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The Spanish government is a strong advocate of reducing CO2 emissions and has made a clear commitment to the implementation of renewable energies. As reflected in Spain's National Energy and Climate Plan (NECP), its objective is to double the current capacity of pumped hydropower storage (PHS) plants by 2030. Therefore, the study presented here is both current and forward-looking. This paper presents the results of the analysis of the technical potential of installing floating photovoltaic (FPV) plants at 25 PHS plants in Spain, i.e., the total capacity of Spanish hydropower plants. The study was conducted using various assessment indicators: the global horizontal irradiance ratio, electrical efficiency ratio, area required ratio, pumping area ratio, volume ratio of water pumped per day, and achievable power ratio. In summary, the following conclusions can be drawn: (i) The global horizontal irradiance ratio indicates whether a FPV plant is economically viable. From this point of view, the Aguayo PHS plant and the Tanes PHS plant are not suitable, as this ratio is very low; (ii) the compliance with the electrical efficiency ratio is flexible, and all hydropower plants meet this criterion; (iii) maximising the use of the assigned grid connection capacity is one of the goals sought by electrical companies when implementing FPV plants at existing PHS plants. The following hydropower plants are not suitable for the implementation of an FPV plant in view of the following: La Muela I, La Muela II, Aguayo, Sallente, Aldeadavila II, Moralets, Guillena, Bolarque II, Montamara, and IP; (iv) if the aim is energy storage, the following hydropower plants are not suitable for the implementation of an FPV plant: the La Muela I, La Muela II, Tajo de la Encantada, Aguayo, Sallente, Aldeadavila II, Conso, Moralets, Guillena, Bolarque II, Tanes, Montamara, Soutelo, Bao-Puente Bibey, Santiago de Jares, IP, and Urdiceto; (v) if the aim is to expand an FPV plant already installed at a PHS plant, the following hydropower plants do not meet this criterion: the La Muela I, La Muela II, Aguayo, Sallente, Aldeadavila, Moralets, Guillena, Bolarque II, Montamara, and IP. There are only eight hydropower plants that meet conditions (i), (iii) and (iv): the Villarino, Torrejon, Valparaiso, Gabriel y Galan, Guijo de Granadilla, Pintado, and Gobantes. [ABSTRACT FROM AUTHOR]

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Soiling of PV modules is an issue causing non-negligible losses on PV power plants, between 3 and 4% of the total energy production. Cleaning is the most common way to mitigate soiling. The impact of the cleaning activity can be significant, both in terms of cost and resources consumption. For these reasons, it is important to monitor and predict soiling profiles and establish an optimal cleaning schedule. Especially in locations where raining is irregular or where desert winds carry a high concentration of particles, it is also important to know how precipitation and dust events affect the soiling ratio. This paper presents a new model based on environmental conditions that helps the decision-making process of the cleaning schedule. The model was validated by the analysis of five large grid-connected PV plants in Spain over two years of operation, with a total power of 200 MW. The comparison between the model and soiling sensors at the five locations was included. Excellent results were achieved, the mean difference between sensors and model being 0.71%. [ABSTRACT FROM AUTHOR]

In recent years, important regulatory changes have been introduced in Spain in the fields of self-consumption and energy tariffs. In addition, electricity prices have risen sharply, reaching record highs in the last year. This evidences the need to conduct new research studies in order to provide an accurate picture of the profitability of battery energy storage systems and photovoltaic systems. This paper proposes a complex simulation tool developed to assist in the optimal design of these kinds of facilities. The tool is used in this study to analyze the benefits of including batteries in PV systems under different self-consumption models, different consumer profiles and different locations across the country. The research results indicate that at current electricity prices, the use of batteries is less profitable than selling excess energy to the grid, unless the price of batteries drops drastically by more than 50% in all the cases analyzed. However, at current battery prices, they become a valuable resource in facilities that do not feed energy surplus into the grid. [ABSTRACT FROM AUTHOR]

In this paper, the main objective is the simulation of the electric supply for homes in remote areas located in Morocco (Oujda and Ouarzazate), Spain (Granada), and Algeria (Bechar). This simulation study is divided into two ideas, the first one is to optimize the hybrid system under a varied number of houses and the second part is to fix it in chosen values. This work relied on the particle swarm optimization (PSO) method to optimize and analyze the proposed stand-alone photovoltaic/wind/diesel/battery hybrid system. MATLAB software is used to run the simulations and to carry out the optimal solutions of the optimized system using a developed PSO algorithm. The PSO approach contains five principal operator axes, which are problem definition, PSO initial parameters, initialization, PSO main loop, and then run of the algorithm. Optimizing the system component sizes and reaching the minimum cost of energy (COE) were the function objectives of this optimization study. Moreover, calculation of the hydrogen production from the generated energy by PV and wind systems is performed. [ABSTRACT FROM AUTHOR]

• Pioneer Spain: first country to include in grid code the synthetic inertia capability. • Synthetic inertial response of a PV inverter studied based on the Spanish grid code. • Analyzed the role of power plant controller in the dynamic response of the facility. • PV system able to contribute to frequency control providing an inertial response. As the large-scale integration of renewable energy grows, inertia in power systems is reduced, which causes the rate of change of frequency to increase and worsens the frequency nadir during disturbances. There is, therefore, an urgent need to accelerate the development of international standards and regulations that require solar PV systems and other renewable installations to also contribute to stability in the network by emulating inertia. Spain is a pioneer in this field: it is currently the only country that includes the synthetic inertia technical requirement in its grid code. In this context, the present paper analyzes the synthetic inertial response of a PV system model that forms part of an actual PV power plant in Spain under two scenarios, according to its grid code: i) when measurements are conducted at the power conversion PV system level and hence only its control algorithms are executed; and ii) when measurements are conducted at the power plant level and the power plant controller also influences the response of the entire installation. Among its aims, this paper seeks to thoroughly assess the response of an actual PV power conversion system that has the capability of actively contributing to frequency regulation in a network and to critically analyze the suitability of having a power plant controller when the PV facility contributes to power-frequency control by means of an inertial response. The results reveal, at the power conversion PV system level, that the inertia emulation module significantly reduces the response times of the installation to changes in frequency -by more than 68% in the worst case under frequency increases, and by 73% under frequency decreases, thus contributing to more rapid power-frequency regulation in the network. However, at the power plant level, the power plant controller disturbs the PV power conversion system's behavior and causes the opposite effect: response times increase -up to more than 7% in the most unfavorable case when the inertia module is enabled. [ABSTRACT FROM AUTHOR]

Due to high competitiveness in the PV sector, despite the low degradation rate of crystalline silicon PV modules (below 0.5%/year), it is still important for utilities to know its actual value due to its impact on energy yield and hence, profitability, over the lifetime of a PV plant. However, uncertainties related to both the influence of downtime periods due to problems that may appear under normal operation of a commercial PV plant and to the measurement of degradation rates at PV plant level make this a challenging task. In order to obtain a significant value, in this paper, three measuring methods with different uncertainty sources are used for 82 MWp of PV modules on different locations in Spain and Portugal over 10 years. According to the different methods used and PV plants analyzed, excluding PV plants with problems, a range of degradation rates between 0.01 and 0.47%/year has been found. The overall average value observed is 0.27%/year. The findings of this work have also revealed the great importance of good operation and maintenance practices in order to keep overall low degradation rates. [ABSTRACT FROM AUTHOR]

Solar cells lose efficiency as the operating temperature increases under normal operating conditions, resulting in a very significant power output reduction. This issue is most relevant in areas with the highest photovoltaic energy harvesting potential, where irradiance and ambient temperature are particularly high. A novel cooling system for commercial photovoltaic modules based on low-enthalpy geothermal cooling is proposed in this paper. Excess heat is evacuated from the solar module in a clean and efficient manner by a single-phase and close-loop cooling circuit that uses the underground as a natural heatsink. In addition, a thermoelectrical theoretical model is presented, that allows the optimization of the flowrate and the maximization of the extra power generation of the cooled module. A prototype was manufactured and tested in outdoor conditions in September 2021 in Spain. Test results are in good agreement with the theoretical model, which has been used for prediction of the performance of the system for a typical meteorological year in the region. A peak efficiency improvement of 10.7% is calculated for the month of July, with an optimal flowrate of 1.8 l/min per square meter of solar module. A yearly weighted average power gain of up to 4.9% is also calculated. [ABSTRACT FROM AUTHOR]

Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic and concentrating solar thermal power plants. Accurate solar nowcasting becomes necessary to detect these sudden changes of generated power and to provide the desired information for optimal exploitation of solar systems. In the framework of the International Energy Agency's Photovoltaic Power Systems Program Task 16, a benchmarking exercise has been conducted relying on a bouquet of solar nowcasting methodologies by all-sky imagers (ASI). In this paper, four ASI systems nowcast the Global Horizontal Irradiance (GHI) with a time forecast ranging from 1 to 20 min during 28 days with variable cloud conditions spanning from September to November 2019 in southern Spain. All ASIs demonstrated their ability to accurately nowcast GHI, with RMSE ranging from 6.9% to 18.1%. Under cloudy conditions, all ASIs' nowcasts outperform the persistence models. Under clear skies, three ASIs are better than persistence. Discrepancies in the observed nowcasting performance become larger at increasing forecast horizons. The findings of this study highlight the feasibility of ASIs to reliably nowcast GHI at different sky conditions, time intervals and horizons. Such nowcasts can be used either to estimate solar power at distant times or detect sudden GHI fluctuations. • ASI-based GHI nowcasts outperform persistence model under cloudy conditions. • Under clear skies, three ASIs reveal more accurate nowcasts than persistence. • ASIs forecasts are more accurate from persistence at increasing forecast horizons. [ABSTRACT FROM AUTHOR]

Heating up of photovoltaic modules during operation results in a significant power output reduction. This effect is especially relevant in regions with the highest photovoltaic potential, where irradiance and ambient temperature are particularly high. In this paper, a novel low enthalpy geothermal cooling system that improves the efficiency of a commercial solar module is described and experimentally validated. Two heat exchangers, one attached to the backside of the module, and another introduced inside a 15 m deep borehole, are connected in a closed circuit. A water-based coolant is pumped through the system, evacuating the excess heat from the module, and dissipating it underground in a clean and efficient manner, without additional water consumption after filling the system. The performance of the cooling system was experimentally tested by implementing it, for the first time, in a single-axis solar tracking isolated photovoltaic facility. Extensive tests were carried out in Spain, between September 2021 and August 2022 under a wide variety of environmental conditions. The efficiency improvement system has demonstrated its technical feasibility over a one-year period, showing a peak net efficiency improvement up to 13.4 %. Moreover, a positive net efficiency improvement has been demonstrated all year long, even during the winter months. [ABSTRACT FROM AUTHOR]

Solar PV technologies have been expanding rapidly, and the installed power has increased, especially in the last decade. Their inclusion in university buildings arises as a key factor for sustainable transition in cities, since they have an important potential as case studies for urban experimentation positive effects on students and other stakeholders. This paper proposes a method to determine the availability for installing solar PV in universities' rooftops, considering simulation and cartography data, together with a final experimental validation stage. Unavailable areas for each rooftop are determined, including obstacles, the inner use of the rooftop and shadowed areas. Finally, the method verifies the technical suitability for all the proposed scenarios and applies an economic-environmental multicriteria evaluation to select the most suitable one. The methodology is validated in the Universitat Politècnica de València Vera-Campus. In total, 88913 m2 of the rooftops are suitable for solar PV incorporation, representing 48 % of the total surface. 52 % of the solar PV installable capacity takes place in surfaces which can incorporate more than 100 kW, 20.6 % between 50 and 100 kW and 27.4 % less than 50 kW. Finally, the multicriteria evaluation proved that the scenario with all the possible installations is the most suitable one. [ABSTRACT FROM AUTHOR]

The increased penetration of renewable energy sources (RESs) as an effective mechanism to reduce carbon emissions leads to an increased weather dependency for power and energy systems. This has created dynamic operation and degradation phenomena, which affect the lifetime estimation of the assets operated with RESs. For the reliable and efficient operation of RES it is crucial to monitor the health of its constituent components and feature selection is a crucial step for building robust and accurate health monitoring approaches. In this context, this paper presents a probabilistic feature selection approach, which probabilistically weights and selects features through a heuristic and iterative process for an improved asset lifetime estimation. Power transformers are key power grid assets and they are used to demonstrate the validity and impact of the proposed approach. The approach is tested on two different photovoltaic power plants operated in Spain and Australia. Results consistently show that the proposed feature-selection approach reduces the prediction error and consistently selects relevant features. The approach has been applied to transformer lifetime estimation, but it can be generally applied to assist in the lifetime estimation of other components operated in RESs. Part of the studies presented here as well as source codes are all open-source under the GitHub repository https://github.com/iramirezg/FeatureSelection. • Probabilistic feature selection approach for improved asset lifetime estimation. • Integration of environmental features for improved renewable-operated asset lifetime. • Systematic and robust feature weighting methodology. • Improved transformer lifetime estimation including sensor and environmental data. • Validated on two real photovoltaic power plant case studies. [ABSTRACT FROM AUTHOR]

Large deployment of photovoltaic (PV) installation worldwide demands reliability assurance of the systems to maintain the confidence in the markets. With the diversity of PV applications, it is essential the detection of circumstances that can be the root of failure mechanisms, such as transportation and installation of the modules. They are one of the main sources of induced vibrations, which, in its turn, can provoke defects and damages in the PV modules. In this work, we have measured and analyzed tri-axial accelerations and mechanical vibration that photovoltaic crystalline modules withstand during transportation by road, including loading and unloading operations. We have also analyzed the natural oscillation frequencies, the resonance phenomena and the highest impacts. It is concluded that a proper fastening of the load inside the truck is necessary and that high impacts during loading and unloading should be avoided. Packing the modules to reduce vibrations is also recommendable. Several solutions to perform this are proposed. [ABSTRACT FROM AUTHOR]

The integration of a CSP tower system with a PV solar field, sharing a thermal energy storage, is modeled and discussed. The tower system uses a new-design solid particle fluidized bed receiver integrated with a thermal storage, where hot particles are directly collected to store daily energy for overnight production of electricity. The PV solar field is aimed to supply the daily energy demand; when there is a surplus of PV energy production, the electric energy is converted to heat and accumulated in the thermal storage too. The integration of the two energy systems is modeled, building efficiency functions for all the sub-components of the integrated plant (heliostat field, receiver, storage, power block, PV field). Yearly simulations are performed for two different locations, Spain and Australia, obtaining that a system with a peak power of 10 MWe CSP + 15 MWe PV can supply—with a limited curtailment—a fraction of more than 60% (respectively, 62% and 68%) of a realistic electric load with a peak demand around 10 MW, to be compared with the 45/47% of the same load obtained adopting a PV-only system with the same overall peak power. In the integrated system, PV directly supplies 40/41% of the load, the remaining 23/28% being produced by the power block (mainly fed by the CSP). [ABSTRACT FROM AUTHOR]

The decreasing costs of solar photovoltaic (PV) technology have led to an exponential growth in the use of PV self-consumption systems. This development has encouraged the consideration of battery energy storage systems (BESS) as a potential means of achieving even more independence from the fluctuating grid electricity prices. As PV technology and energy storage costs continue to decline, both technologies will likely play an increasingly important role in the renewable energy sector. The profitability of batteries in PV self-consumption systems is largely influenced by the price of consumed electricity and the price at which surplus energy is remunerated. However, strategies in PV-BESS self-consumption systems typically do not take electricity prices into consideration as a variable for decision making. This study simulates and analyzes battery operation strategies that take into account electricity prices. The simulations are performed using real industrial consumption data and real electricity prices and tariffs, they cover the entire lifespan of the batteries, and include aging and degradation due to use and cycling. A techno-economic model is used to evaluate the advantages of incorporating these battery operational strategies into an actual PV-BESS system. The results demonstrate that the proposed strategies enhance the savings that batteries can provide. [ABSTRACT FROM AUTHOR]

Solar photovoltaic self-consumption is an attractive approach to increase autarky and reduce emissions in the building sector. However, a successful deployment in urban rooftops requires both accurate and low-computational-cost methods to estimate the self-consumption potential and economic feasibility, which is especially scarce in the literature on net billing schemes. In the first part of this study, a bottom-up GIS-based techno-economic model has helped compare the self-consumption potential with net metering and net billing in a Mediterranean municipality of Spain, with 3734 buildings in total. The capacity was optimized according to load profiles obtained from aggregated real measurements. Multiple load profile scenarios were assessed, revealing that the potential self-sufficiency of the municipality ranges between 21.9% and 42.5%. In the second part of the study, simplified regression-based models were developed to estimate the self-sufficiency, self-consumption, economic payback and internal rate of return at a building scale, providing nRMSE values of 3.9%, 3.1%, 10.0% and 1.5%, respectively. One of the predictors with a high correlation in the regressions is a novel coefficient that measures the alignment between the load and the hours with higher irradiance. The developed correlations can be employed for any other economic or demand scenario. [ABSTRACT FROM AUTHOR]

The rapid expansion of photovoltaics within the global energy market requires increasing use of land, a limited resource where different uses compete. In this respect, photovoltaic systems that combine electricity generation with land use for crops are becoming increasingly important. This article proposes an analytical model validated in an operating bifacial photovoltaic plant during the summer months. This analytical model considers view factors and heat transfer calculations, as well as an electrical model of the photovoltaic modules. A study was carried out on a commercial solar power plant (11.24 MWp) in Seville, southern Spain, where different vegetal species were planted in two strings, and string performance was monitored. Nine crop species with different irrigation and light requirements, offering different albedo parameters and thermal characteristics. The results show advantages from the point of view of module temperature and power gain. This paper provides regressions for the characterisation of the photovoltaic agricultural plant, with R2 higher than 85%, both for module temperature and energy exported in the string with crops. [Display omitted] [ABSTRACT FROM AUTHOR]

Rooftop photovoltaic generation can help cities become key players in the transition to clean energy. The optimal solar photovoltaic production on rooftops depends on two angles: tilt angle and azimuth angle. It is accepted in all studies that the ideal orientation of photovoltaic modules is toward the south (north) in the northern hemisphere (south). In contrast, the determination of the optimum tilt angle is more complex, and there are different equations for its calculation. Most of these equations do not take albedo into account. In this work, 47 Spanish province capitals representing the most populated cities have been studied with different equations for the calculation of the optimum annual tilt angle (Technical report by the Spanish Institute for the Diversification and Saving of Energy (IDAE), Lorenzo's and Jacobson's equation) and different types of albedo. Accounting for the geographical and the meteorological conditions of the cities, we analyzed the optimum tilt angle through a Mathematica© optimization code. The influence that different variables have on optimum tilt angle has been quantified by means of the term relative energy harvested. The use of the equations as a function of latitude increases the annual relative energy harvested by increasing the albedo. When the albedo is 0.2, the annual relative energy harvested is very similar in all equations. Comparing to the method that maximizes the total irradiation incident on a tilted surface, the minimum and maximum value of the percentage of relative energy harvested per year were 0.01 and 2.50% for the IDAE guideline, 0.00 and 2.38% for Lorenzo's equation, 0.00 and 2.46% for Jacobson's equation. A simplified polynomial regression model to estimate optimum tilt angle as a function of latitude, altitude and albedo has been proposed as well. [ABSTRACT FROM AUTHOR]

Photovoltaics (PV) has reached high level of maturity in terms of material efficiency and low production costs. For this reason, nowadays, lot of emphasis is put on the reduction of the operation and maintenance costs. Soiling is one of the issues that most affect these costs. So, the understanding of its electrical and economic implications is essential to optimize the cleaning routines and minimize the associated costs. This paper investigates the possibility of estimating soiling directly from PV performance data, without the need of installing specific soiling monitoring equipment, which typically needs careful and regular maintenance. Five analytical methods are evaluated and applied to the data of PV modules of different technologies (m-Si, CdTe and CIS). An experimental campaign is conducted in a location in Southern Spain with low-moderate levels of soiling. The methods show promising accuracies when used to obtain the soiling losses of a module, especially during soiling-intense and long dry periods. • Soiling losses were directly extracted from the performance data of PV modules. • The goodness of five different analytical methods was assessed. • These methods allow soiling to be quantified without need for additional sensors. • Each methodology was applied to PV modules of three different technologies. • The accuracies of the methods were higher in periods with greater soiling losses. [ABSTRACT FROM AUTHOR]

Solar energy is in high demand due to its environmental benefits and economic potential; however, concerns remain about the total impact it holds. In 2020, for Spain, Castilla-La Mancha was the second autonomous community with the highest photovoltaic energy production. Thus, a systematic review on 15 large-scale PV solar energy projects was carried out to assess the industry impacts, through environmental impact assessment (EIA), within the Autonomous Community of Castilla—La Mancha. An estimation of these impacts from a pre-operational approach is presented, based on primary energy needs and emissions discarded during its life cycle due to the manufacture, operation, and recycling of the photovoltaic modules. Based on both the life cycle assessment (LCA) and EIA, the approaches were compared with the results obtained. The obtained results suggest that determining the actual impacts of power plants in this region could provide justified information for the public administration and technicians in the measures for the installation and operation of PV plants and the future benefits of renewable solar technologies. Furthermore, the results indicate the possibility to recognize the relationship between the size of the plant and a high generation capacity, with a shorter time to pay for emissions from the manufacture and recycling of panels, suggesting that it is around 1.66–2.08 years for the Castilla-La Mancha region. [ABSTRACT FROM AUTHOR]