporal record. Two periods are considered in the dataset: the historical (1950 – 2014) and the future (2015-2100) periods. The non-parametric Mann-Kendall trend test is applied to identify significant wind energy intensity trends and the non-parametric Mann-Whitney test is applied over the entire domain's all-grid points to statistically evaluate the significant differences between wind energy intensity of different time periods. For an estimation of the evolution of the electrical power throughout the XXI century, the latest generation wind turbine SG 7.0-170 from Siemens-Gamesa has been used as a reference. Considering winter as the season of maximum wind energy production, the results show a future higher electricity production compared to the selected historical period in almost the entire Iberian Peninsula, although there is a decreasing production trend throughout the century. The remainder seasonal results indicate a general drop in electrical power due to a decrease of wind resource in the whole Peninsula throughout the century, especially in autumn with significant losses of more than 2 MW of electricity production in many Portuguese areas on the western coast of the peninsula.

How to cite: Luna, M. Y., Díaz-Fernández, J., García-Miguel, A., Calvo-Sancho, C., Castedo, R., Ortega, J. J., Bolgiani, P., Sastre, M., and Martín, M. L.: A wind energy resource analysis in the Iberian Penindula under climate projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6374, https://doi.org/10.5194/egusphere-egu24-6374, 2024.

15:05–15:15
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EGU24-7974
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ERE2.5
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On-site presentation
James Fallon, David Brayshaw, John Methven, Kjeld Jensen, and Louise Krug

Critical infrastructure, such as telecommunications networks and hospitals, are in many cases required to have reserve power systems in place, mitigating transmission network failures and protecting against national power grid outage. A previous case study of Great Britain (GB) telecommunications assets implemented a temperature-driven model of infrastructure electricity demand (Fallon et al., 2023), used to plan reserve capacity installation sufficient to meet the highest anticipated 5-day periods of energy consumption (or other regulatory targets). Extending this work with climate models (UKCP18), we demonstrate that the capacity planning framework reliant upon reanalysis observations underestimates capacity installation appropriate to meet historic weather risk, while assessments are improved using historic period climate model outputs. Additionally, climate projections simulating future periods support further upgrading the installed reserve capacity beyond historic requirements.

Quantile-correcting bias adjustments of climate model outputs can address significant discrepancy between the model world and observations temperature distributions across the historic period (model timespan where global climate matches recent observations). Uncorrected, this climate model error leads to an exaggerated frequency of extreme temperature events, hence overestimating the reserve capacity requirement. But under a quantile-correcting approach, assuming a consistent underlying representation of the weather dynamics, the temperature distribution is adjusted to match the reanalysis distribution.

Temperature delta-shifts are calculated to represent the GB historic period climate variability observed across model ensemble members. The resulting infrastructure electricity demand timeseries are compared against timeseries produced from historic period temperature data adjusted by quantile delta mapping, demonstrating that reanalysis data alone is insufficient to capture the greater reserve capacity requirements predicted by quantile delta-mapping of climate model outputs in the historic time period.

Using future period climate model outputs, we compare three alternative treatments of model temperature timeseries simulating future climate: a delta-shift adjustment of reanalysis data, a regional trend-preserving mean bias adjustment, and quantile delta mapping. In each case, reserve capacity requirements increase (5% to 10% increase in a world 2.0°C above pre-industrial temperatures). There is significant variability across different model ensemble members, and sensitivity to individual weather years.

Reserve system operators can use the approaches outlined to make an informed assessment of the need for upgrading or installing new reserve systems, ensuring the stability and resilience of critical infrastructure assets. The consistent trajectories across different approaches and model ensemble members may improve confidence in results, whilst individual model ensemble members can be investigated to identify potential ‘worst case’ outcomes.

How to cite: Fallon, J., Brayshaw, D., Methven, J., Jensen, K., and Krug, L.: Simulating Reserve Power Systems in Future Climates: Bias Adjustment Approaches for Regional Climate Projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7974, https://doi.org/10.5194/egusphere-egu24-7974, 2024.

15:15–15:25
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EGU24-8178
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ERE2.5
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ECS
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On-site presentation
Bram van Duinen, Lieke van der Most, Michiel Baatsen, and Karin van der Wiel

The European electricity system is becoming increasingly dependent on weather conditions, which influence both electricity demand and production. Non-linear dependence of the electricity system on the weather conditions can lead to energy droughts – high demand coinciding with low renewable energy production – even under non-extreme meteorological conditions. Weather conditions driving energy droughts can transcend national boundaries, which leads to the possibility that multiple countries experience concurrent energy droughts, potentially leading to a widespread energy crisis. We examine the interplay between large-scale weather conditions and the risks of co-occurrence and opportunities of disjoint occurrence of energy droughts in renewable electricity systems in European countries. We analyse 1600 years of modelled energy data against meteorological conditions from large ensemble climate model simulations to identify patterns of co-variability of energy droughts in the present-day climate.

We find a strong spatial variability in the risk for concurrent energy droughts within Europe, depending on a country’s renewable energy mix and the region's response to specific large-scale meteorological patterns (weather regimes). Some countries, such as Latvia and Slovenia, mostly experience energy droughts isolated from their neighbouring countries. However, we also find clusters of countries that experience concurrent energy droughts. This is the case for the North Sea region, and many countries in central/eastern Europe. Here, there is limited potential for cooperation, putting these countries more at risk of energy crises. Finally, we differentiate between moderate and extreme energy droughts, which have different co-occurrence signatures. This implies that an interconnected electricity grid has potential to resolve some moderate events, but is less effective in the extreme events.

How to cite: van Duinen, B., van der Most, L., Baatsen, M., and van der Wiel, K.: Strength of co-variability of energy droughts highly region dependent , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8178, https://doi.org/10.5194/egusphere-egu24-8178, 2024.

15:25–15:35
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EGU24-17572
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ERE2.5
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On-site presentation
Ana Lopez, Kai Lochbihler, and Gil Lizcano

The deployment of low carbon affordable energy generation technologies plays a crucial role to achieve the Paris Agreement long-term goal to reduce global greenhouse gas emissions to limit global temperature increase well below 2ºC above pre-industrial levels, and pursue efforts to limit it to 1.5º C above pre-industrial levels. In particular wind power installed capacity is projected to increase exponentially over the next few decades. Wind power generation is, however, weather-dependent. Therefore, understanding the variability of wind, how it might be affected by climate change, and how this affects the economics of wind projects seems vital as countries continue to invest in wind energy.

At the global level, the last IPCC report (IPCC AR6 WGIII, 2022) states that the climate change impact on future wind resources will be limited. Regional studies, however, show that wind resources are projected to increase for instance over Northern Europe and decrease over Southern Europe. In North America, various studies have low agreement for the changes on future resources, in part because the inter-annual variability is larger than the projected changes due to climate change. For South America, some studies find increases in wind resources in windy areas. In general, the compounding of the anthropogenic climate change signal with high spatial and temporal wind variability can lead to large uncertainties in the projected impacts of climate change on wind resources, and as a result, on the economics of a project. 

In this study we showcase a methodology to analyze the impact of climate change on the economic indicators of a portfolio of wind farm projects across Europe. Projections of changes in wind resources are obtained using an ensemble of Coupled Model Intercomparison Project 6 (CMIP6) global climate models statistically downscaled to correct biases and increase the spatial resolution. Uncertainties in climate projections are taken into account by considering an ensemble of climate models and different emissions scenarios as represented by the Shared Socioeconomic Pathways (SSPs) . A series of assumptions about the features of a representative wind farm and its key economic parameters (e.g. capital expenditures and operational costs) are made to compute two common economic indicators: the Internal Rate of Return (IRR) and the Levelized Cost of Energy (LCOE).

By varying the production following the different climate scenarios, we analyze the impacts of climate change on the economics of the portfolios for different time horizons in the future. We find that the effect of changes of resource on IRR and LCOE depend on the region, emissions scenario and projection period. In the short term, changes are often masked by the internal variability of the resource on the site.

We also discuss, from the point of view of our role as climate services provider for the wind industry, the limitations of the data provided in the CMIP6 experiment, and some of the data needs we have identified.

How to cite: Lopez, A., Lochbihler, K., and Lizcano, G.: Uncertainties in climate projections and the economics of wind farm portfolios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17572, https://doi.org/10.5194/egusphere-egu24-17572, 2024.

15:35–15:45
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EGU24-18490
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ERE2.5
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ECS
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On-site presentation
Vera van der Veen, Sanita Dhaubanjar, Sonu Khanal, and Walter Immerzeel

With steep elevation gradients and an abundance of water, Nepal is one of the leading countries in hydropower capacity. This potential is largely unutilised; representing a significant untapped renewable energy resource that could help Nepal achieve its emissions target and improve its energy security. However, future climate projections suggest changes in discharge seasonality, which will impact the hydropower potential. Hence, we provide an estimate of current and future theoretical hydropower potential in the four large basins in Nepal, namely Mahakali, Karnali, Gandaki, and Koshi. We use current and future discharge simulated in the Spatial Processes in Hydrology (SPHY) model from a previous study to force the theoretical potential module in the Hydropower Potential Exploration (HyPE) model. The HyPE model set up for Nepal is run for 48 combinations of future climate scenarios, combining temperature change in the range of 3°C to 8°C and precipitation change in the range of -30% to 40%. Average monthly discharge components (baseflow, rainfall runoff, snowmelt, and glacier melt) are analysed separately for the reference period (1979-2018), mid-century (2036-2065), and end of century (2071-2100). For each time horizon, we evaluate the relative contribution of the discharge components to the theoretical hydropower potential and quantify the impact of future changes in discharge seasonality.

 

The Indian summer monsoon dominates the discharge patterns in Nepal. The historical water balance shows an overlap in the peak contributions from rainfall and glacier melt to discharge with both occurring in July and August. A shift in the peaks from these components is not apparent for the climate scenarios considered. However, the peak from snow melt contribution shifts one to two months earlier for most climate scenarios in all basins. Such shift in the seasonal discharge composition could prove promising for stabilizing year-round hydropower generation. At 5 km resolution, we estimate the total theoretical hydropower potential for the four Nepalese basins to be 1170 TWh/yr during the reference period. While challenges remain in accurately simulating discharge in mountainous and data-scarce basins in Nepal contexts using SPHY, the majority of the projections suggest a promising increase in the monthly average discharge and the subsequent monthly theoretical hydropower potential. We observe an increase in total Nepalese hydropower potential up to 22% for the mid-century and 36% by the end of the century. Variations across the basins occur and a decrease in hydropower potential is also observed for the dry future climate scenarios. However, it is important to note that theoretical potential may not be a realistic indicator for hydropower development. Only a small part of the theoretical potential may be technically and financially feasible and an even smaller part may be sustainable. Nonetheless, our research provides a first step to the identification of hydropower project sites considered within the context of a changing climate.

How to cite: van der Veen, V., Dhaubanjar, S., Khanal, S., and Immerzeel, W.: The Nepalese theoretical hydropower potential in a changing climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18490, https://doi.org/10.5194/egusphere-egu24-18490, 2024.

Posters on site: Fri, 19 Apr, 10:45–12:30 | Hall X4

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Display time: Fri, 19 Apr 08:30–Fri, 19 Apr 12:30
X4.153
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EGU24-2418
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ERE2.5
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ECS
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Sushovan Ghosh, Dilip Ganguly, and Sagnik Dey

India aspires to increase its reliance on renewable energy sources to fulfil its climate commitments. Among renewables, Solar Photovoltaic (SPV) energy has grown rapidly around the world, including in India. However, little is known about how solar dimming and global warming may affect solar power over the region in the future. The production of SPV energy is influenced by meteorological parameters, highlighting the concerns related to grid stability, intermittency, and reliability caused by weather-induced variability.  

Under the Paris Agreement, all the nations agree to restrict the global warming to “well below” 2°C above pre-industrial levels and, if possible, “pursue” efforts to limit warming at 1.5°C. Therefore, it is imperative to understand future climate change and their spatial heterogeneity at 1.5°C and 2°C warming for developing  strategies for renewables.

This research examines the distribution and variability of India's solar resources by utilising state-of-art global climate models from Coupled Model Intercomparison Project phase 6 (CMIP6) and CMIP6 - NASA Earth eXchange Global Daily Downscaled Projections (NEX-GDDP). The analysis of global mean temperature changes reveals that the 2030s and 2040s will be the decade when majority CMIP6 models reach 1.5°C and 2°C warming under SSP2-4.5 (intermediate emission pathways) and SSP5-8.5 (high emission) scenarios respectively with respect to  pre-industrial period (1850–1900).

We find that under the intermediate (high) emission scenarios, the annual mean surface solar radiation over the Indian landmass will decrease by -8±3 Wm-2 (-5±2 Wm-2) relative to the baseline period (1985-2014) at 1.5°C global warming. An additional 0.5°C of warming (at a global warming level of 2°C) results in a comparatively smaller decline in surface solar irradiance with respect to baseline under both scenarios. At 1.5°C and 2.0°C global warming, most regions are anticipated to experience an increase in surface irradiance under the SSP5-8.5 scenario, as compared to SSP2-4.5. The magnitude and direction of change of aerosols, clouds and associated meteorological parameters needs to be explored further. 

This research will contribute to crucial planning and decision-making processes concerning India and other nations with similar interests.

How to cite: Ghosh, S., Ganguly, D., and Dey, S.: Assessing the future solar resources over India at 1.5°C and 2°C warming worlds, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2418, https://doi.org/10.5194/egusphere-egu24-2418, 2024.

X4.154
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EGU24-2672
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ERE2.5
Chang Kim, Hyungoo Kim, and Jin Young Kim

This study assesses the reliablity of CMIP6 models in projecting solar irradiance, a crucial aspect of climate dynamics. While extensive scrutiny has been given to historical data from 1975 to 2000, our primary focus is directed towards assessing the models' performance from 2010 to 2020 and their predictive efficacy for the future. Through a meticulous methodology involving statistical comparisons, validation against measurements, and consideration of external factors, we found that CMIP6 models commendably aligned with observed solar irradiance during the historical period, showcasing their adeptness in replicating past climate conditions. However, an in-depth analysis of the recent decade unveiled deviations from observed solar irradiance, prompting concerns regarding the models' adaptability to the swift pace of contemporary climate change. Shifting our gaze to the prospective view, we explore the models' robustness in adapting to emerging climatic trends and emphasize the necessity of continuous refinement, incorporation of real-time data, and a comprehensive understanding of external factors to enhance accuracy in future predictions. Rapid climate change introduces uncertainties such as aerosol concentrations, greenhouse gas emissions, and solar variability, posing challenges that necessitate constant model adjustment. The implications for climate change mitigation are significant, as reliable solar irradiance predictions inform decisions on renewable energy adoption, agriculture planning, and climate adaptation measures. In conclusion, this study bridges the gap between historical evaluations and future projections, providing valuable insights for policymakers, researchers, and stakeholders invested in mitigating the impact of climate change. Continuous refinement of CMIP6 models and a holistic approach to understanding external factors are crucial for building a robust foundation in addressing the challenges posed by climate change in the coming decades.

How to cite: Kim, C., Kim, H., and Kim, J. Y.: An Evaluation of Solar Irradiance Projected by CMIP6 Models Toward Long-Term Projection of Climate Change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2672, https://doi.org/10.5194/egusphere-egu24-2672, 2024.

X4.155
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EGU24-5874
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ERE2.5
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ECS
Alexander Chamberlain-Clay and Elisabeth Thompson

The ERA5 reanalysis is established as a key source of gridded wind-speed information for much of the world, having better performance and higher resolution (30km) than other reanalysis products. It’s used as a source of truth for driving wind-power models, and verifying ML predictions, especially in the absence of observational measurements. However, verification of ERA5 has mostly focused on Europe and the northern hemisphere, not examining performance in low-observation regions such as East Africa, where wind power investment and green energy provision is crucial to climate goals. As part of the FOCUS-AFRICA project, this study investigates how well the ERA5 reanalysis represents the climatology of 19 different observation sites in Tanzania and compares them to 3 CORDEX-Africa models driven by ERA-Interim at a similar resolution to ERA5, and one convection-permitting 4.4km resolution model (CP4A). ERA5 is shown to perform poorly at representing inland wind climatologies in Tanzania, with Perkins skill scores of 0.21-0.62 (1 is perfect), in comparison to European inland stations showing an average a score of ~0.8 in previous studies. This is caused by underestimations of mean wind speed compared to observations for inland sites.  The CP4A model performs best with scores of 0.54-0.79, despite the fact this model is not forced by real-world conditions.

These results show the need for caution when using ERA5 as a basis for any wind resource assessment or model validation. It also indicates that wind resource in East Africa may be underestimated, which would have negative impacts on investment decisions in the region. 

How to cite: Chamberlain-Clay, A. and Thompson, E.: Comparing ERA5 and model data to observations for wind resource assessment – a case study from Tanzania , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5874, https://doi.org/10.5194/egusphere-egu24-5874, 2024.

X4.156
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EGU24-7322
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ERE2.5
Seon Tae Kim

This study presents the impact of climate change on the wind and solar power generation potentials over South Korea considering ensemble projections from downscaled high-resolution bias-corrected future climate change scenario data. Under future global warming, solar power potentials over South Korea are projected to decrease in spring (March-May) and winter (December-February) seasons relative to present climate in the late 21st century (2081-2100), particularly showing a relatively large decrease in the northern part of South Korea. The decrease tendency is more significant and larger in the high-CO2 emission scenario (SSP5-8.5) than the low-CO2 emission scenario (SSP2-4.5). The projected decrease in solar power potential in spring is mainly due to increased air temperature by future global warming and the decrease in winter is attributable to the projected increase in the air temperature and the decrease in solar radiation at the surface. Wind power potentials which are estimated with the wind energy density is generally projected to decrease with future global warming in all seasons except for summer. This decrease tendency is also larger in the late 21st century of the SSP5-8.5 scenario, especially over the southern part of South Korea in winter and spring and over the northern part in fall. These results may help optimize the regional renewable energy generation system development and plans

How to cite: Kim, S. T.: Changes in Solar and Wind Power Generation Potentials over South Korea under Future Global Warming., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7322, https://doi.org/10.5194/egusphere-egu24-7322, 2024.

X4.157
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EGU24-15943
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ERE2.5
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ECS
Giacomo Falchetta, Adriano Vinca, Gregory Ireland, Marta Tuninetti, André Troost, Manfred Hafner, Edward Byers, and Ackim Zulu

Multi-dimensional and overlapping Nexus challenges affect many parts of rural sub-Saharan Africa. More than 90% of cropland is rainfed, less than one third of households have electricity at home, more than 15% of people report insufficient food intake and more than 40% of people live below the poverty line. Climate change impacts on vulnerable systems with limited adaptive capacity and strong population growth are increasing the magnitude of the challenge. As a result, there is a strong need for multi-level, multi-sector interventions (from national policies to regional/river basin-scale planning, to local planning and investment). To implement such actions, it is key to assess solutions (technology and investment) and appraise their feasibility and implementation potential (from both a policy and a financial point of view). In this study, we soft-link bottom-up process-based water and energy demand and techno-economic infrastructure assessment models into a multi-node, national Nexus-extended Integrated Assessment Model (MESSAGEix-Nexus) for supply and investment assessment. Based on the integrated modelling, we obtain an understanding of the role of an explicit consideration of (productive) energy access jointly with Water-Agriculture-Food interlinkages for rural Nexus infrastructure requirements, investment, and sustainable development objectives. This demonstrates how climate impacts and water and energy needs affect each other and jointly shape infrastructure and investment pathways. Then, by linking technical models with business models analysis, we are able to assess feasibility of implementation and appraise which are the key micro and macro determinants to ensure feasibility, investment, and uptake of small-scale Nexus infrastructure, crucial for rural development and adaptation to changing climate conditions. Altogether, our research demonstrates how national-scale integrated modelling with an explicit focus on Nexus interlinkages allows for assessing locally-relevant demand sources and investment needs, and their implications for sustainable development. In turn, this allows for deriving  policy and investment-relevant insights.

How to cite: Falchetta, G., Vinca, A., Ireland, G., Tuninetti, M., Troost, A., Hafner, M., Byers, E., and Zulu, A.: Achieving renewable energy-centered sustainable development futures for rural Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15943, https://doi.org/10.5194/egusphere-egu24-15943, 2024.

Posters virtual: Fri, 19 Apr, 14:00–15:45 | vHall X4

The posters scheduled for virtual presentation are visible in Gather.Town. Attendees are asked to meet the authors during the scheduled attendance time for live video chats. If authors uploaded their presentation files, these files are also linked from the abstracts below, but only on the day of the poster session. The button to access Gather.Town appears just before the time block starts. Onsite attendees can also visit the virtual poster sessions at the PICO spot in the corresponding on-site poster hall (e.g. virtual posters of vHall X4 are visible at PICO spot 4).
Display time: Fri, 19 Apr 08:30–Fri, 19 Apr 18:00
vX4.38
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EGU24-11262
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ERE2.5
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ECS
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Highlight
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Anasuya Gangopadhyay, Rajat Masiwal, and Ashwin K Seshadri

Decarbonizing electricity grids across the world will be increasingly impacted  by systematic seasonal variation in wind speed and solar irradiance as well as seasonally varying patterns of demand, more so in the context of progressive decarbonization of energy services such as winter heating. These seasonal variations are governed by local meteorology which also has large-scale manifestations impacting entire electricity grid systems. Using ERA5 reanalysis, we quantify the amplitude of seasonality in wind speed and solar insolation across the world and consider the impacts on grid scale generation. Owing to effects of seasonal evolution of solar insolation as well as the seasonal cycle of cloudiness, the seasonal cycle amplitude for solar insolation at the surface is much larger in higher latitudes. For horizontal winds, high seasonal amplitudes are experienced in global tropical monsoon regions and higher latitudes associated with meridional shifts in mid-latitude zonal winds. In general, wind power availability is much higher in high-latitude winters.

Seasonal weather variation also drives electricity demand for heating and cooling, which is a major part of the total electricity consumption of many regions. While many large electricity consumers including China, US, India, and Brazil experience peak electricity consumption during summer, most European countries have higher demand during winter, giving a double peak structure for global monthly electricity demand. Many large electricity consuming countries experience nearly 40 percent variation in electricity demand between seasons. Solutions to bridge large seasonal variations in demand and generation, e.g. bulk energy storage, excess of wind and solar capacity, renewable portfolio design, and demand-side management present critical challenges.

This paper will consider whether a portfolio of such solutions is adequate to balance seasonal variability in supply and demand. We will characterize the main patterns of seasonal load variability across countries, explore whether within-country wind and solar variability are well matched with these patterns, and consider the role of excess capacity and storage in bridging the gaps, in context of limitations of seasonal-scale demand side management. Bridging seasonal-scale gaps and mitigating the impacts of various manifestations of seasonality remains an important roadblock towards net zero electricity systems worldwide, and we will survey the most promising solutions to this challenge.

How to cite: Gangopadhyay, A., Masiwal, R., and K Seshadri, A.: Balancing seasonality in decarbonising electricity systems worldwide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11262, https://doi.org/10.5194/egusphere-egu24-11262, 2024.