An insufficient amount of solar resource collected and the variability of this resource can compromise the viability of solar plant projects. For this reason, feasibility studies are usually accompanied by seasonal radiation data, which provides evidence of changes throughout the year. However, there is not a single index to quantify at the same time both elements - the amount available and the variability of the resource - which would provide a measure of the viability in a certain place to set up a solar plant. In this work, a new viability index based on the Gini coefficient (VIG) is proposed and its value is estimated for a wide region of the planet. The VIG calculates the binomial return-risk represented by the average-variance relationship. It clearly improves the results for high latitudes provided by the Sharpe index, which describes the ratio between the difference of the average return and a risk-free return and the risk in general. Finally, the article considers the storage option, drawing the value of the risk improvement index (RI) from the temporal series of the cumulated direct-normal irradiance (DNI) and an ample spectrum of constant demands. RI shows the risk improvement associated to storage of solar energy.

During the last years solar energy has been increasing the percentage of the total energy production around the world and it is expected it persists growing notably [1].In insular grids, such as Canary Islands, the knowledge of solar radiation behaviour is one of the most important variables in order to ensure the stability for power systems.In this paper we study the suitability of Gridded Satellite data for modelling solar radiation for both PV and CSP purposes.The analysis and comparison is performed using hourly Global and Direct Solar radiation from the satellite model CM SAF database and four ground measurement stations in Gran Canaria.This study could give us a better knowledge of solar radiation behavior in a wide spatial and temporal coverage.Moreover, an accurate satellite radiation data could improve solar radiation forecasting for power systems manage systems [2].

In this chapter, the Jevons paradox is studied in the context of the debate on the limits to Growth. This “Jevons paradox” is part of a more general criticism of William Stanley Jevons to classical economics. For Jevons, when the cost of production declines due to resource efficiency, the marginal utility of commodities that use the given resource declines, increasing directly the consumption of those commodities and indirectly the consumption of other commodities with which they are exchanged. Then, scientific progress and resource efficiency is not a good path to the lesser use of resources. Actually, as coal is a non-renewable energy resource, it may be depleted. Jevons’ line of thought led to new areas in economics that imply that economics cannot be fully split from other sciences. The chapter assesses the current importance of the Jevons paradox in the macroeconomic and the microeconomic level, looking at the relationship between economic growth and energy efficiency. Finally, the chapter comments on the energy policies proposed to avoid the rebound effect, with some concluding remarks on the evolution of the concept.

This work addresses the development of a PAR model in the entire territory of mainland Spain. Thus, a specific model is developed for each location of the study field. The new PAR model consists of a combination of the estimates of two previous models that had unequal performances in different climates. In fact, one of them showed better results with Mediterranean climate, whereas the other obtained better results under oceanic climate. Interestingly, the new PAR model showed similar performance when validated at seven stations in mainland Spain with Mediterranean or oceanic climate. Furthermore, all validation slopes ranged from 0.99 to 1.00; the intercepts were less than 3.70 μmol m−2 s−1; the R2 were greater than 0.988, while MBE was closer to zero percent than −0.39%; and RMSE were less than 6.21%. The estimates of the PAR model introduced in this work were then used to develop PAR maps over mainland Spain that represent daily PAR averages of each month and a full year at all locations in the study field.

Photosynthetically active radiation (PAR) is a useful variable to estimate the growth of biomass or microalgae. However, it is not always feasible to access PAR measurements; in this work, two sets of nine hourly PAR models were developed. These models were estimated for mainland Spain from satellite data, using multilinear regressions and artificial neural networks. The variables utilized were combinations of global horizontal irradiance, clearness index, solar zenith angle cosine, relative humidity, and air temperature. The study territory was divided into regions with similar features regarding PAR through clustering of the PAR clearness index (k(P)(AR)). This methodology allowed PAR modeling for the two main climatic regions in mainland Spain (Oceanic and Mediterranean). MODIS 3 h data were employed to train the models, and PAR data registered in seven stations across Spain were used for validation. Usual validation indices assess the extent to which the models reproduce the observed data. However, none of those indices considers the exceedance probabilities, which allow the assessment of the viability of projects based on the data to be modeled. In this work, a new validation index based on these probabilities is presented. Hence, its use, along with the other indices, provides a double and thus more complete validation.

The European Union Green Deal aims at curbing greenhouse gas emissions and introducing clean energy production. But to achieve energy efficiency, the opportunity cost of different energies must be assessed. In this article, two different energy self-sufficient systems for wastewater treatment are compared. On the one hand, high-rate algal ponds system (HRAP) is considered; on the other hand, a conventional activated sludge system (AS) which uses photovoltaic power (PV) is studied. The paper offers a viability analysis of both systems based on the capacity to satisfy their energetic consumption. This viability analysis, along with the opportunity cost study, will be used in the article to compare these two projects devoted to the treatment of wastewater. In order to assess viability, the probability of not achieving the energy consumption threshold at least one day is studied. The results point that the AS+PV system self-sufficiency is achieved with much lesser land requirements than the HRAP system (for the former, less than 6500 m(2), for the latter 40,000 m(2)). However, the important AS capital cost makes still the HRAP system more economic, although storage provides a great advantage for using the AS+PV in locations where a lot of irradiance is available.

In this work Photosynthetically Active Radiation (PAR) in oceanic and mediterranean climates is modeled. Twenty-two different models have been developed and tested: eleven Multilinear Regression (MR) models and eleven Artificial Neuron Network (ANN) models, using combinations of variables such as Global Horizontal Irradiance (GHI), Global Extraterrestrial Irradiance (G(0)), Temperature (T) and Relative Humidity (RH). Data provided by Satellite Application Facility on Climate Monitoring (CM SAF) are used to develop and train the models, while the models have been validated using field data from four stations located in Spain, covering the different study climates. According to the results, zones with different climate conditions need different models, both for the case of MR and ANN. The results show the need of including the GHI in all models in order to obtain accurate estimates; in fact, the presence of more variables only improves slightly the results in mediterranean climate, while in oceanic climate no improvement is observed. On the other hand, comparing MR and ANN models, ANN models did not show better results than those of MR models in no one of the cases studied. Regarding the climate, both types of models are clearly better for the mediterranean case than for the oceanic one. In order to improve the performance of the model for oceanic climate a correction based on the site adaptation technique was carried out. The good results obtained by this technique fully justify its use. The best proposed models provide better performance than other models which are restricted to certain locations. Besides, the clustering technique based on the PAR variable, used in this work, allows obtaining useful models for a whole region. Finally, another advantage of this methodology is that there is no need of ground measurements for its development, except for the site adaptation technique. (C) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved.

The main objective is the development of a network of measurement, modeling, database and web services of photosynthetically active radiation (PAR) over mainland Spain.

Abstract The first aim of this work was to obtain temporal variability patterns for satellite‐derived solar radiation estimations in Zambia. A principal component analysis, in Zambia and the surrounding zones, was performed and from this analysis the physical phenomena associated with these patterns were established. According to the results, two temporal variability patterns stand out: the first is associated with the regional global climate characteristics, including both the deterministic and non‐deterministic components of solar radiation, and the other is strictly associated with the influence of the intertropical convergence zone (ITCZ) responsible for the behaviour of solar radiation during October–March. The second aim of the work was to analyse the spatial variability of the irradiance in the study area. For this aim, a clustering analysis based on the interquartile range of the data was performed. The analysis leads to a spatial distribution of the radiation in agreement with the influence of the ITCZ on the territory. Indeed, those stations less affected by the ITCZ, in the south and east of the territory, show a clear diminution of the radiation around June. However, the stations of the northwest zone, the most affected by the belt of low pressure during November–April, do not present this diminution.

A model based on the known high correlation between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI) was implemented to estimate PAR from GHI measurements in this present study. The model has been developed using satellite-derived GHI and PAR estimations. Both variables can be estimated using Kato bands, provided by Satellite Application Facility on Climate Monitoring (CM-SAF), and its ratio may be used as the variable of interest in order to obtain the model. The study area, which was located in mainland Spain, has been split by cluster analysis into regions with similar behavior, according to this ratio. In each of these regions, a regression model estimating PAR from GHI has been developed. According to the analysis, two regions are distinguished in the study area. These regions belong to the two climates dominating the territory: an Oceanic climate on the northern edge; and a Mediterranean climate with hot summer in the rest of the study area. The models obtained for each region have been checked against the ground measurements, providing correlograms with determination coefficients higher than 0.99.

Electrical energy production using renewable energies is one of the most important challenges in recent years. Among renewable energies, it is worth highlighting photovoltaic and thermoelectric systems due to their adaptation to the Canary Islands. One of the most important issues to ensure the stability for solar power systems, mostly in insular grids as Canary Islands, is the precise knowledge of solar radiation. In this paper, we focus in Gridded Satellite data suitability for modelling Global Horizontal Irradiation (GHI) in islands with complicated orography, as Canary Islands. Solar radiation data retrieved from CM SAF and McClear model were analysed and compared with 22 ground measurement stations in Canary Islands. Moreover, this analysis presents the results of including a site-adaptation methodology for improving satellite suitability. We used different procedures to perform this site adaptation depending on the solar radiation conditions (clear sky or cloudy sky hours), the location of the measurement station (we establish two clusters according to the climate conditions) and the season. This study could provide information about satellite models suitability in islands and a better knowledge of solar radiation behavior. Furthermore, accurate satellite radiation data for wide spatial and temporal coverage could improve solar radiation modelling and forecasting.

This chapter reviews the state of the art of forecasting and nowcasting of direct normal irradiance (DNI) for concentrating solar thermal (CST) systems. After a review of the main methodologies involved in solar radiation forecasting, specific considerations for CST plants have been taken into account. Before highlighting the main challenges in DNI forecasting, the baseline of solar radiation is presented showing a review of benchmarking exercises. Most of this comparison exercises are based on global horizontal irradiance. Some review articles as well as selected works dealing specifically with DNI and solar thermal power plants have also been discussed. Typical forecasting classifications are based on the time period forecasted or the treatment technique. Numerical weather prediction models (NWPMs) are the most suitable models for predicting solar radiation from 4 h up to several days. Statistical forecasting is usually related to the use of local measurements and learning processes in order to derive future behavior. Depending on the time-frequency, this behavior can provide data for years, months, days, hours, minutes, or seconds; then statistical models can cover all time resolutions and forecasting horizon. Nowcasting is a common denomination for the forecasting period up to 6 h. During this period, in addition to NWPM and statistical models, satellite- and sky cameras–derived forecasting are involved. This chapter focuses on forecasting from the point of view of a CST power plant, but at the end of the chapter, some considerations related to single vs. aggregated or regional forecast are also presented. Main challenges are concentrated in the nowcasting period, that is, up to 6 h, as it needs harmonization of signals to provide reliable forecasts of high space–temporal resolution at the plant level: this means, to predict maps with the resolution of several meters and some seconds. Improvements in aerosol knowledge and circumsolar radiation forecasting are also needed for the improvement of all methodologies.

The monthly mean variation of the solar global reaching the Earth's surface has been characterized at a global level by a regression model. This model considers the monthly variation itself (to different horizons and even the maximum annual variation) as the study variable, and it is applied without using data corresponding to measured meteorological variable. Two explicative variables have been used, the variation of the extraterrestrial irradiation and the variation of the clear sky global horizontal irradiation. The work has been carried out from datasets including average global daily solar irradiation for each month of the year measured on the ground. The model quality has been proven to be very dependent of the temporal variation considered, in such a way that higher variations, that is to say, higher distances between months, lead to an improvement in the model outcomes.

A simple method for correcting satellite-derived direct normal irradiance, with important deviations to the experimental data, is presented in this work and illustrated for the particular case of Rajasthan (India). Northwest India is expected to have a high level of solar radiation and it is an interesting area for solar concentrating power systems. However uncertainty in direct normal irradiance estimations from satellite may affect negatively to the bankability of solar plants. Direct normal irradiance have been estimated for a site in Rajasthan from satellite information for the period 2003 to 2011, and ground measurements during 2011 have been used to analyze the uncertainties and to develop a simple correction method. The original satellite estimations showed important deviations from the experimental values and high bias. A systematic underestimation of direct irradiance has been observed during the dryer seasons that could be attributed to an overestimation of the aerosol optical depth input to the model. These observations have allowed the design of a correction methodology. Unbiased new estimations of direct normal irradiance have been generated with this methodology with important reduction in the deviations and with an agreement in the distribution functions compared to the distribution function of the ground data.

This interim solar modelling report provides an overview of the results achieved by modelling the solar radiation based on satellite data and numerical weather prediction models (NWPM) in phase one of the solar resources mapping project for Tanzania. The project comprises three phases. The first phase comprises project inception, preliminary modelling, and implementation planning. Within this phase one, an un-validated solar atlas based on the synergistic combination of satellite and NWPM derived solar data for Tanzania has been carried out. The interim output of the solar atlas is presented in this report. Within phase two, ground-based data collection will be undertaken through a measurement campaign at sites selected from areas defined according to the results of phase one. Finally, in phase three, a resource atlas with reduced direct normal irradiance (DNI) and global horizontal irradiance (GHI) and diffuse horizontal irradiance (DHI) uncertainty with respect to in phase one will be generated from post-processing satellite and NWPM solar radiation outputs with the validated ground-based solar data collected during the measurement campaign of phase two. Preliminary analysis of solar resource and its variability in Tanzania is the focus of this report. Section one gives background. Section two gives introduction. Section three contains a review of previous solar resource assessment and measurements in Tanzania. Section four presents the methodology for the solar resource assessment; using analysis of the satellite and NWPM derived solar data coherence and combination. In section five solar maps are presented and briefly discussed. Finally, section six gives conclusions and outlines the current achievements and the future needs in the solar resource mapping project for Tanzania.

A new stochastic model to describe atmospheric attenuation from yearly global solar irradiation has been developed and implemented. The proposed model takes into account the consideration that the whole of all attenuating elements can be thought of as a population where the higher the number of individuals the lesser the clearness index. Thus, the inverse of the clearness index is considered as the variable of a stochastic process. From the proposed master equation as starting point, the new model is characterized by transition rates (assessed from a growing parameter - G - and a decreasing parameter - D) which depend mainly on the climatological characteristics at each location. In this sense, different regions with an attenuation level calculated from the yearly global irradiation have been established using the Koppen-Geiger climate classification as a first approach.The model parameters G and D have been determined for different regions using the inverse of the clearness index as variable. The probability density function obtained after the application of the stochastic model for each climate zone shows how the index mode increases from the zones with lower levels of attenuation to those with higher levels of attenuation. This result confirms the proposed null hypothesis related to the use of the inverse of the clearness index as an attenuation population indicator.The fit between the empirical data and the data provided for the model is good enough according to a Kolmogorov-Smirno test with a significance level of 0.05. Nevertheless, it is necessary to slightly modify the climate zones of Koppen-Geiger initial classification for a better explanation of the atmospheric attenuation. This climate zones modification can be considered as an additional result (C) 2014 Elsevier B.V. All rights reserved.

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This paper deals the study of variability and intermittency of solar irradiation using an analogy with the turbulence and thus making use of some methodologies used in the study of intermittency of the turbulence. An analysis of the shape of the PDFs corresponding to the increments in the clearness and transmittance indexes, for direct and global radiations, is presented. In addition a study of the relations between the scaling exponents of the structure functions of the clearness and transmittance indexes and the orders of these structure functions has been carried out. According to the study, the range of relative variability is due to changes in the atmospheric components that play a role in the attenuation of solar irradiation. This range of variability is higher in the case of the global irradiation than in the case of the direct. Moreover, the multifractality is showed more intense in sites where, due to local effects, sharper variations in the radiation can be expected, as the case of deserts.

A previous publication exposed a comparative analysis of the results derived from two models, i.e. DirInt and DirIndex, that estimate direct normal irradiance from global horizontal irradiance data. 9975 experimental data were used, measured from 2007 to 21010 in a weather station located at the Public University of Navarre in Pamplona, Spain (latitude: 42.83 N, longitude: -1.6 E, altitude: 435 m). It was concluded that results from the two models were similar, although due to an intermittent operation of the measuring equipment in the years under study, caused by the multiple stops of the tracking system, an ununiformed stational data distribution was obtained, which could lead to biased results. For this reason, it was considered much convenient to extend the analysis to the years 2011 and 2012, when a continuous operation of the measuring equipment took place and, consequently, high quality experimental data were registered. In this paper the model DirInt is applied, as well as the DirIndex combined with three clear sky transmittance models, i.e. ESRA, SOLIS and REST2. The results of the applied models were compared to direct normal irradiance ground data, thus also allowing analysis of the sensitivity of DirIndex to the clear sky model used for its generation. First and second order statistics are employed for the sensitivity analysis. The results allow progress in implementing appropriate combinations of models (classical, transmittance models or others) to accurately estimate the direct irradiance.

espanolEn un trabajo previo se realizo un analisis comparativo de los resultados ofrecidos por dos modelos de estimacion de irradiancia directa a partir de datos de irradiancia global medidos sobre plano horizontal: DirInt y DirIndex. En dicho trabajo, se partio de 9975 datos experimentales correspondientes a los anos 2007 a 2010 medidos en la estacion meteorologica de la Universidad Publica de Navarra, en Pamplona (latitud: 42.83 N, longitud: -1.6 E, altitud: 435 m). Se concluyo que los resultados obtenidos con ambos modelos eran similares, si bien, debido al funcionamiento interrumpido de los equipos de medida en los anos estudiados, ocasionado por multiples paradas del sistema de seguimiento solar, se tenia una distribucion de datos estacional poco uniforme que podia llevar a resultados polarizados. Por ello, se considero conveniente ampliar el analisis a los anos 2011 y 2012, en los que se consiguio un funcionamiento practicamente continuo de los equipos de medida que permitio disponer de datos experimentales de gran calidad en la estacion meteorologica indicada. Asi, en el presente trabajo se aplica el modelo DirInt y el DirIndex combinado con tres modelos de transmitancia para cielo despejado, ESRA, SOLIS y REST2, lo que permite cuantificar la sensibilidad de DirIndex al modelo de cielo claro que se usa para su generacion, mediante la comparacion de los resultados de los modelos aplicados con datos terrestres. Para el analisis de sensibilidad se emplean estadisticos de primer y segundo orden. Los resultados obtenidos permiten avanzar en la aplicacion de combinaciones adecuadas de modelos (clasicos, modelos de transmitancia u otros) con el fin de estimar de forma precisa la irradiancia directa. EnglishA previous publication exposed a comparative analysis of the results derived from two models, i.e. DirInt and DirIndex , that estimate direct normal irradiance from global horizontal irradiance data. 9975 experimental data were used, measured from 2007 to 21010 in a weather station located at the Public University of Navarre in Pamplona, Spain (latitude: 42.83 N, longitude: -1.6 E, altitude: 435 m). It was concluded that results from the two models were similar, although due to an intermittent operation of the measuring equipment in the years under study, caused by the multiple stops of the tracking system, an ununiformed stational data distribution was obtained, which could lead to biased results. For this reason, it was considered much convenient to extend the analysis to the years 2011 and 2012, when a continuous operation of the measuring equipment took place and, consequently, high quality experimental data were registered. In this paper the model DirInt is applied, as well as the DirIndex combined with three clear sky transmittance models, i.e. ESRA, SOLIS and REST2. The results of the applied models were compared to direct normal irradiance ground data, thus also allowing analysis of the sensitivity of DirIndex to the clear sky model used for its generation. First and second order statistics are employed for the sensitivity analysis. The results allow progress in implementing appropriate combinations of models (classical, transmittance models or others) to accurately estimate the direct irradiance.