This study addresses the optimization issues of a Parabolic Trough (PT) power plant by retrofitting it with a photovoltaic (PV) plant to find the optimal configuration for already operational Concentrated Solar Power (CSP) plants. A simulation tool based on Modelica and OpenModelica has been developed to analyze and optimize the performance of CSP/PV hybrid plants under several grid limitation scenarios, one of which includes an electrical heater to utilize the PV surplus, considering the impact of hybridization on their overall performance and therefore also on their economic viability. The results obtained provide clear insights into how different configurations of CSP and PV plants interact and how certain variables, such as the PV ratio and thermal storage size, influence the overall performance of the hybrid plant.

The Weibull distribution is commonly accepted as the most suitable model for describing the annual distribution of Direct Normal Irradiance (DNI). However, when the annual DNI is assumed to follow a Normal distribution instead of a Weibull distribution, there is a notable increase in the cumulative annual values for unfavourable and worst-case scenarios. In this research, we assess the suitability of different statistical indexes for goodness-of-fit by applying them to the annual cumulative DNI and Global Horizontal Irradiance (GHI) data recorded at six locations with varying climates. Our observations reveal that, across all locations, the Representative Solar Year (RSY) aligns with the 50% Probability of Exceedance (PoE50) of a Normal distribution fitted to the observed data. We quantify that assuming the annual DNI conforms to a Weibull distribution, as opposed to a Normal distribution, results in a substantial decrease of approximately 7% in the annual cumulative value for the worst-case scenario. Based on our analysis, we find no compelling evidence to reject the hypothesis that the annual DNI follows a Normal distribution.

The short-term variability of solar resource is one of the main challenges faced by the large-scale implementation of photovoltaic (PV) systems today; this will increase as the installed power of solar PV increases. To evaluate its influence on electrical grid operation, it is essential to analyse the variability of solar resource based on high-frequency data, 30 s and shorter. In this study, the high-frequency measurements of Global Horizontal Irradiation (GHI) and Direct Normal Irradiation (DNI) recorded every 5 s at the radiometric station of the University of Seville for 20 years are analysed and characterised. For this purpose, a corrected database for GHI and DNI was obtained from the application of a correction methodology. To understand the reliability of this database it is required to know its uncertainty. This work proposes a methodology to quantify the uncertainty of high-frequency radiometric databases whose wrong data have been corrected. Applying it, the daily uncertainty is 2.69

This study aims to explore the potential of combined CSP and PV systems in high latitude areas. Several performance metrics are evaluated and compared with standalone CSP or PV plants to identify the benefits and challenges of deploying such hybrid plants. Six different sites have been selected and the ASDELSOL hybrid power plant simulation tool, developed by the Thermodynamics and Renewable Energies Group at the University of Seville, has been used. This simulation tool allows performing dynamic performance simulations of hybrid solar plants under various operation strategies, along with conducting economic evaluations. We have analyzed a hybrid solar plant composed of 50 MW PTC and 75 MW PV, with 10 hours of TES and a 15 MW electric heater to transfer excess PV energy to the TES tanks in a 50 MW base load operation strategy, where the main objective of the PV plant is to cover the self-consumption of the PTC plant. Results obtained show that PV/PTC hybridization reduces LCOE and increases CF compared to standalone PV or PTC plants. These improvements are more pronounced in regions where the contribution of PTC plants is lower. In high latitude regions, an N-S orientation of PTC fields achieves higher production than an E-W orientation. However, a combination of both orientations can optimize their production and performance. Finally, it is concluded that it is necessary to carry out feasibility studies in high latitude locations before dismissing them outright, as it has been observed that, in certain regions, hybrid PV/PTC solar plants can offer an effective alternative.

Vídeo en el que se reproduce al detalle los pasos a seguir para el desarrollo de una práctica de propiedades coligativas. El objetivo de la práctica es observar el aumento ebulloscópico que experimenta el agua al mezclarse con diferentes cantidades de cloruro de sodio o sal. Para ello en el vídeo, además de describirse el procedimiento y los elementos necesarios para desarrollar la práctica, se muestran los datos numéricos necesarios para poder calcular experimentalmente la constante de ebullición del agua. Ese recurso está dirigido a los estudiantes de la asignatura termodinámica de las titulaciones Grado en Ingeniería en Tecnologías Industriales, Grado en Ingeniería Química y Grado en Ingeniería de la Energía. Además de en estas asignaturas, el estudio de las propiedades coligativas está incluido en el programa de otros grados y asignaturas como Física, Química, Materiales, etc. Por ello, este recurso podría ser utilizado en estos otros ámbitos. Es idóneo para explicar experimentalmente el comportamiento de la temperatura de ebullición de diferentes sustancias simples o disolventes al añadirle diferentes solutos. Cuando una sustancia se disuelve en un disolvente, aparecen fuerzas adicionales que deben ser superadas por las moléculas del disolvente para poder pasar a la fase vapor. Por lo tanto, la energía necesaria para evaporar las mismas moléculas de la disolución es mayor que en el disolvente puro. Esto se traduce en un aumento de la temperatura de ebullición característica de cada disolvente que se puede caracterizar a partir de su constante ebulloscópica.

Thermodynamics is an engineering subject that is particularly difficult to teach and learn because it requires strong abstract theoretical concepts and extensive multidisciplinary knowledge. This manuscript introduces mind map learning as an alternative methodology for structuring both the learning and teaching processes in a transparent way for students in the context of thermodynamics. Mind maps help students to learn in a non-linear way promoting out-of-the-box thinking. In a quantitative pre–post study, the student knowledge outcomes were investigated through surveys and compared with the results of a control group. Factor analysis was carried out grouping four principal categories (66% of the total variance): visual insight to create links between pre-existing and new knowledge; motivation, related to curiosity to learn new concepts; applicability and critical thinking. Cronbach’s alpha was 0.84, which revealed good internal consistency. The results obtained are explained through constructivist and neuroeducation theories pointing out the relevance of the following concepts: alignment between pre-existing and new knowledge, learning improvement when multisensorial resources are used (like visual forms, font size, colors, hearing, speaking, etc.), and the impact of visual information on brain executive functions. The key to genuine education is curiosity and experience, as well as diving into hands-on learning, asking questions, and experimenting to truly grow.

In this work, we test and improve an algorithm proposed in previous studies to generate synthetic series of plausible solar years (PSY). The method provides 100 synthetic years of coupled global horizontal irradiance (GHI) and direct normal solar irradiance (DNI) in 1-min resolution. The algorithm uses 10–20 years of hourly coupled GHI + DNI datasets that can be retrieved for most of the locations of the world from satellite estimates. The method consists of three steps. In the first step, we use the probability integral transform method to obtain 100 annual set series at monthly scale. The second step, we downscale the synthetic sets from monthly to daily time resolution using a first-order autoregressive model (AR 1). In the last step, we use ND model for generate the 1-min synthetic data sets from daily sets. The algorithm is evaluated at five locations with different type of climate according to the Koppen-Geiger classification and at different temporal scales: annual, monthly, daily, and 1-min resolution. In all cases, synthetic PSYs series cover a wider range of scenarios than the observed series but maintaining their distribution. Results suggest that the synthetically generated PSYs are capable to reproduce the natural variability of the solar resource at any location facilitating the stochastic simulation of solar harnessing systems.

Since January 2017, SAM includes models for simulating concentrating collectors in industrial process heat applications (IPH). These IPH models are based on the more complex Concentrated Solar Power (CSP) models already available in SAM. Adapting the inputs of the IPH models to represent real industrial applications is difficult and often leads to convergence errors. SWIPH is a decision support tool that simplifies the entry of input variables needed in SAM's IPH models. In addition to providing default values for the industry sector selected, SWIPH uses supervised classification algorithms to predict if the combination of inputs introduced by the user leads to a converge error. When that is the case, it suggests the closest set of input variables that produces a valid simulation. SWIPH is able to predict with 94% accuracy whether the given inputs will produce a valid simulation or on the other hand, what kind of error would it raise.

In this paper, we present a description of how to use a web based tool employing the ND model by Larraneta et al. [1]. The tool is suited for downscaling DNI, GHI or coupled DNI and GHI from 1-h to 1-min. It requires only an annual solar radiation dataset in the hourly resolution as input and provides 1-min data in any location without local adaptation. We have applied the tool in three locations with different climates. The similitude between measured and generated DNI distributions has been evaluated through the Kolmogorov-Smimov test Integral (KSI) for annual synthetic 1-min datasets. Obtained KSI values range from 6.2 W/m(2) to 11.5 W/m(2).

El recurso de Realidad Virtual desarrollado para guiar en una visita virtual a una planta fotovoltaica permite al usuario, mediante una observación 360º, identificar los elementos principales que integran una planta de generación eléctrica fotovoltaica. A través del recurso, el usuario puede comprender los distintos componentes que se necesitan para operar una planta de estas características, además de las relaciones entre ellos. El objetivo de la actividad es dar a conocer cómo funciona una planta fotovoltaica, instalación que por los riesgos eléctricos inherentes a su operación, no permite el acceso físico a los usuarios. De este modo, el usuario es capaz de acceder al espacio industrial donde se ubican los componentes de la planta y ver su actividad de modo inmersivo. La aplicación del recurso de realidad virtual se propone para un uso docente y divulgativo. En el ámbito docente se propone como una herramienta audiovisual de soporte en las asignaturas de Energía Fotovoltaica y Energía Solar en los grados de Ingeniería de la Energía (GIE) y de Ingeniería de las Tecnologías Industriales (GITI), respectivamente. Además, el soporte de realidad virtual permitirá actividades de divulgación para dar a conocer las instalaciones fotovoltaicas, cómo se diseñan y operan.

The classification of days according to the solar radiation features is one of the tools frequently used for the solar resource assessment, modelling or forecasting. Recent studies discuss the appropriate classification method or number of types of days, but these studies usually don't take into account, at least in an explicit way, the relation between the types of days and the yield of solar plants. In this work, we compare the representativeness of the types of days defmed by two classification methods from the viewpoint of the production of a Central Receiver (CR) and a Parabolic Trough (PT) solar plant. The selected classification methods are based on the daily solar radiation features: energy, variability and temporal distribution. So, in a first step, the days of a period of 16 years of measurements recorded in Seville (Spain) are classified by these two methods. In a second step, the daily gross productions of both CSP plants are estimated using System Advisor Model program. Then, the representativeness of the types of days of each classification method is evaluated according to the production of the CR and the PT plant by means of a methodology based on the clear sky yield index or k(p), index. Finally, the ARE and the annual relative RMSE and the MAE for the plants and classification methods analyzed are compared. Then, we can conclude, that the representativeness of the types of days of a classification method has a certain dependence on the plant that depends on the classification method applied.

Concentrated solar power (CSP) and photovoltaic (PV) solar systems can be hybridized, creating synergies: on one hand procuring dispatchability by storing thermal energy, and on the other hand generating electricity at a highly competitive prize. In this paper, we present an approach to the operation strategies and modes for integrated hybrid CSP + PV systems. We focus on parabolic trough (PT) solar plants, especially those operating in the south of Spain. Our study consists in the definition of suitable states for each of the subsystems that constitute a hybrid solar plant. We then propose modes from the combination of suitable states and establish the conditions for the transition between modes depending on the operation strategy. We propose two operation strategies: demand coverage and base load production. The results of this paper can be used in decision making for hybrid solar system simulation programs.

Integrals that are of interest in the analysis, design, and optimization of concentrating solar thermal systems (CST), such as the annual optical efficiency of the light collection and concentration (LCC) subsystem, can be accurately computed or estimated in two distinct ways: on the time domain and on the spatial domain. This article explores these two ways, using a case study that is highly representative of the commercial CST systems being deployed worldwide. In the time domain, the computation of these integrals are explored using 1-min, 10-min, and 1-h solar DNI input data and using The Cyprus Institute (CyI)'s High-Performance Computing (HPC) system and an open-source ray tracer, Tonatiuh++, being actively developed at CyI. In the spatial domain, the computation of these integrals is explored using SunPATH, another open-source software tool being actively developed at CyI, in tandem with Tonatiuh++. The comparison between the time and spatial domain approach clearly indicate that the spatial domain approach using SunPATH is dramatically more computationally efficient than the time domain approach. According to the results obtained, at least for the case study analyzed in this article, to compute the annual energy delivered by the LCC subsystem with a relative error less than 0.1%, it is enough to provide SunPATH with 1-h DNI data as input, request from SunPATH the sun position and weights of just 30 points in the celestial sphere, and run Tonatiuh++ to simulate these 30 points using 15 million rays per run. As the test case is highly representative, it is expected that this approach will yield similar results for most CST systems of interest.

Industrial activity concerned with the profitability and safety of investments can be supported and promoted by research through the creation of new mathematical modeling approaches, and the quantification and mitigation of uncertainties. In recent years there has been increasing interest in the adoption of probabilistic approaches to assess sources of uncertainty in solar energy systems to estimate their feasibility, considering yield estimates, investments, operation and maintenance costs, and solar resource. In this context, the synthetic solar irradiance data set approach emerges as a promising tool to emulate the variability inherent to the solar resource in confident designs and feasibility analyses of these systems. Chapter 5 deals with the requirements of the industry with respect to synthetic solar data, and how such requirements are currently addressed during the main stages of development of solar projects. We recap methods for benchmarking the success of generated synthetic irradiance, reviewing statistical indicators for that purpose. We discuss and compare the use of single annual and multiple synthetic annual data sets of solar irradiance in the first stages of solar projects, and present their uses in a case study application in a Concentrating Solar Power (CSP) plant with a similar configuration to a well-known operational Parabolic Trough (PT) plant located in Spain.

The electroencephalographic signal constitutes the main sign classically used for the identification of states of alertness. However, activities in the high frequency (>100 Hz) range have not been properly studied despite their high potential for sleep scoring in rodents. In the present study, we designed a method for the identification of the sleep–wake states in rats by exclusively using high‐frequency activities of the electroencephalogram. By calculating the ratio between the amplitude of the electroencephalographic signal from 110 to 200 Hz and from 110 to 300 Hz, we obtained an index that had values that were low during wakefulness, intermediate during non‐REM sleep and high during REM sleep. This high‐frequency index (HiFI) allowed the identification of each state without the need to study other signs such as muscle activity or eye movements. To evaluate the performance of the index, we compared it with the conventional scoring of the sleep–wake cycle based upon the study of the electromyogram and delta (0.5–4 Hz), theta (6–9 Hz) and sigma (10–14 Hz) bands of the electroencephalogram. The index had an accuracy of 90.43 ± 1.91% (Cohen's kappa value of 0.82), confirming that the study of the high‐frequency activities of the electroencephalogram was sufficient to reliably identify alertness states in the rat. Compared to other sleep‐scoring methods, the HiFI has several advantages. It only requires one electroencephalography electrode, thus reducing the severity of the surgical preparation of the experimental animal, and its calculation is very simple, so it can be easily implemented online to classify sleep–wake states in real time.

CSP feasibility analysis, bankability assessment and plant design are generally based in one-year meteorological series representative of "typical" o extreme conditions. There is a growing interest in accounting on the inherent variability of the performance of solar plants on their input variables in the plant model. In particular, for generating the probability distributions of annual energy yield, simulation tools require as input a large number of plausible meteorological years (PMYs). In this article we generate 100 synthetic years of DNI in the 1-min resolution for the location of Seville, Spain, and we estimate and evaluate the power produced by two CSP plants with similar configuration as two well-known parabolic trough and central receiver solar plants (Andasol 3 and (Gemasolar) using System Advisor Model (SAM). We estimate that there is an almost linear relation between the Probabilities of Exceedance (PoE) of the DNI and the gross electricity generation of the solar plants but that for a given annual value that corresponds to a PoE of the DNI, there is a range of possible production values depending mainly on the monthly distribution of the solar radiation datasets.

The Variability Index (VI) is widely used to quantify the intra-day solar radiation variability. It compares the length of the global horizontal irradiance (GHI) or direct normal irradiance (DNI) profiles with the length of the corresponding clear sky GHI/DNI profiles. The VI is not a normalized index, it shows dependency on the day of the year, geographic location and time resolution. Thus, the quantification of the intra-day variability of the solar resource between different locations or different seasons could be mistaken. In this work, we propose a novel definition of the VI in order to normalize it (VI). Moreover, we suggest a methodology to assess the dependencies of the intra-day solar resource variability quantifiers with the day of the year, geographic location and time resolution. We evaluate and compare the performance of both indexes in two different locations along two synthetic years and a measured annual dataset in different time resolutions.