ERE2.2 | Spatial and temporal modelling of renewable energy systems
EDI
Spatial and temporal modelling of renewable energy systems
Convener: Luis Ramirez Camargo | Co-conveners: Johannes Schmidt, Marianne Zeyringer
Orals
| Wed, 26 Apr, 14:00–17:55 (CEST)
 
Room 0.96/97
Posters on site
| Attendance Wed, 26 Apr, 08:30–10:15 (CEST)
 
Hall X4
Posters virtual
| Attendance Wed, 26 Apr, 08:30–10:15 (CEST)
 
vHall ERE
Orals |
Wed, 14:00
Wed, 08:30
Wed, 08:30
This session addresses spatial and temporal modelling of renewable energy systems, both in a prospective as well as in a retrospective manner. Therefore, contributions which model the characteristics of future renewable energy systems are equally welcome as contributions which assess the characteristics of the past performance of renewable energies. Session contributions may reach from purely climate based assessments of simulated renewable generation time series, over assessments of land use to full energy system models used to better understand energy systems with high shares of renewables.

Studies may for instance:
Show the spatial and temporal variability of renewable energy sources, including resource droughts and complementarity between technologies and locations.
Derive scenarios for the spatial allocation of renewable energies based on climatic, technical, economic, or social criteria.
Assess past spatial deployment patterns of renewables.
Assess past impacts on land cover and land-use, including impacts on biodiversity and other environmental indicators.
Derive integrated scenarios of energy systems with high shares of renewables (Including systems from the local scale e.g. in form of local Energy Communities to the national or continental scale).

The objective of the session is to provide an insight into recent advances in the field of renewable energy system modeling. The session welcomes research dedicated to climatic and technical issues, environmental impact assessments, and policy-making, forecasting and real time applications concerning renewable energy systems.

Full papers can be submitted along with the abstract to a dedicated topical collection in the ISPRS International Journal of Geo-Information.

Orals: Wed, 26 Apr | Room 0.96/97

Renewable resource availability and droughts
14:00–14:05
14:05–14:25
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EGU23-10896
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ECS
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solicited
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On-site presentation
Jonathan Minz, Axel Kleidon, Marc Imberger, Oliver Branch, Jake Badger, and Volker Wulfmeyer

Energy scenarios envision installation of up to 230 GW of wind capacity over available areas within the German onshore by 2050. The associated technical wind energy potential is typically derived assuming that the electricity generated by the wind turbines does not affect the wind resource. Consequently, future capacity factors, the ratio of generation to installed capacity, are implicitly assumed to be independent of the extent to which the wind resource is depleted. However, capacity factors reduce as wind capacity is increased. This is because kinetic energy (KE) removal lowers wind speeds that result in lower generation from the turbines. To assess the relevance of this resource depletion effect on capacity factors, we simulated electricity generation by wind turbines with a range of hypothetical and planned deployment scenarios using the Weather Research and Forecasting (WRF) model that incorporates the effects of atmosphere - turbine interactions and compared these to estimates derived from a simple, momentum-balance approach (VKE). Despite potential biases in modelled wind speeds, we find that for a typical planned scenario of ~200 GW deployed over 13.8% of land area, mean annual wind speeds reduce by an average of 0.4 m s-1 compared to the case where the impact of atmospheric - turbine interactions is excluded. Associated reductions in capacity factor are up to 20% in regions of high installed capacities. To isolate the key atmospheric influence, we compare the simulated range of wind speeds and capacity factors with those from the VKE model that only accounts for KE removal effects. We find that the KE removal effects play the dominant role in shaping the reductions in wind speeds and capacity factors, thus providing a simple tool to capture these effects.  We conclude that with increased deployment of wind energy in the context of the energy transition, these wind resource depletion effects need to be taken into account, but this can be done in a comparatively simple and physical way.

How to cite: Minz, J., Kleidon, A., Imberger, M., Branch, O., Badger, J., and Wulfmeyer, V.: Evaluating the physical limits to technical wind energy potential over onshore Germany in 2050, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10896, https://doi.org/10.5194/egusphere-egu23-10896, 2023.

14:25–14:35
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EGU23-7150
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ECS
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On-site presentation
Idunn Aamnes Mostue, Marianne Zeyringer, Trude Storelvmo, and David Ruiz Baños

In a rapidly changing climate, changes in the frequency and intensity of future extreme weather events is expected to pose complex impact on future
weather-dependent energy systems. The contribution by Working Group I to the latest IPCC report (AR6) includes for the first time a dedicated chapter
on weather extremes. It demonstrates that even relatively small incremental increases in global mean temperature (+0.5C) cause statistically significant
changes in extremes on the global scale and for large regions. In 2021, Europe experienced the worst wind drought in 60 years, followed by extreme heatwave episodes and a national daily maximum temperature record of 40.3C in the UK in 2022.

The transition of the energy sector to renewable energy is key to reach the Paris Agreement goal of limiting global warming, but this also increases the energy sector’s exposure to future weather extremes in a changing climate. The impacts of climate variability and climate change on present and near future national energy systems are increasingly well documented within the literature. However, within this interdisciplinary field of research there has been little attention on impacts of extreme weather events on the energy system operations. Modellers usually use historic weather data and therefore do not consider ”new” extreme weather risks, posing problems on both the operational and infrastructural side. Omitting those risks can lead to designing systems that are operationally inadequate, i.e. prone to (long) power outages leading to major social, economic and health consequences.

The present work aims to study the variability of renewable energy generation for weather years under different future climates over Europe. We will use different future climate scenarios from the Coupled Model Intercomparison Project 6th Phase (CMIP6), to assess future projections of wind energy capacity factors. The global datasets of climate data will be adapted for Europe where we will interpolate the wind speed based on model-level raw data and further create energy capacity factors. We expect this study to be a first step in exploring the future changes in and occurrences of extreme weather events, and how these will impact the generation of renewable energy over Europe. This will in turn contribute to the knowledge on how we can plan for climate resilient renewable energy systems robust to future extreme weather events over Europe.

How to cite: Mostue, I. A., Zeyringer, M., Storelvmo, T., and Ruiz Baños, D.: Future projections of wind energy capacity factors over Europe using CMIP6, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7150, https://doi.org/10.5194/egusphere-egu23-7150, 2023.

14:35–14:45
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EGU23-13862
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ECS
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On-site presentation
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Franziska Schöniger, Gustav Resch, Demet Suna, Florian Hasengst, Nicolas Pardo-Garcia, Gerhard Totschnig, Herbert Formayer, Philipp Maier, David Leidinger, and Imran Nadeem

Motivation

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.

Method

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).

The following weather-dependent generation and demand profiles are generated:

  • E-heating, e-cooling, and e-mobility charging demand (dependent on temperature)
  • Photovoltaics generation (dependent on radiation, losses dependent on temperature)
  • Wind generation (dependent on wind speed)
  • Hydro generation (dependent on hydro inflow)

Results and conclusions

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.

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.

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).

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.

Funding

The project SECURES is funded by the Climate and Energy Fund (Klima- und Energiefonds) under project number KR19AC0K17532.

How to cite: Schöniger, F., Resch, G., Suna, D., Hasengst, F., Pardo-Garcia, N., Totschnig, G., Formayer, H., Maier, P., Leidinger, D., and Nadeem, I.: The impact of climate change on future electricity generation and demand patterns in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13862, https://doi.org/10.5194/egusphere-egu23-13862, 2023.

14:45–14:55
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EGU23-7130
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ECS
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On-site presentation
Guillermo Valenzuela-Venegas and Marianne Zeyringer

Chile has proven to be a country with great potential for renewable energies, favoring in the last decades the development of renewable energy projects, increasing its solar and wind capacities from 202 MW (1.1%) in 2012 to 6522 MW (21%) in 2021, and increasing further by 2022 to a total of 10476 MW (32%). According to the Chilean Energy Ministry, this trend will continue to increase to cover 70% of energy generation by 2030 with renewable energy sources and to meet the carbon neutrality scenario by 2050. However, since the electricity generation from renewable energy sources is affected by future extreme weather events caused by climate change, this possible uncertainty and variability should be considered when new energy projects are designed and developed. The present work aims to study the variability of renewable energy generation under future climate scenarios in Chile.

To capture the future variability of the weather conditions, we use the global climate models from Coupled Model Intercomparison Project Phase 6 (CMIP), which assess future climate change projections considering climate variability and uncertainties scenarios. We adapt these datasets for Chile, interpolate the wind speed based on model-level raw data proposed by Hahmann et al., and calculate capacity factors per renewable technology.

Through this study, we expect to explore the changes in renewable energy generation in Chile, estimating the impact of climate changes in this area. This work will help decision-makers decide on the future energy transition of Chile in the face of extreme changes in the climate condition of the country.

How to cite: Valenzuela-Venegas, G. and Zeyringer, M.: Studying renewable energy generation variability under future climate scenarios in Chile, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7130, https://doi.org/10.5194/egusphere-egu23-7130, 2023.

14:55–15:05
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EGU23-17356
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ECS
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On-site presentation
Petr Dolezal, Srinivasan Keshav, and Emily Shuckburgh

When modelling possible future renewable electricity systems, a strong focus needs to be directed to the input weather variables driving any such system. Since we cannot know the exact weather in any slightly distant future, a probabilistic approach is usually chosen, modelling the system over many possible scenarios, typically all of the past recorded weather data available. However, this narrows the range of situations considered to about 40 years, placing fundamental limits on the analysis, e.g. of rare, extreme scenarios.

In our work, we explore the possibility of using past expired ensemble forecasts from the ECMWF [1] to drastically increase the number of scenarios considered to up to 10 000 years of data. These ensemble forecasts are physical models that are regularly initialized from the same slightly perturbed snapshot, but due to the chaotic nature of weather, their predictions diverge from each other. The later stages of their predictions are thus entirely independent predictions of what the weather could have been, including the correct spatial correlations. We analyze the data from the operational archive of ECMWF to assess their suitability for modelling renewable systems of the future and demonstrate how this wealth of additional weather scenarios can enable the utilization of otherwise heavily data-dependent machine learning techniques in energy modelling. 



 [1] European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Model Ensemble extended forecast https://www.ecmwf.int/en/forecasts/datasets/set-vi

How to cite: Dolezal, P., Keshav, S., and Shuckburgh, E.: Using expired weather forecasts to supply up to 10 000 years of weather data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17356, https://doi.org/10.5194/egusphere-egu23-17356, 2023.

15:05–15:15
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EGU23-5419
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On-site presentation
Enrico Antonini, Edgar Virguez, Sara Ashfaq, Lei Duan, Tyler Ruggles, and Ken Caldeira

Wind droughts, or prolonged periods of low wind speeds, can be a severe issue for electricity systems that are largely reliant on wind generation. Therefore, it is important for energy system planning to understand the depth and distribution of wind droughts and their trends over time. In this study, we analyze the ERA5 weather reanalysis from 1979 through 2021, using an energy deficit metric that integrates the depth and duration of wind droughts over an annual temporal scale. Our analysis shows that the most severe wind droughts in many places occurred well before wind power generation started to penetrate power systems. This prevalence of wind droughts in the historical record, combined with little evidence for strong trends in their prevalence, suggests a statistical analysis of weather reanalysis products could provide valuable guidance in designing electricity systems reliant on wind power that are robust to wind droughts.

How to cite: Antonini, E., Virguez, E., Ashfaq, S., Duan, L., Ruggles, T., and Caldeira, K.: Historical analysis of global distribution of and trends in wind droughts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5419, https://doi.org/10.5194/egusphere-egu23-5419, 2023.

15:15–15:25
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EGU23-12295
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ECS
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On-site presentation
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Aleksander Grochowicz, Koen van Greevenbroek, and Hannah Bloomfield

The climate crisis and cost reductions in key technologies like solar, wind, and batteries are pushing an ambitious transition of power systems to renewables. This shift towards intermittent generation deepens the impact of weather and climate on the energy sector and can introduce new risks if not accounted for properly. Furthermore, as the ramifications of climate change are only to become even more noticeable, extreme events are expected to increase both in frequency and intensity. This in itself may lead to additional stress on renewable power systems, and recent research in energy meteorology relates these extreme weather events to so-called compound weather events, which are caused by more than one variable or component at the same time. However, compound events, their characteristics, and their risk for energy systems design are not yet well understood.

In this work, we use outputs of a power system model to identify what meteorological drivers lead to difficult periods and stress in the European electricity system. For this we couple energy modelling and meteorology in an iterative process that can connect weather insights from a synoptic scale to features of a highly resolved representation of the European electricity network. We use the open energy system model PyPSA-Eur with four decades of reanalysis weather data to find cost-minimal solutions for a fully decarbonised European power system. Dual variables of these optima are used to identify difficult weather periods, understood as periods that drive system design and total cost. This use of dual variables of the optima - as opposed to studying weather data in isolation - allows for a more accurate identification of difficult periods, tailored to the energy system at hand. We then characterise the underlying weather conditions during those periods and assess their effects on the power system and energy variables. Due to the level of integration, some of these spread across the entire continent, whereas other phenomena remain local; they can be of varied intensity and persist on different time scales.

Bringing an enhanced understanding of which weather events are difficult for energy systems, this approach can help to find obstacles for a transition to a fully renewable European power network, and inform how certain risks can be avoided or resilience strengthened.

How to cite: Grochowicz, A., van Greevenbroek, K., and Bloomfield, H.: Identifying weather stress events from power system optimisation outputs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12295, https://doi.org/10.5194/egusphere-egu23-12295, 2023.

15:25–15:35
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EGU23-10553
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ECS
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On-site presentation
Arya Samanta, Moritz Adam, Mathias M. May, and Kira Rehfeld

Solar panels of utility scale are a rapidly growing contribution to the renewable energy supply with increasing efficiency and steeply reducing costs of photovoltaics (PV). Although there is consensus on long term reduction of greenhouse gas emissions and advantages of avoided emissions by using PV systems, there is need to understand the climatic effects of land surface modifications of such systems.

We first review studies focusing on effects of utility-scale solar farms and compare their results in accordance to their characterization of a photovoltaic and the type of model used to evaluate effects. Then, we perform simulations of larger than current utility-scale solar farms but also comparatively small localized farms which are both characterized by modified land surface properties. These regions are either identified on the basis of solar insolation and desert-like criteria (low precipitation) or are proposed in existing studies for potential deployment of solar farms. The solar farm deployments are characterized by static or gradual changes in respective boundary conditions of albedo, soil roughness and outgoing longwave thermal properties. Separate experiments are conducted with non-dynamic and dynamic vegetation components to investigate potential feedbacks originating from the interplay of vegetation and precipitation. To this end, we use a comprehensive model (MPI-ESM-LR; Mauritsen et al., 2019), and the Earth System Model of Intermediate Complexity PlaSim (Fraedrich et al., 2005) to understand, and cross-validate, the effects in two models of different complexity model.

We examine the results considering changes in radiative forces and surface energy budget and, therefore, the surface temperatures which can likely lead to atmospheric circulation patterns, precipitation and vegetation feedbacks. If lower complexity models provide results in an acceptable ballpark of comprehensive ESMs, then they could be further used for future quick compute simulations with various deployment scenarios and experimentation with variable technical aspects. Spatially explicit deployment of PV with focus on parameterized thermal properties dependent on the simulated climate would also allows us to look at the complementary effect of climate on panels and could help constrain the effect of different pathways on PV technology in the future.

How to cite: Samanta, A., Adam, M., May, M. M., and Rehfeld, K.: Comparing the effects of large scale solar farms on climate and regional surface energy budget in different climate models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10553, https://doi.org/10.5194/egusphere-egu23-10553, 2023.

Externalities and potentials of renewables
15:35–15:45
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EGU23-13185
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Highlight
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On-site presentation
Andrea Hahmann, Aikaterini Mitsakou, Nicolás G. Alonso De Linaje, Oscar García-Santiago, Jake Badger, Jelle van Uden, Anders Rennuit-Mortensen, and Michiel den Haan

The European Union has set ambitious greenhouse gas reduction targets, stimulating renewable energy production and accelerating the deployment of offshore wind energy in northern European waters, mainly the North Sea. We investigate if the set targets are achievable given the wind climate of the North Sea and efficiency loss resulting from large-scale extraction of kinetic energy.

We utilise the wind climate of the North Sea estimated from ERA5 and the New European Wind Atlas (NEWA) to evaluate the offshore energy potential of this region. We consider three scenarios of wind turbine technologies: wind farms in operation today, existing plus wind farms in the construction and planning stage, and all wind farms, which include all possible areas where offshore wind farms could be built in the future, which are determined from current exclusions zones in the North Sea. We estimate the annual energy production and capacity factors per country for the various scenarios under free-stream conditions, considering wind farm wakes from engineering models and the loss of efficiency of huge wind farms. We study the sensitivity of the energy potential to the source of wind climate (ERA5 versus NEWA), whether the data is bias-corrected or not, and the method used to apply the wake losses to the wind farm considered. We also evaluate the possible year-to-year variability of these estimates.

How to cite: Hahmann, A., Mitsakou, A., Alonso De Linaje, N. G., García-Santiago, O., Badger, J., van Uden, J., Rennuit-Mortensen, A., and den Haan, M.: Estimating the Offshore Wind Energy potential of the North Sea considering exclusion zones and the efficiency of large wind farms clusters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13185, https://doi.org/10.5194/egusphere-egu23-13185, 2023.

Coffee break
16:15–16:25
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EGU23-4191
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ECS
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Highlight
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On-site presentation
Sebastian Wehrle and Johannes Schmidt

Deploying renewable electricity generators comes with significant benefits but can also bring about social costs, for example, through interference with landscapes or the biosphere. 
We develop a novel methodology for quantifying the local social costs of renewable energy technologies. Through zoning decisions, authorities implicitly value spatial characteristics by trading-off different traits, such as wind resource quality or distance to settlements. 
We develop a simple theoretical model of renewable zoning and implement a corresponding discrete choice model that allows us to estimate the implied valuation from observed data in high spatial resolution. The wind power zoning in the federal state of Lower Austria, home to Austria's most significant wind resources, serves as our case study. 
According to our preliminary estimates, local social costs are non-negligible and significantly affect wind turbines' socially optimal spatial distribution. These results can inform optimal capacity choice in power system models and support wind turbine siting. Moreover, spatially highly resolved assessments of social cost are a significant improvement over conventional potential assessments based on binary exclusion criteria.

How to cite: Wehrle, S. and Schmidt, J.: Inferring local social cost from renewable zoning decisions. Evidence from Lower Austria's wind power zoning., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4191, https://doi.org/10.5194/egusphere-egu23-4191, 2023.

16:25–16:35
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EGU23-1148
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ECS
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Virtual presentation
Oliver Ruhnau, Anselm Eicke, Raffaele Sgarlato, Tim Tröndle, and Lion Hirth

Numerical optimization models are used to develop scenarios of the future energy system. Usually, they optimize the energy mix subject to engineering costs such as equipment and fuel. For onshore wind energy, some of these models use cost-potential curves that indicate how much electricity can be generated at what cost. These curves are upward sloping mainly because windy sites are occupied first and further expanding wind energy means deploying less favorable resources. Meanwhile, real-world wind energy expansion is curbed by local resistance, regulatory constraints, and legal challenges. This presumably reflects the perceived adverse effect that onshore wind energy has on the local human population, as well as other negative external effects. These disamenity costs are at the core of this paper. We provide a comprehensive and consistent set of cost-potential curves of wind energy for all European countries that include disamenity costs, and which can be used in energy system modeling. We combine existing valuation of disamenity costs from the literature that describe the costs as a function of the distance between turbine and households with gridded population data, granular geospatial data of wind speeds, and additional land-use constraints to calculate such curves. We find that disamenity costs are not a game changer: for most countries and assumptions, the marginal levelized cost of onshore wind energy increase by 0.2–12.5 €/MWh.

How to cite: Ruhnau, O., Eicke, A., Sgarlato, R., Tröndle, T., and Hirth, L.: Cost-Potential Curves of Onshore Wind Energy: the Role of Disamenity Costs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1148, https://doi.org/10.5194/egusphere-egu23-1148, 2023.

16:35–16:45
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EGU23-2855
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Highlight
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On-site presentation
Philip Tafarte, Charlotte Geiger, and Paul Lehmann

Wind power onshore is one of the key technologies in the process of transitioning to a climate-neutral energy system. Yet, negative externalities of wind power for people and nature can occur. These externalities are usually regulated with spatial planning instruments that exclude certain areas from wind power development, like forest bans or increased setback distances to settlements, which were introduced across many regions in recent years. However, this regulatory practice can cause trade-offs between the regulated externalities. We use a multi-criteria GIS-based model of the potential areas for wind power onshore in Germany to identify and quantify these trade-offs for forest bans and setback distances to settlements.  Our results show that relevant trade-offs exist between a forest ban and the proximity of the remaining potential areas to settlements as well as between setback distances and the share of forest in the remaining potential area. Further, we find that individual and simultaneous implementations of the described regulations reduce the potential area of and production potential from wind power to an extent that future expansion targets for onshore wind power in Germany are no longer achievable.

How to cite: Tafarte, P., Geiger, C., and Lehmann, P.: The opportunity cost of land use restrictions and their impact on the energy transition - a case study for Germany´s onshore wind power, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2855, https://doi.org/10.5194/egusphere-egu23-2855, 2023.

16:45–16:55
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EGU23-13628
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On-site presentation
Wilfried van Sark, Gabriela Koster, and Britta Ricker

Bulgaria suffers significantly from energy poverty. With the EU goal to reduce 55% of its emissions by 2030, careful considerations are needed in the decarbonization policies within the energy system to avoid redistributive consequences that affect vulnerable groups.

 

Decarbonizing the building sector through photovoltaic (PV) solar technology is a viable option and supported by EU directives. PV technology offers financial benefits for the public and reduces energy dependency from the grid. Mapping the solar potential of a building is needed to determine whether an investment in PV is viable. Solar potential mapping that incorporates socio-economic factors can inform policymakers on alleviating energy poverty.

 

In this paper, a solar potential mapping approach using ArcGIS Pro is developed that allows physical, technical, as well as socio-economic aspects, including social considerations. As a case study for Bulgaria, the city of Plovdiv was chosen.  Open datasets have been used. Energy affordability is used which can be determined on the basis of energy consumption and energy prices.

 

The results show that there is a high solar energy potential in Plovdiv, while the actual potential depends on which irradiance dataset is used. The potential is estimated to supply the entire city's electricity needs by 20-58%, which translates to providing electricity needs of about 90,000 to 135,000 inhabitants. The solar potential exceeds the building energy consumption needs of 200-300 kWh/m² in all the buildings in Plovdiv. The estimated potential savings after PV installation from utility bills is between €21-32 million annually. The socio-economic factors help place the potential values in perspective, thus visualizing the benefits of distributed PV systems. It strengthens the argument of developing policies including energy poverty indicators.

How to cite: van Sark, W., Koster, G., and Ricker, B.: Solar potential mapping to address energy poverty in a data poor region: A case study in Plovdiv, Bulgaria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13628, https://doi.org/10.5194/egusphere-egu23-13628, 2023.

System analysis
16:55–17:15
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EGU23-11780
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ECS
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solicited
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On-site presentation
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Koen van Greevenbroek and Aleksander Grochowicz

To fulfil the Paris agreement, European countries have set out decarbonisation targets for 2050 and to reach them plan to massively expand the deployment of renewable energy technologies. Within the European Union, the member states are responsible for mapping out national strategies that meet the overarching EU objectives, including those of the recent REPowerEU plan. At the same time, the European electricity network is highly integrated with many interdependencies such that national policy decisions already have cross borders effects.


We study trade-offs between design flexibility on a regional level and in the entire network, and whether decisions by some actors (i.e. countries, regions or the EU) can enable or restrict the choices of others. This is done using the open sector-coupled energy system optimisation model PyPSA-Eur-Sec at a high spatial and temporal resolution, aiming at carbon-neutral scenarios for 2050. We define design flexibility in the context of near-optimal feasible spaces ---  using recent advances we are able to approximate the joint near-optimal feasible space for both a particular region and the rest of the system. By intersecting near-optimal spaces for different scenarios, we make this approach robust to uncertainties including weather variability and technology costs. For a number of selected regions in Europe, we thus look for both regional and European investment decisions which enable or restrict agency by enlarging or shrinking the space of solutions compatible with the decarbonisation targets for 2050.

How to cite: van Greevenbroek, K. and Grochowicz, A.: Enabling agency: trade-offs between regional and European design flexibility in renewable energy systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11780, https://doi.org/10.5194/egusphere-egu23-11780, 2023.

17:15–17:25
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EGU23-12347
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ECS
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On-site presentation
Oskar Vågerö, Marianne Zeyringer, and Tor Håkon Jackson Inderberg

What constitutes socially just or unjust energy systems or transitions can be derived from the philosophy and principles of justice. Assessments of justice and modelling outputs leads to great differences based on which justice principles are applied. From the little research so far published in the intersection between energy systems modelling and justice, we find that comparisons between the two principles of utilitarianism and egalitarianism dominate in assessments of distributive justice, with the latter most often considered representing a 'just energy system'. Not recognising alternative and equally valid principles of justice, resting on e.g. capabilities, responsibilities and/or opportunities, may contribute to a narrow understanding of justice that fail to align with the views of different individuals, stakeholders and societies. More importantly, it can lead to the unjust design of future energy systems and energy systems analysis. 

In this work, we contribute to the growing amount of research on justice in energy systems modelling by assessing the implications of different philosophical views on justice on modelling results. Through a modelling exercise with a power system model for Europe (highRES Europe), we explore different designs of a future net-zero European energy system, and its distributional implications based on different justice principles. In addition to the utilitarian and egalitarian approach, we include, among others, principles of 'polluters pay' and 'ability-to-pay', which take historical contributions of greenhouse gas emissions and the socio-economic conditions of a region into account. 

We find that socially just energy systems look significantly different depending on the justice principles applied. Key output metrics include costs, technology mixes and spatial deployment of electricity generation infrastructure. The results should contribute to a greater discussion among researchers on the implications of different constructions of justice in modelling, expansion of approaches, and demonstrate the importance of transparency and assumptions when communicating such results. 

How to cite: Vågerö, O., Zeyringer, M., and Inderberg, T. H. J.: Modelling the just allocation of energy infrastructure - Implications of assumptions and definitions of justice on model results, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12347, https://doi.org/10.5194/egusphere-egu23-12347, 2023.

17:25–17:35
|
EGU23-17364
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On-site presentation
Victhalia Zapata, Anteneh Dagnachew, Oreane Edelenbosch, and Detlef van Vuuren

There are 770 million people without access to electricity globally, and 77% live in Sub-Sahara Africa (SSA). If the current electrification trends continue, IEA projections indicate that still 670 million people will lack electricity access by 2030, meaning that the SDG7.1 goal of achieving universal electricity access will not be achieved with current policies. Most of the research on optimal solutions for achieving SDG7.1 is focused on SSA. However, a nonnegligible number of people still lack access in other regions; therefore, a global perspective is important. This work aims to spatially analyze the least-cost strategies for achieving universal electricity access globally, the investment needed, and the synergies with climate change mitigation. Optimal least-cost solutions vary depending on the local situation. For instance, the cost of in-situ systems depends on the spatial spread of households, local energy demand and resource availability. Therefore, high-resolution (HR) spatial assessment is needed, also for integrated global analysis.

For this research, we build upon the work of Dagnachew et al. for SSA and expand the scope to global. The model is updated and re-coded for open-source access, and the spatial resolution has been increased from 30’ x 30’ to 5’x 5’. The levelized cost (LCOE) for eleven plausible electrification solutions is assessed per grid cell worldwide to select the least-cost option. They can be summarized in three categories: central grid extension and two off-grid options, stand-alone and mini-grid systems. A central grid connection is the solution that usually offers the largest security of supply. However, for remote areas, the high cost of grid extension justifies prioritizing off-grid solutions. Mini-grids consist of small powerplant (s) that feed electricity into a distribution grid. It is the most reliable off-grid option and can be built ready for future grid connection.

The main factors influencing LCOE are socio-geographic conditions and potential local energy resources for wind and solar. The socio-geographic factors are annual electricity use per household, obtained from the integrated assessment model IMAGE, population density translated into the number of households per grid cell, population dispersion within the grid cells and urban/rural rates. Another important factor is the distance to the central grid, assessed per grid cell (5’x5’ resolution) and determines the cost of grid extension. Preliminary results indicate that after optimizing for the lowest cost, central grid densification is the most suitable option for most people currently lacking access. Photovoltaic systems are used the most for the off-grid options, combined with diesel for mini-grids and in solar home systems. Total investment for the SSA region for achieving SDG7.1 is estimated at around 600 billion.

How to cite: Zapata, V., Dagnachew, A., Edelenbosch, O., and van Vuuren, D.: Global pathways to achieve universal electricity access in 2030, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17364, https://doi.org/10.5194/egusphere-egu23-17364, 2023.

17:35–17:45
|
EGU23-500
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ECS
|
On-site presentation
Anasuya Gangopadhyay, Ashwin K. Seshadri, and Balachandra Patil

In a steadily decarbonizing electricity system, it becomes increasingly important to explore cost-effective wind-solar-storage combinations to replace conventional fossil-fuelled power generation without compromising grid reliability. For a renewable-rich state in Southern India (Karnataka), we systematically assess the economics of various wind-solar-battery energy mixes given decreasing fossil-fuelled base generation and hydropower availability using Pareto frontiers. Our approach considers hourly load data, simulates generation based on hourly weather reanalysis products, and models the effects of battery charging and discharging on battery lifetime. We find that the allowed curtailment level limits the achievable grid reliability. Given declining baseload generation and available hydropower in the state electricity grid, the wind-solar-battery combined system can provide limited reliability, which declines as the grid is progressively decarbonized. A fully decarbonized grid with 2 GW of hydropower and a stringent 10% curtailment threshold can achieve maximum reliability of 66%. These values are sensitive to available hydropower capacity, baseload generation from fossil fuel, and the curtailment threshold. For a fully decarbonized grid, increasing the allowed curtailment threshold of renewable generation (during times of excess) to 80% would ensure 99% grid reliability. However, such a solution would be costly, requiring large wind-solar installations that exceed officially assessed potential, constrained by land allocation. Furthermore, these calculations show that adding storage capacity without concomitant expansion of renewable generation capacity is inefficient. The findings highlight the importance of a fresh examination of curtailment thresholds, renewable potential, and possibilities of demand-side management to evaluate pathways to the decarbonization of the electricity grid while maintaining reliability.

How to cite: Gangopadhyay, A., K. Seshadri, A., and Patil, B.: Wind-solar-storage trade-offs in a decarbonising electricity system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-500, https://doi.org/10.5194/egusphere-egu23-500, 2023.

17:45–17:55
|
EGU23-3367
|
ECS
|
On-site presentation
Théo Chamarande, Benoit Hingray, and Sandrine Mathy

Ensuring a universal access to a reliable, affordable, and sustainable energy by 2030 would require electrifying around 600 million people in Sub-Saharan Africa. The International Energy Agency estimates that one third of the future electricity connections would be met by mini-grids (MG). This electrification must be compatible with the objective of the Paris agreement and global pathways expected to limit warming to 1.5°C have to reach net-zero CO2 emission as soon as 2050. Autonomous MGs based on solar PV are there a promising solution to electrify rural areas. They have a low cost and allow to significantly reduce greenhouse gases (GHG) emissions compared to diesel generators.

Many different MG configurations hybridizing solar PV, diesel genset and batteries can supply the production required for a given community, and the sizing of MG is usually done by minimizing criteria such as the levelized cost of electricity (LCOE) and/or the carbon footprint (CFP) of the system. The goal of this study is to quantify the distance between the CFP optimum and the LCOE optimum configurations, and the potential to find compromising configurations between.

To do so, we consider fictitious hybrid MG for a large range of configurations (PV and diesel share, storage capacities) to supply typical load profiles for 93 different locations over Africa. The solar PV production is simulated using meteorological data at a 15min resolution (ERA5, Heliosat SARAH2) and we ensure that the electrical consumption is fully supplied with simple dispatch rules for the batteries and the genset.

We show that the least LCOE (LCOE*) and the least CFP (CFP*) configurations and values are mainly driven by the mean capacity factor of the solar resource and by its co-variability with the electric load profile. The larger the capacity factor, the lower the LCOE and the CFP, and the nighttime energy consumption strongly influences the CFP values for both configurations.

We show that, even in a configuration where all the production is obtained from solar, the CFP of a MG is non-negligible. If the CFP of a MG is obviously determined by the direct greenhouse gases (GHG) emissions related to fuel combustion, it indeed also results from the indirect GHG emissions obtained for solar PV and batteries production. For the studied locations, the CFP* values cannot go below a minimum threshold between 180 𝑔𝐶𝑂2/𝑘𝑊ℎ and 250 𝑔𝐶𝑂2/𝑘𝑊ℎ depending on the climatic zone and the load profile considered.

For almost all locations, the LCOE* configuration is obtained with a hybrid MG. We also show that this configuration usually allows a CFP reduction by more than 50% compared to a genset only configuration, and that, relatively high increases (often >20%) of the LCOE are needed to reduce further MG emissions at the level of the CFP* configuration. We however also show that significant CFP reduction can be obtained at low cost by choosing a configuration between the CFP* and the LCOE* configurations.

How to cite: Chamarande, T., Hingray, B., and Mathy, S.: Reducing the carbon footprint of mini-grids in Africa: the value of solar PV, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3367, https://doi.org/10.5194/egusphere-egu23-3367, 2023.

Posters on site: Wed, 26 Apr, 08:30–10:15 | Hall X4

X4.137
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EGU23-17544
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ECS
|
Thomas Monahan, Tianning Tang, and Thomas. A. A. Adcock

A hybrid model is proposed for the short-term online prediction of tidal currents. The harmonic residual analysis (HRA) model is designed to augment the numerical schemes employed by tidal energy installations by forecasting the residual error of existing methods. Using a combination of techniques from Information and Fractal Theory, a novel component selection criterion for singular spectrum analysis (SSA) is used to remove true noise from the residual time series and to decompose the signal into components that are appropriate for linear-recurrent forecasting (LRF) and high order fuzzy time series (HOFTS) respectively. The performance of the HRA method is evaluated using a combination of simulated and real data from sites in the United Kingdom and the United States. Results demonstrate the model's viability for 6-minute and 1-hour forecast horizons across sites exhibiting variable degrees of non-linearity. Empirical analysis of the resultant tidal energy forecast verifies the superior accuracy and reliability of the HRA method when compared with existing numerical schemes. Simulated data from three sites at the Pentland Firth, UK is also provided to facilitate further study of the site's power generation characteristics and to allow for direct model performance comparisons.

How to cite: Monahan, T., Tang, T., and Adcock, T. A. A.: Enhancing Tidal Energy Forecasting Using Hybrid Online Machine Learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17544, https://doi.org/10.5194/egusphere-egu23-17544, 2023.

X4.138
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EGU23-9594
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ECS
Mahmoud Kenawi

Renewable energy sources are being increasingly utilized in order to mitigate climate change and phase out the use of fossil-based fuels. However, the impact of developing such energy sources on the land and ecosystem needs to be assessed and mitigated properly to avoid any source of problem shifting.

Hydropower is considered nationally and globally the dominant source of renewable energy that can effectively contribute to reducing the usage of fossil fuels as well as being a backbone to help other renewable energy sources with their problem of variability due to its flexibility of production. However, the alteration of the land dynamics due to its deployment varies significantly depending on various spatial and technological factors.

In Norway, more than 70% of hydropower production was developed in the period between 1950 and 1980.  yet, the identification of the land system used for this development and the alteration of the landscape remains unknown.

This work contributes to the limited insights of quantifying the land used for hydropower development in Norway and how the land has transformed due to this development over time. We classified historical aerial images representing the areas for 40 hydropower systems in Norway counting for 8.1 GWh installed capacity which is 24% of Norway’s total hydropower installed capacity and 12% of the total reservoir area. We analyzed what kind of land was used for this development and compared these historical images with recent images to assess the land use change surrounding these hydropower systems with a 1 km buffer zone. 

We found that 63% of the total reservoir areas were already existing water bodies while 9% of the vegetation land was used for this development. We also found that 84% of the reservoirs were built on existing lakes or lakes that were expanded due to hydropower developments.

Additionally, we found that vegetation percentage either remained still or continued growth in most of the analyzed schemes while urban development was slightly small counting only for scattered cabins deployment and construction of roads.  The results of this work help unveil the uncertainties between land dynamics and hydropower development in Norway.

 

 

How to cite: Kenawi, M.: Quantification of the land-use pattern and areal effects of the hydropower development in Norway, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9594, https://doi.org/10.5194/egusphere-egu23-9594, 2023.

X4.139
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EGU23-11226
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ECS
Yinglu Liu

Building a new power system with new energy as the main body is a fundamental measure for energy and power sector to achieve carbon peak and carbon neutrality, and also a prerequisite for the whole economy and society to achieve the goal of "double carbon". However, how to construct a new type of power system is still a global problem, and its solution needs to rely on multidisciplinary knowledge. In this paper, a new power system analysis framework is constructed, and the structural characteristics and operation mechanism of the new power system are analyzed from the perspective of multidisciplinary comprehensive analysis. Based on this framework, we can initially diagnose various problems encountered in the construction of new power system and find possible solutions. Different actors participating in the construction of new power system can also find their own strength points in it and contribute to the security, stability and economic operation of the system.

How to cite: Liu, Y.: Climate effects of wind farm in China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11226, https://doi.org/10.5194/egusphere-egu23-11226, 2023.

X4.140
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EGU23-664
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ECS
|
Tahsin Görmüş, Burak Aydoğan, and Berna Ayat

The investigation of extreme sea conditions is of great importance regarding to the design and survivability of marine and offshore structures. Accurate quantification of the storm events in terms of the n-year return levels is needed. Extreme value distributions are used to analyze the extreme waves in the interested location, but the comparison of the distributions is usually ignored. This comparison is important, since a small deviation could mean much higher differences in the design parameters of the structures. This study evaluates the extreme wave conditions in the prescribed locations located in the Mediterranean Sea by quantitatively comparing different statistical distributions. The recent ERA5 dataset is used for the analysis. Statistical distributions of Generalized Extreme Value (GEV), Gumbel, Weibull and Lognormal are used based on the Annual Maximum Series (AMS); Weibull and Generalized Pareto Distribution (GPD) are used based on the Partial Duration Series (PDS). Peak-over-threshold method is used with 99.5th percentile threshold of the hourly 42-year long time-series after careful considerations of the alternatives found in the literature regarding to the threshold selection. The return levels of the significant wave height (Hm0,N) for each of the selected location is computed using the relation Hm0,N=F-1(1-1/λN) in where F denotes the cumulative distribution function of the used statistical distribution, N is the return period in years, and λ is the yearly frequency of the extreme events in the extracted time-series. The distribution parameters are acquired using the maximum likelihood approximation. The comparison of the distributions is made using the Anderson-Darling (AD) test. Mediterranean Sea exhibits diverse sea conditions. 12 spatially distributed locations are selected to represent the wave climate in the basin. The analysis clearly depicts the importance of the statistical distribution model selection. In the Gulf of Lion, 100-year return level Hm0,100 ranges between 9.5 m (Weibull/AMS) and 11.3 m (Gumbel/AMS). Inter-model uncertainty increases with the increasing return period. It is evaluated that the characteristics of the extreme wave series are determinative over the fitting accuracy of the distributions. Considering the best-fitting distributions among the 12 selected locations throughout the basin, the Hm0,100 values range between 4.9 m and 9.8 m. GEV distribution is selected as the best-fitting AMS distribution in five of those locations by the AD test, where for PDS models, Weibull distribution is outperformed the GPD in 11 points. This research is a part of a project supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant number 122M279, and the first author is also supported by TÜBİTAK 2211 PhD scholarship programme.

How to cite: Görmüş, T., Aydoğan, B., and Ayat, B.: Comparison of extreme value distributions for significant wave heights in the Mediterranean Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-664, https://doi.org/10.5194/egusphere-egu23-664, 2023.

X4.141
|
EGU23-790
Burak Aydoğan, Tahsin Görmüş, and Berna Ayat

In this study, we investigated the spatiotemporal characteristics and variability of Mediterranean and Black Sea wind power. As the data source, ERA5 1-hourly dataset from the European Centre for Medium-Range Weather Forecasts is used in between the years of 1959 and 2020 and for 100-m altitude. The statistical analysis of the 62-year long time-series covered the investigation of several timescales of hourly, sub-daily, daily, monthly, seasonal, and yearly averaged values. The average values are spatially mapped for yearly and seasonal timescales. The study area has been divided into thirteen subsections to uncover the differences between the statistical parameters of the sub-basins. It is shown that in terms of wind power potential, two of the most energetic locations in the study area is Gulf of Lion and the Aegean Sea. The temporal average wind power density (WPD) map showed that the spatial maximum of the WPD reaches over 1100 W/m2 in the Gulf of Lion where the spatial average of the temporal average is over 370 W/m2. Several well-known indicators of variability have been used, such as yearly variability index, intra-annual variability index, and coefficient of variation to quantify the fluctuations. It is shown that in general, higher temporal variability has been obtained in the Eastern Black Sea, Eastern Tyrrhenian Sea, and the Sea of Azov for yearly and monthly timescales. A trend analysis based on over six-decade time-series showed that statistically significant downward trends are found in the Levantine Basin, Tunisian Plateau, and the Ionian Basin. Another important feature of the study is that WPD in the study area is also classified according the two spatial properties: water depth and the distance to the shoreline. A general conclusion of this investigation is that WPD increases with the distance to the shoreline where the most promising sub-sections with the highest potential within the first 25 km distance and up to 60 m water depth are the Aegean Sea and the Sea of Azov.

Acknowledgement: This research is supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant number 122M279, and Tahsin Görmüş is also supported by TÜBİTAK 2211 PhD scholarship programme.

Keywords: wind power, temporal variability, Mediterranean, Black Sea

How to cite: Aydoğan, B., Görmüş, T., and Ayat, B.: Temporal variability of wind power in the Mediterranean and the Black Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-790, https://doi.org/10.5194/egusphere-egu23-790, 2023.

X4.142
|
EGU23-7394
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ECS
Robin Tutunaru, Stephan Bosch, Lukas Greßhake, and Uwe Holzhammer

For a sustainable energy transition, concepts are needed that can map the techno-economic, socio-ecological, spatial and temporal complexity of regional site decisions for renewable energies (RE). Remarkable in this respect is that so far hardly any knowledge is available on how to design a computer-based methodological approach that precisely analyses and reflects the individual positions of the regional actors of the energy transition and visualises them with respect to the specificity of the actor-related land use interests. Our study therefore aims to analyse the complex interactions between the diverse competing land use claims. The central thesis is that a sustainable deployment of RE has to address in particular the communication processes between actors of the energy transition. Hence, we aim to capture the specific perspectives of certain stakeholders on the expansion of renewable energies. In doing so, we want to visualise the results by means of Geographic Information Systems (GIS) in such a way that they can be understood by each stakeholder or citizen and subsequently allow a constructive debate on the suitability of certain areas for the RE expansion. Favourable and unfavourable renewable energy sites cannot be generalised from the outset, rather they are linked to the interests, values and norms of the actors (e.g. cost minimisation, sustainability, land use efficiency, landscape aesthetics).

In order to analyse this complex interplay of technological, economic, ecological and social parameters and to be able to carry out a standardised evaluation of a socially balanced regional renewable energy deployment, this study will introduce an innovative GIS-based methodology. Our approach helps to deal with the competing social interpretations and constructs of all regional stakeholders that strive for a sustainable energy future.

How to cite: Tutunaru, R., Bosch, S., Greßhake, L., and Holzhammer, U.: A stakeholder-based approach for the sustainable deployment of renewable energies in conflictual social contexts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7394, https://doi.org/10.5194/egusphere-egu23-7394, 2023.

X4.143
|
EGU23-15736
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ECS
|
|
Maximilian Roithner, James Price, Johannes Schmidt, and Marianne Zeyringer

The Norwegian electricity demand has been almost entirely (~95 %) met by hydropower (~140 TWh of annual production, ~30GW of installed generation capacity), and low power prices were predominant for years. This has led to the development of industry and consumer dependence on ubiquitous cheap energy. The energy price shock in 2022 elevated price levels and opens multiple possible futures. With rising demand to be expected through electrification, increases in wind power generation capacity have been discussed and at least onshore been met with scepticism, and acceptance issues. As the export of energy in the form of oil and gas has been a major source of income for Norway that is now sought to be replaced, additional stakes join the discussion. Ideas of energy intensive industry such as battery production or data centres which would rely on low electricity prices, while also bringing demand increases, have been expressed. 

The future path splits between (further) integration into the European power system and (more) isolation of the Norwegian system. This would be expressed through electricity transmission and generation equipment expansion, which are important measures to ensure the adequacy and low carbon intensity of future nation- or continent-wide power systems. Policies may be measured by different competing targets, such as national price levels (which if low are favourable for industry), transnational carbon intensity (which if low helps to reach climate targets) or cross-border electricity trade (which if high helps to balance the system and generates income for the exporter). 

 We explore those trade-offs with Norway as a case study. The technical potential for North Sea offshore wind generation expansion is evident, and policy targets to expand offshore wind generation to the level of current hydropower generation (the highest in Europe) exist. Yet, the expansion of subsea transmission capacities (which would allow for more balancing through the Norwegian hydro reservoirs) seems to be on hold. Using the expansion and dispatch optimizing power system model highRES, we present scenarios for different degrees of expansion of offshore wind generation and (mostly subsea) transmission, to illustrate the crossroads in Norwegian energy policy, whose outcome could impact the European system.

How to cite: Roithner, M., Price, J., Schmidt, J., and Zeyringer, M.: Where will the Norwegian wind power go? Comparison of generation and transmission expansion scenarios., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15736, https://doi.org/10.5194/egusphere-egu23-15736, 2023.

Posters virtual: Wed, 26 Apr, 08:30–10:15 | vHall ERE

vERE.6
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EGU23-14160
|
Arianna Leoni, Angelo Carlino, Wyatt Arnold, and Andrea Castelletti

Development pathways for Sub-Saharan Africa project a substantial increase in population and living standards. To accommodate the future energy demand, the power and the energy system community have been developing least-cost optimization models to support long-term planning. Given the rise of climate change impacts and the necessity to mitigate them in the future, investments in new energy infrastructure should contemplate carbon neutral alternatives wherever economically viable.

However, integrated assessment and long-term energy planning models usually focus on annual or seasonal energy balances neglecting higher time resolution dynamics that can actually lead to short but high impact events. Indeed, the variability of renewable generation and power demand can lead to significant risks of high electricity prices, transmission lines overload, and power generation deficits.

To quantify these impacts, we inform a power system simulation model, PowNet, with energy development pathways from the long-term energy system planning model, OSeMOSYS-TEMBA. While the latter models the development of all the countries in continental Africa with a seasonal resolution from 2015 to 2070, the first has an annual horizon with hourly resolution and focuses on countries included in the Southern African Power Pool. In particular, PowNet is used to optimize the dispatch of power from each source as well as the usage of transmission lines, and it is constrained to the power capacity available according to the long-term energy planning provided by the OSeMOSYS-TEMBA model. We assess these impacts in 2025 and 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. We study the difference in generation mix, the impact on transmission lines overloading, power generation deficits, and electricity prices.

Preliminary results show an increase of the generation during the years, in particular of the renewable resources, that varies depending on the selected scenario. Moreover, 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 prove 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 lack ofpower storage technologies in the energy system model might also significantly affect capacity expansion plans and consequent impacts. These results show the importance of the assumptions embedded in 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., Carlino, A., Arnold, W., and Castelletti, A.: Downscaling Sub-Saharan Africa energy projections for power system planning: impacts, inconsistencies, and potential improvements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14160, https://doi.org/10.5194/egusphere-egu23-14160, 2023.

vERE.7
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EGU23-598
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ECS
|
Anderson Soares, Djalma Falcão, Raquel Toste, Luiz Landau, and Luiz Assad

The increasing electricity demand, coupled with the global need to reduce greenhouse gases, has made renewable energies an attractive solution to the problem. The oceans offer good alternatives for diversification and expansion of the energy matrix, among the possibilities for energy production is that one comes from ocean currents. Therefore, this work aims to evaluate the harnessing energy from ocean currents on the Brazilian coast based on the results of the global circulation model used in CMIP5, the Brazilian Earth System Model (BESM). Due to low temporal and spatial resolution, BESM results were downscaled using ROMS. In order to evaluate the effects of climate change on hydrokinetic production in the ocean, the simulation must represent the current climate conditions and the future condition,  based on the historical scenario and RCP4.5 respectively. For this purpose, these results were used as lateral boundary conditions and surface forcing into a two-way nested model composed of a donor and two receiver grids, with 1/5° and 1/15° of horizontal resolution, respectively. The highest resolution grids embrace the regions with the highest hydrokinetic potential on the southeastern and northern coasts, where the Brazilian current or North Brazilian current predominates. In addition to spatial and temporal variability, the synergy between ocean current as a source of electric power supply and others sources from the Brazilian electrical matrix will be discussed.

How to cite: Soares, A., Falcão, D., Toste, R., Landau, L., and Assad, L.: Assessment of energy production potential from ocean currents along the Brazil coastline taking into account climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-598, https://doi.org/10.5194/egusphere-egu23-598, 2023.

vERE.8
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EGU23-16237
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ECS
Paola Velasco Herrejón, Marianne Zeyringer, Tanja Winther, and Johannes Schmidt

Decarbonisation of the energy system is key to achieving the Paris Agreement goal of limiting global temperature rise to below 2°C which can be achieved by electrified and interconnected systems with a high share of variable renewables. This transition is shaped by uncertain factors, which include technology innovation, resource availability, and socio-economic variables. Energy system modelling (ESM) has been a key policy tool to study decarbonisation pathways. ESM provides stakeholders in the energy sector with knowledge-based and systematic methods to reach decisions about which technologies to support. However, present-day ESM mainly integrates techno-economical input parameters, whereas social factors, such as local responses to new installations, are largely understudied. ESM might therefore produce solutions that are not accepted by communities and as a result, could jeopardize energy transition goals. The main goal of this presentation is to present the framework for WINDACCEPT, a Horizon Europe project that aims to develop an innovative and interdisciplinary mixed-methods approach integrating concepts of sociology (stakeholder analysis), economic philosophy (capability approach), and technology systems (energy systems modelling) to better define the ‘real world’ feasibility of large-scale wind farms from a range of economic, political, regulatory, and societal perspectives. This new methodology will be developed and applied to the case of Norway, a country with excellent wind resources but high local opposition towards their development. The selected case study is NVE area No. 40 which includes the municipalities of Hasvik, Hammerfest, Måsøy, Kvalsund, Alta, Porsanger, and Nordkapp. This case study was selected to provide deep knowledge of the context of wind energy social barriers in Norway based on the following factors: 1) excellent wind power conditions, 2) (partly) considered by the NVE as a suitable area for wind power development based on social and environmental factors, 3) a zone where three major RE have been cancelled, and 4) a Sámi area. The methodology aims to contribute to elucidating the impacts of community barriers and value the costs and benefits of alternative options on the net zero energy system design in Norway and the effects on long-term, whole system decarbonisation in an interconnected Europe. The proposed framework will also aim to maximise techno-social synergies that provide beneficial relationships between technological and social systems to increase the social sustainability of RES.

How to cite: Velasco Herrejón, P., Zeyringer, M., Winther, T., and Schmidt, J.: A methodology for integrating community acceptance of wind energy into energy system modelling (ESM), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16237, https://doi.org/10.5194/egusphere-egu23-16237, 2023.