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Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design. [ABSTRACT FROM AUTHOR]

In the course of analysing the annual air temperature in Wrocław (TWr), a rapid change of the thermal regime was found between 1987 and 1989. TWr increased by >1°C, a strong, statistically significant positive trend emerged. The analysis of processes showed that strong warming in the cold season of the year (December–March) occurred as a result of an increase in the NAO intensity and warming in the warm season because of increased sunshine duration in Wrocław (ShWr). Multiple regression analysis has shown that the winter NAO Hurrell's index explains 15% of TWr variance, and the ShWr of the long-day (April–August) period 49%, whereas radiative forcing 5.9%. This indicates that the factors incidental to the internal variability of the climate system explain 64% of the TWr variability and the effect of increased CO2 concentration only ~6%. The reason for this rapid change of the thermal regime was a radical change in macro-circulation conditions in the Atlantic-European circular sector, which took place between 1988 and 1989. The heat, which is the cause of warming in Wrocław, comes from an increase in solar energy inflow (April–August) and also is transported to Europe from the North Atlantic surface by atmospheric circulation (NAO). These results indicate that the role of CO2 in shaping the contemporary temperature increase is overestimated, whereas the internal variability of the climate system is underestimated. [ABSTRACT FROM AUTHOR]

Solar and wind energy are expected to play a key role in creating a climate-neutral Europe by 2050 and decarbonizing energy production in general, albeit requiring significant deployment. This presupposes that the population accepts such energy sources, thus necessitates understanding how people perceive energy systems. Unlike the abundant literature about wind energy, social acceptance of solar energy has received less attention, especially concerning large solar installations. Opinion polls indicate that solar energy enjoys a high level of socio-political acceptance and is preferred to other renewables, although it is unclear whether this acceptance persists as the technology is deployed on a large scale. This paper helps close this gap by describing the results of a representative survey (n = 601) conducted using a between-subject design to examine how attitudes of the public towards solar energy vary based on the size of installations, how the latter compare to attitudes towards wind energy, and what the role of affect is in the former. Results reveal that the stronger preference for solar power decreases to a similar level as that for wind energy when comparing installation of similar sizes, highlighting that solar energy installations may not easily be scaled up. The study also shows that affect plays an important role in forming people's attitudes towards wind and solar, especially concerning large-scale installations. This underlines the need for policymakers and project developers, who aim to deploy renewables on a large scale, to attend to the affective component of decision-making. • Between-subject design survey with a representative sample (n = 601). • Positive attitudes towards solar energy are mediated by installation size. • Solar parks are less positively perceived than rooftop PV installations. • When comparing installations of similar sizes, solar is not more popular than wind energy. • Large installations evoke stronger emotions, which in turn influence attitudes. [ABSTRACT FROM AUTHOR]

The number of large-scale solar thermal installations has increased rapidly in Europe in recent years, with 70 % of these systems operating with flat-plate solar collectors. Since these systems cannot be easily switched on and off but directly depend on the solar radiation, they have to be combined with other technologies or integrated in large energy systems. In order to most efficiently integrate and operate solar systems, it is of great importance to consider their expected energy yield to better schedule heat production, storage and distribution. To do so the availability of accurate forecasting methods for the future solar energy yield are essential. Currently available forecasting methods do not meet three important practical requirements: simple implementation, automatic adaption to seasonal changes and wide applicability. For these reasons, a simple and adaptive forecasting method is presented in this paper, which allows to accurately forecast the solar heat production of flat-plate collector systems considering weather forecasts. The method is based on a modified collector efficiency model where the parameters are continuously redetermined to specifically consider the influence of the time of the day. In order to show the wide applicability the method is extensively tested with measurement data of various flat-plate collector systems covering different applications (below 200 ° Celsius), sizes and orientations. The results show that the method can forecast the solar yield very accurately with a Mean Absolute Range Normalized Error (MARNE) of about 5 % using real weather forecasts as inputs and outperforms common forecasting methods by being nearly twice as accurate. • Self-learning approach with only very few parameters to be determined. • Automatically considers seasonal changes and pollution of collector fields. • Simple regarding its mathematical structure and straightforward to implement. • Experimental long-term validation with data from various collector systems. • Superior to state-of-the-art forecasting methods regarding accuracy. [ABSTRACT FROM AUTHOR]

This paper describes the studies carried out in project PASCOOL to document and assess the thermal performance of selected buildings in Southern Europe and to identify possible improvements. Twenty-three buildings from nine European countries were surveyed and monitored for a shprt period during summertime. The measurements and survey data obtained formed the basis for sensitivity studies with thermal simulation. The selection encompassed buildings of typical construction, including both recent and traditional, residential and non-residential. The sensitivity studies addressed the effects of shading, thermal inertia, ventilation, window orientation and colour of external surfaces,envelope insulation, and occupancy patterns. The paper presents the methodology adopted for the measurements and sensitivity studies and discusses the main conclusions drawn from the studies. It identifies options for improving occupant thermal comfort with little or no mechanical cooling. [ABSTRACT FROM AUTHOR]

This paper describes solar thermal technologies for the solution of long term Europe`s energy problem with better reliability. A short overview about solar energy is explained with a basic energy analysis. This report also includes some evaluations and discussions of solar energy systems in the following pages. The general purpose of the article is to understand how efficiently solar thermal systems generates energy, and solve the Europe`s increasing energy demand in our century. [ABSTRACT FROM AUTHOR]

In line with the energy development strategy of Europe, it is necessary to implement energy efficient buildings, in which the external enclosures are converters of solar energy to thermal. Therefore, the purpose of the publication was the scientific substantiation and development of the solar heating system with the use of rooftop solar panels. Graphical and analytical dependences of the coefficient of thermal efficiency of the solar panel in heat supply system from the angles of solar radiation incoming and the density of the radiation flux were obtained. Analysis of the results showed that the coefficient of thermal efficiency of the solar panel without transparent coating with the placement of pipelines of the circulation circuit of the coolant over the heat absorber increases by 50%. [ABSTRACT FROM AUTHOR]

Biomass can help reaching climate goals in many sectors. In electricity generation it can complement variable renewables or, if coupled with carbon capture and storage (CCS), also provide negative emissions. This paper adds to the existing literature by focusing on the cost-efficiency of balancing variable renewables with biomass and by providing an indication on acceptance of these technologies. A dynamic optimization model is used to analyse the role of biomass in the European electricity system pending different emission targets for 2050. The results are compared with survey data on investment preferences for biomass technologies, and wind and solar power. The formulation of the emission target greatly influences the cost-efficient use of biomass, with more concentrated use observed, if bioenergy with CCS is allowed. This indicates that a Europe-wide emission target could be more cost-efficient than separate national targets. Both governmental and nongovernmental actors tend to be negative towards investing in biomass technologies, although with greater variation if combined with CCS, indicating possible challenges for implementation. Their attitudes towards wind and solar power are much more positive in all countries, supporting the continuation of the existing trend of an increasing share of variable renewables in the European electricity system. • Formulation of the emission target greatly influence biomass use and distribution. • Europe-wide emission targets may be preferred when negative emissions are required. • Negative emissions combined with natural gas are cost-efficient variation management. • Preferences to invest in bio-based technologies are low in all countries. • Non-governmental actors strongly oppose bioenergy with carbon capture and storage. [ABSTRACT FROM AUTHOR]

• First power system study considering regional differences in cost of capital. • System design is significantly affected compared to homogeneous reference. • Levelized costs of wind power decrease. • Levelized costs of solar photovoltaic increase. • Levelized costs of electricity are unevenly distributed across Europe. In order to reduce greenhouse gas emissions of the power sector, high shares of renewable power sources need to be integrated into existing systems. This will require vast amounts of investments. Cost of the capital needed for these investments are unevenly distributed among European regions. They show a clear North-South and West-East divide, which has not exhibited significant signs of narrowing in recent years. Power system studies investigating a continent-wide European power system, however, usually assume homogeneous cost of capital. The objective of this paper is to investigate how regional differences in cost of capital affect the result of these studies with respect to the optimal power system design. Our analysis is based on power system optimization with inhomogeneous cost of capital in Europe. We find that assuming homogeneous cost of capital leads to estimates on the levelized costs of electricity in a highly renewable European power system, which are too conservative. The optimal system design is significantly affected compared to an inhomogeneous scenario. In particular, we show that inhomogeneous cost of capital favors overall wind power deployment in the case of Europe, while the investment in solar power decreases. [ABSTRACT FROM AUTHOR]

Both wind and solar irradiance are considered as variable sources of energy. The generated power is dependent on varying weather conditions. In this study, three indicators are introduced: generation power-to-storage day ratio, photovoltaic-to-wind energy ratio, and reliability improvement indicator. The values of the indicators are determined for 5701 points located in Europe. The results have been presented on charts illustrating statistics of the indicators as well as on maps. This study illustrates various aspects of the solar and the wind energy potential in the context of energy storage. The results show that for the majority of locations, the cost of 1 kWh of storage must be up to 3.2 times less than the cost of 1 kW of a photovoltaic system. Also, it should be up to six times less than the unit cost of the wind turbine system at 50 m in order to decrease the system cost, depending on the number of autonomy days. For most of the locations, the nominal power of the photovoltaic system should be significantly lower than the power of the wind turbine if the system is to meet the required reliability. If the reliability of the power supply has to be increased from 95% to 98%, the nominal power of the photovoltaic generator has to be increased, depending on the assumed days of autonomy, between 1.25 and 1.45 times and the power of the wind turbine at 50 m between 1.3 and 2 times for the greater number of locations. [ABSTRACT FROM AUTHOR]

Reanalysis data such as MERRA and MERRA-2 are commonly used to derive solar and wind power generation time series, and to estimate their resource potentials. However, the spatial resolution of the reanalysis data (0.5° latitude x 0.625° longitude for MERRA-2) is not sufficient for small-scale energy system models (e.g. states and cities), nor for siting potential projects. This paper uses the MERRA-2 reanalysis data in combination with additional data sources for land-use, topography, and protected areas, in order to obtain accurate global resource potential maps with a spatial resolution of 15 arcseconds. We also generate time series for individual cells of the rasters and identify the best locations for future wind and solar projects. The results are validated against measured hourly generation data of wind and photovoltaic power plants in Europe. [ABSTRACT FROM AUTHOR]

Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system's required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system's backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network. [ABSTRACT FROM AUTHOR]

A benchmarking exercise was organized within the framework of the European Action Weather Intelligence for Renewable Energies ("WIRE") with the purpose of evaluating the performance of state of the art models for short-term renewable energy forecasting. The exercise consisted in forecasting the power output of two wind farms and two photovoltaic power plants, in order to compare the merits of forecasts based on different modeling approaches and input data. It was thus possible to obtain a better knowledge of the state of the art in both wind and solar power forecasting, with an overview and comparison of the principal and the novel approaches that are used today in the field, and to assess the evolution of forecast performance with respect to previous benchmarking exercises. The outcome of this exercise consisted then in proposing new challenges in the renewable power forecasting field and identifying the main areas for improving accuracy in the future. [ABSTRACT FROM AUTHOR]

Besides continuous implementation of concentrating solar power plants (CSP) in Europe, which stipulate cost reduction by mass production effects, further R&D activities are necessary to achieve the cost competitiveness to fossil power generation. The European Concentrated Solar Thermal Roadmap (ECOSTAR) study that was conducted by European research institutes in the field of CSP intends to stipulate the direction for R&D activities in the context of cost reduction. This paper gives an overview about the methodology and the results for one of the seven different CSP system concepts that are currently under promotion worldwide and considered within ECOSTAR. The technology presented here is the parabolic trough with direct steam generation (DSG), which may be considered as an evolution of the existing parabolic systems with thermal oil as heat transfer fluid. The methodology is explained using this exemplary system, and the technical improvements are evaluated according to their cost-reduction potential using a common approach, based on an annual performance model. Research priorities are given based on the results. The simultaneous implementation of three measures is required in order to achieve the cost-reduction target: Technical improvement by R&D, upscaling of the unit size, and mass production of the equipment. [ABSTRACT FROM AUTHOR]

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models' performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations it shows that combining an LSTM network with a CNN yields the best performance. However, regarding the chosen GoF measures, differences to the alternative approaches are fairly small. The hybrid model's advantage lies not in the improved GoF but in its versatility: contrary to an LSTM or a CNN, it produces good results under all tested weather conditions. [ABSTRACT FROM AUTHOR]

Industry sector has an important impact on primary energy consumption at the international level, and solar energy constitutes a real alternative to cover these energy needs partially. Among thermosolar concentration technologies, Linear Fresnel Collector (LFC) technology has some advantages that make it more accessible to industries. With the aim of providing new tools for easier decision-making processes, in the present work, several energy audits were carried out in industries (located in the south-west of Europe, with considerable steam consumptions), quantifying thermal and energy consumptions and defining both work schedules and seasonality. Afterwards, a comparison based on three factors was carried out: Thermal consumption regarding total industry consumption, the performance of the work during the solar schedule, and the quantification of the monthly average concentrated energy for a certain LFC facility. The analysis carried out according to these criteria showed different results for each case, making a global assessment necessary to suitably ponder each factor. This analysis ranked tomato industries as the most suitable for LFC technology, due to the fact that their main operating period was during the months with the highest solar isolation, and the solar schedule was completely integrated in a 24-h working day. Also, industrial waxes and laundries showed a good combination of both facts. [ABSTRACT FROM AUTHOR]