ERE2.2

Increasing the generation of variable renewable energy sources (VRE), such as wind or solar photovoltaics, is one pivotal element in the decarbonization of our energy systems. VRE availability depends on prevailing weather conditions. During a period with high VRE availability, surplus energy needs to be integrated into the system. Times of VRE shortage require flexibility options that can serve demand. These options need to cover VRE droughts, i.e., long-lasting periods of low VRE availability. They may challenge the security of supply, notably in the case of simultaneity with high demand phases, and vary largely across time and space. This paper evaluates VRE droughts in terms of severity, duration, timing, and simultaneity in Germany and Europe using the Pan-European Climate Data Base by ENTSO-e, which provides VRE availability factors for 35 years.

Two definitions apply to VRE droughts (Ohlendorf & Schill, 2020). First, droughts as periods of consecutive hours with availability factors constantly below a certain threshold (CBT). Second, droughts as periods of consecutive hours with a moving average of VRE availability factors below a certain threshold (mean below threshold – MBT). While the CBT notion identifies drought periods in the narrow sense, the MBT definition also accounts for longer stretches of low VRE availability on average, with short instances of VRE availability above a threshold possible. Contrasting results from these two approaches reveals insights on the short- and long-term need for flexibility, for instance, by different types of storage.

Additionally, there are two options to count VRE droughts: First, a drought window denotes a period of consecutive availability factors with a fixed duration, qualified either according to the CBT or MBT notion. Windows are counted for increasing window size, starting with a few hours up to multiple months. This method identifies flexibility slices that the system needs to provide for all relevant time scales. Second, a drought event is a period of consecutive availability factors with variable duration. The algorithm counts in descending order from the longest event lasting multiple months to events lasting only a few hours. Consequently, each qualified CBT or MBT period is counted only once. Results reveal the number of drought events with a minimum duration that the system needs to balance.

This paper analyzes VRE droughts of individual VRE generation technologies, all VRE generation technologies combined, and, to account for simultaneity with demand peaks, residual load time series to identify periods with an energy deficit in the system (Ruhnau & Qvist, 2022). Insights allow for a distinct assessment of the relevance of energy droughts concerning VRE technologies individually and in terms of simultaneity for the transition of our energy systems, both in the German and European context (Raynaud et al., 2018; Kaspar et al., 2019).

References

Ohlendorf, N., Schill, W.-P., 2020. DOI: 10.1088/1748-9326/ab91e9

Kaspar, F., Borsche, M., Pfeifroth, U., Trentmann, J., Drücke, J., Becker, P., 2019. DOI 10.5194/asr-16-119-2019.

Raynaud, D., Hingray, B., François, B., Creutin, 2018. DOI: 10.1016/j.renene.2018.02.130.

Ruhnau, O., Qvist, S., 2022. (in press).

How to cite: Kittel, M.: Severity of variable renewably energy droughts in Germany and Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9909, https://doi.org/10.5194/egusphere-egu22-9909, 2022.

Policy and economic analyses use simple estimates of regional and global wind energy potential, or technical wind energy potential, to evaluate low carbon energy transition pathways. They  neglect the reduction in mean wind speeds due to the extraction of kinetic energy (KE) from the lower atmosphere as a means to reduce the computational complexity. However, climatological analyses of proposed regional wind turbine deployments with capacity densities ranging from 2-10 MW km^-2 show that this assumption leads to significant overestimation of wind energy potentials because the removal of KE does reduce wind speeds and turbine yields. This gap between policy focussed and climatology based estimates implies the need for the former to use a more climatologically descriptive, yet simple, approach to estimating technical potential. Framing regional wind energy potential within the context of a fixed lower atmosphere KE budget which uses variation in mean boundary layer height to define the KE budgets can improve estimates without increasing computational complexity. We evaluate this hypothesis by analysing a set of previously published Weather Research and Forecasting simulations of a hypothetical large scale wind turbine deployment in Kansas, US, which showed that nighttime yields were lower than daytime, despite wind speeds being 40% higher at night. We assess this seemingly counter-intuitive result by estimating day and nighttime yields while constraining them with separate day and night KE budgets. Daytime budgets are defined by higher mean boundary layer heights (2000m) while nighttime budgets by lower heights (900m). The combination of wind speeds boundary layer variations during day and night result in similar budgets. This means that turbines extract more KE from the atmosphere at night than daytime, leading to the nighttime budgets being depleted faster and thus lower deployment yields. Using the standard approach, which discounts the effect of KE removal by wind turbines, leads to a 180% and 600% overestimation in day and nighttime yields, respectively, relative to the weather model simulations. The KE budget approach , in contrast, leads to a significant improvement with day and nighttime bias being reduced to 20% and 60%, respectively. Using this approach, we revaluate existing technical wind energy potentials using the net area available for wind energy deployment in Kansas to show that yield expectations of 2000-3000 TWh yr^-1 could be reduced by almost 50%. Despite this reduction, the technical potential remains almost 3-5 times higher than the state’s 2018 primary energy consumption. We show that framing the yield from regional wind turbine deployments within a fixed lower atmosphere KE budget framework that uses mean boundary layer variations to define the KE budget leads to more climatologically representative estimates of technical potential without increasing computational complexity. These estimates are likely to improve further with the inclusion of nighttime stability effects. Climatologically representative estimates of technical wind energy potential will enable the development of more robust renewable energy transition policy. 

How to cite: Minz, J., Mbungu, N., Kleidon, A., and Miller, L.: Estimates of technical wind energy potentials can be improved by incorporating information about the variation in mean boundary layer heights, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5764, https://doi.org/10.5194/egusphere-egu22-5764, 2022.

The expansion of marine renewable power is a major alternative for the reduction of greenhouse gases emissions. In Europe, however, the high penetration of offshore wind brings intermittency and power variability into the existing power grid. Offshore solar photovoltaic power is another technological alternative under consideration in the plans for decarbonization. However, future variations in wind, air temperature or solar radiation due to climate change will have a great impact on both renewable energy resources. In this context, this study focusses on the offshore energy assessment off the coast of Western Iberia, a European region encompassing Portugal and the Northwestern part of Spain. Making use of a vast source of data from 35 simulations of a research project called CORDEX, this study investigates the complementarity of offshore wind and solar energy sources with the aim of improving the energy supply stability of this region up to 2040. The most pessimistic greenhouse gases emission scenario (RCP8.5) is considered. The 35 simulations are validated by comparing wind speed at 10m, air temperature at 2m and solar radiation values with data from the ERA5 reanalysis database. Although the offshore wind energy resource has proven to be higher than solar photovoltaic resource at annual scale, both renewable resources showed significant spatiotemporal energy variability throughout the western Iberian Peninsula. When both renewable resources are combined, the stability of the energy resource increased considerably throughout the year. The proposed wind and solar combination scheme is assessed by a performance classification method called Delphi, considering stability, resource, risk, and economic factors. The total index classification increases when resource stability is improved by considering hybrid offshore wind-photovoltaic solar energy production, especially along the nearshore waters.

How to cite: Costoya, X., deCastro, M., Carvalho, D., Arguilé-Pérez, B., and Gómez-Gesteira, M.: Offshore wind and solar photovoltaic energy combination to stabilize energy supply in the western Iberian Peninsula in the near future., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10283, https://doi.org/10.5194/egusphere-egu22-10283, 2022.

Hydrogen is a versatile energy carrier. When produced with renewable energy by water splitting, it is a carbon neutral alternative to fossil fuels. The industrialization process of this technology is currently dominated by electrolyzers powered by solar or wind energy. For small scale applications, however, more integrated device designs for water splitting using solar energy might optimize hydrogen production due to lower balance of system costs and a smarter thermal management. Such devices offer the opportunity to thermally couple the solar cell and the electrochemical compartment. In this way, heat losses in the absorber can be turned into an efficiency boost for the device via simultaneously enhancing the catalytic performance of the water splitting reactions, cooling the absorber, and decreasing the ohmic losses.^[1,2] However,integrated devices (sometimes also referred to as “artificial leaves”), currently suffer from a lower technology readiness level (TRL) than the completely decoupled approach.

Here, we describe our progress in designing integrated solar water splitting devices to power research stations in Antarctica as a first potentially economic competitive implementation of this technology.^[3] In such remote world regions, local and small-scale hydrogen production can become both economically and environmentally favorable, since the logistics for fossil fuels are expensive and environmentally hazardous. One reason for the low TRL of integrated devices is the complex and poorly understood influence of different weather/climate conditions and changes in the solar spectra on their efficiency.^[4] Therefore, we introduce an open-source Python-based model that combines solar cell physics, optical simulations, electrochemistry, as well as atmospheric and climate data as part of the “YaSoFo” environment.^[5] We model and analyze the climatic response of a device based on state-of-the-art AlGaAs/Si dual-junction photoabsorbers in Antarctica. Furthermore, we present a first prototype demonstrating solar water splitting at temperatures as low as -20°C. ^[3]  

Our work gives important insights into the chances and challenges for thermally coupled solar water splitting and lays the foundation for our goal of using these devices in remote world regions with cold climates.

[1] R. van de Krol, B. Parkinson, MRS Energy Sustain., 2017, 4(e13), 1-11

[2] S. Tembhurne, F. Nandjou, S. Haussener, Nat. Energy, 2019, 4, 399–407

[3] M. Kölbach, K. Rehfeld, M.M. May, Energy Environ. Sci., 2021,14, 4410-4417

[4] M. Reuß, J. Reul, T. Grube, M. Langemann, S. Calnan, M. Robinius, R. Schlatmann, U. Rau,  D. Stolten, Sustain. Energy Fuels, 2019, 3, 801-813

[5] M. M. May, D. Lackner, J. Ohlmann, F. Dimroth, R. van de Krol, T. Hannappel, K. Schwarzburg, Sustain. Energy Fuels, 2017, 1, 492-503

How to cite: Kölbach, M., Höhn, O., Barry, J., Finkbeiner, M., Rehfeld, K., and May, M. M.: Climatic response of thermally coupled solar water splitting in Antarctica, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11608, https://doi.org/10.5194/egusphere-egu22-11608, 2022.

Solar and wind power curves typically exhibit inverted daily and annual cycles. However, their monthly anomalies show both positive and negative low correlation values across Europe, which compromises the effectiveness of their integration in the energy grid. This is because the well-known asymmetric response of the resources to the main large-scale teleconnection patterns vanishes and/or shows low synchronicity when the compound effect of these patterns is considered, as we show here. So we propose a step-wise method to help narrowing the monthly deviations of the total wind-plus-solar electricity production at the regional level from a given curve (here, the mean annual cycle of the total production), applied here across five continuous European regions but with straight application elsewhere and at other temporal scales. It detects the optimal shares of each power over previously identified sub-regions with homogeneous temporal variability of the monthly anomalies of the wind and solar capacity factors. Results show that, keeping the current total regional shares, just through a smart distribution of the power units, the standard deviation of the monthly anomalies of the total wind-plus-solar production is reduced up to 20% without loss in the mean capacity factor as compared to a base scenario with uniform distribution of the installations. This reduction grows above 50% if the total regional shares also came into the optimization game.

Acknowledgments:

This study was supported by the Spanish Ministry of Science, Innovation and Universities – Agencia Estatal de Investigación and the European Regional Development Fund through the project EASE (RTI2018-100870-A-I00), and by the Fundación Séneca – Agencia de Ciencia y Tecnología de la Región de Murcia through the project CLIMAX (20642/JLI/18).

How to cite: Jerez, S., Barriopedro, D., García-López, A., Lorente-Plazas, R., Somoza, A., Turco, M., and Trigo, R. M.: An action-oriented approach to make the most of the wind and solar power complementarity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12420, https://doi.org/10.5194/egusphere-egu22-12420, 2022.

For the analysis of the expected performance of renewable energy systems of all sizes, nowadays various data bases offer the required time series of irradiances and wind speed. The validation of these sets is mainly based on various comparison schemes of averages or distribution functions on a yearly or monthly scale, forming a comprehensive toolbox for the respective quality assessment.  This allows for a high confidence in predictions of system performance data, as-long-as system operation can be considered as “memory-less”.  This is most prominently not the case for systems containing storage devices whose performance depend on the temporal characteristics of the time series - which had been less in focus for the validation of irradiance sets. 

This contribution aims to discuss which sequential characteristics of the data series govern the storage sizing. This should result in the identification of parameters that are applicable for the validation of irradiance series for this task. As example, photovoltaic + battery systems are analyzed, that are driven by data extracted from different sources made available by the PVGIS (https://ec.europa.eu/jrc/en/pvgis ) service.

How to cite: Beyer, H. G.: Identifying sequential characteristics of irradiance data sets applicable for the validation of sets for the assessment of the performance of renewable energy systems containing storage, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9615, https://doi.org/10.5194/egusphere-egu22-9615, 2022.

From a superficial reading of the literature on land-use requirements for renewable energy systems, one may conclude that the community has a very clear understanding of how much land is necessary to deploy renewable energy generation technologies. In particular for solar PV and wind power (VRES), the technologies with the highest growth potentials in the coming decades, abundant literature is available. However, a systematic overview is lacking, in particular, concerning approaches used for estimating the requirements, underlying factors that affect the results, and the regional differences.

There is no standard metric that is applied for estimating the land area necessary to accommodate a certain amount of renewable energy capacity. Several different metrics are used for this purpose, including land-use efficiency, land-use intensity, power density, and land occupation, to name a few. E.g., land-use efficiency in one paper can refer to the land area needed to install a certain capacity for energy generation, whereas another paper considers land-use efficiency as the area needed to generate a certain amount of electricity. Therefore, estimates of land-use requirements quantified with the same metrics vary greatly.  

The variability of the land-use requirements is also rooted in the underlying assumptions regarding the area, power-related component, and time of the chosen metrics. However, a systematized review of all aforementioned assumptions on land-use by renewable energies is absent.

Land-use requirements are often derived from the existing VRES facilities. Hence, their values are influenced by such location-specific factors as climatic conditions, orography, land ownership, among others. As land-use requirements are often integrated into the research that estimates potentials for the future deployment of renewable energy, the influence of those factors is implicitly integrated as well. Hence, the potentials for one region may be estimated by applying the data from another region. Although the application of region-specific land-use requirements could reduce the introduced inconsistencies, known land-use requirements are in its vast majority estimated for the US. Therefore, a compilation that in particular gathers literature on land-use of renewable energies in underrepresented world regions is of high importance.

How to cite: Turkovska, O., Gruber, K., Klingler, M., Klöckl, C., Ramirez Camargo, L., Regner, P., Wehrle, S., and Schmidt, J.: An overview of land-use requirements for solar PV and wind power, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11962, https://doi.org/10.5194/egusphere-egu22-11962, 2022.

We construct a geodatabase of spatially resolved PV supply profiles for building, land and water-bound installations under typical meteorological circumstances. This is done for three 2050 energy transition scenarios, which are all in line with the Dutch Climate Agreement, but differ from each other regarding the degree of decentralization of electricity demand and supply.

Hourly global horizontal irradiation (GHI) measurements by 33 Dutch ground observation stations are gathered and linearly interpolated to obtain a raster dataset with a resolution of 25 km. GHI is converted to global tilted irradiation (GTI) for a multitude of slope and azimuth combinations by subsequently applying the Erbs diffuse fraction and Perez transposition models, thus generating a GTI lookup table.

By combining building polygons and a high-density LiDAR height point cloud, roof surface polygons characterized by a slope and azimuth are identified for all buildings in the Netherlands. Using the GTI lookup table, the solar resource on each of the roof surfaces is determined. Scenario-specific national PV capacities for residential and utility buildings are then distributed over neighborhoods proportional to the total yearly solar resource on their corresponding roof surfaces. The resulting neighborhood capacities are sub-distributed over slope-azimuth-positions by applying distribution ratios found in a large dataset on registered Dutch PV systems.

Scenario-dependent national capacities for field-bound PV (agriculture, roadside and dike) and inland water-bound PV are distributed over municipalities proportional to their corresponding suitable land use areas. Offshore PV capacity is kept on national level. All neighborhood and municipality capacities are converted to GTI. The building-bound profiles are then translated to PV supply by applying solar elevation angle dependent performance ratios and an assumed panel efficiency of 20%. The same is done for the land and water-bound profiles, only now assuming a constant performance ratio of 90%. Residential building-bound PV is fully allocated to the low voltage distribution grid. For the utility variant, the portion allocated to low voltage level is equal to the neighborhood floorspace share of utility buildings estimated to have a grid connection capacity of less than 300kW. The remainder is assigned to mid voltage level. Water and land-bound PV supply is apportioned to mid and high voltage level with a 3:1 ratio, except for the offshore category, which is fully allocated to high voltage level.

Research results will be presented in the form of a country map and a cumulative distribution function (CDF) graph for; low voltage PV supply; mid voltage PV supply,  low voltage self-sufficiency,  and mid voltage self-sufficiency. All maps and CDF graphs provide information for all three 2050 scenarios, a 2030 scenario and the present situation. 

The PV supply calculation module described above is part of our Advanced Scenario Management model. This model consists of a number of supply and demand modules (traditional building demand, heat pump demand, electric vehicle demand, PV supply and wind turbine supply), each producing low voltage (neighborhood), mid voltage (municipality) and high voltage (country) level electricity profiles. Together, they allow for supply-demand system analysis for multiple voltage levels and energy transition scenarios.

How to cite: van Sark, W., Nortier, N., and Mewe, A.: Spatio-temporal potential profiles for building, land and water-bound photovoltaic installations for future Dutch energy transition scenarios, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4468, https://doi.org/10.5194/egusphere-egu22-4468, 2022.

The variable nature of wind power generation poses many challenges. The scientific community has addressed many of these challenges and made much progress in the recent years. These include, for example, quantifying resource variability, constraining future climate change impacts on wind energy, and suggesting robust system designs. Much of this research, however, has been academic in nature and lacks bi-directional interactions with stakeholders who make real world decisions. As an attempt to facilitate more exchange with industry partners, we present first results of a stakeholder workshop. The workshop theme is the role of climate in wind energy site assessments, including aspects related to climate variability and climate change. In addition to direct yield related parameters, such as capacity factors and their variability, we also plan to address relevant indirect effects that are less extensive researched, such as climate-induced changes in bat activity that trigger generation interruptions and blade icing. We report on the workshop design, highlight lessons learned and illustrate how the stakeholder feedback is used in shaping the precise research questions to be addressed in the course of the KliWiSt project [1]. KliWiSt is a German acronym that stands for the impact of climate change on wind energy site assessments. The general transdisciplinary approach can be adapted and used in other stakeholder-oriented research projects.

How to cite: Schaffer, L., Borowski, J., Dörenkämper, M., Jacob, D., Keup-Thiel, E., Sieck, K., and Wohland, J.: Let’s talk: incorporating stakeholder needs in climate-science based wind resource assessments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4463, https://doi.org/10.5194/egusphere-egu22-4463, 2022.

How to cite: Roithner, M., Zeyringer, M., and Price, J.: Evaluation of varying spatial resolution in power system modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11025, https://doi.org/10.5194/egusphere-egu22-11025, 2022.

Extreme exploitation of fossil fuels has imposed catastrophic scarcity of energy sources, worldwide. Bioenergy is extremely pertinent to renewable energy alternatives. Municipal solid waste (MSW) and industrial organic waste has sufficient energy potential due to ample organic content. Moreover, landfilling being most economic disposal method offers incubated treatment of solid waste along with production of gases for energy generation. Bioreactor landfills are the new advancements to conventional landfills which accelerates the bioenergy production through incorporation of leachate recirculation. In this research, four simulated anaerobic landfill bioreactors co-disposed with paper mill sludge (PMS) as an industrial organic waste and MSW in three different proportions were installed. One reactor was kept as control (BRL1) with sole disposal of MSW along with other co-landfilled reactors with ratios of PMS and MSW as 1:3 (BRL2), 1:1 (BRL3) and 3:1 (BRL4). Leachate produced from each landfill reactors was utilized for moisture maintenance and degradation enhancement through its recirculation. Periodic analysis of leachate physico-chemical parameters and chromatographic analysis of landfill gas were performed until 300 days of landfilling. Artificial neural network (ANN) modeling was performed to predict biogas production and leachate organic pollutants removal from operating anaerobic landfill simulators. Experimented physico-chemical parameters including pH, electrical conductivity, volatile solids, volatile fatty acids, total alkalinity, ammoniacal and total nitrogen were used as input layer for neural network modeling. Different sets of output layers for leachate pollutants (chemical oxygen demand and total heavy metal concentrations) and biogas yield were decided for individual ANN training. Levenberg-Marquardt algorithm was used to train data sets with 10 number of hidden layers, 15% validation and 15% testing. Moreover, the performance of each landfill reactor was optimized statistically using back propagation network model. Over the completion of landfilling process, BRL3 with equal co-disposal ration of PMS and MSW fetched maximum biogas yield of 146.14 mL/VS/d, which was 1.53, 1.33 and 2.35 times more than that of BRL2, BRL4 and BRL1, respectively. The prediction model could forecast and statistically optimize the biogas content with excellent fitting with experimented data (R² > 0.95). This study expands the dimensions of experimental and mathematical investigations for co-landfilling practices for not only acquiring energy out of simultaneously co-landfilled solid wastes from distinct origins but also supports the attempts for diminishing its leachate pollutant concentrations.

Keywords: Artificial neural network, Bioenergy production, Landfills, Co-disposal, Municipal solid waste, Paper mill sludge

How to cite: Srivastava, A. N. and Chakma, S.: Artificial Neural Network Modeling for Prediction of Bioenergy Production and Organic Pollutant Removal from Simulated Co-Disposed Landfills , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-118, https://doi.org/10.5194/egusphere-egu22-118, 2022.