Solar Energy Resource Assessment Research Articles

Solar Energy Resource Assessment in Chile: Satellite Estimation and Ground Station Measurement

The progress from the last four years in solar energy resource assessment for Chile is reported, including measurements from a ground station network spanning from two to three years of data, and satellite estimations from the recently developed Chile-SR model including two full years of data. The model introduces different treatments for the meteorological variables and the effective cloud cover computations which allow estimation of the global horizontal irradiation on an hourly basis. The BRL model of diffuse radiation is then applied in order to estimate the diffuse fraction and diffuse irradiation, from which the Direct horizontal irradiation is then computed. Direct normal irradiation is computed by applying proper solar geometry corrections to the direct horizontal irradiation. The satellite estimation model was developed as an adaptation from Brazil-SR model, with an improved formulation for altitude-corrected atmospheric parameters, and a novel formulation for calculating effective cloud covers while at the same time detecting and differentiating it from snow covers and salt lakes. The model is validated by comparison with ground station data. The results indicate that there are high radiation levels throughout the country. In particular, northern Chile is endowed with one of the highest solar resources in the world, although the resource variability is higher than previously thought.

Solar Energy Resource Assessment of the Geba Catchment, Northern Ethiopia

The global shift towards renewable energy is manifested in developing countries such as Ethiopia primarily because of continuous economic growth in the last two decades and secondly due to the vast untapped potential resources. In addition to other factors, the lack of accurate data of the resources has, however, hampered the development of solar energy technologies. The aim of this paper is to investigate the resource estimation by undertaking direct measurements at selected sites in the Northern part of Ethiopia.This paper presents an assessment of the solar energy resource based on the primary data collected between January 2011 and December 2012. The daily and monthly average global solar radiation is analyzed based on the 10minute interval measurement retrieved from the data loggers.From the analysis it is seen that the measured values give a better accuracy and distribution of the global solar radiation than earlier Fig.s that were based on satellite images and model calculations. Furthermore, these results can be used to determine the solar resource potential of Northern Ethiopia for further energy development.

Assessment of solar and wind energy resources in Serbia

Serbia aims to improve the composition of its energy sources and increase the contribution of renewable and sustainable energies to meet its growing electricity production demand. Results of many studies and numerous measurement campaigns suggest that Serbia has a considerable potential for the solar and wind energy utilization for electricity generation. The objective of this article is to present a brief assessment of these solar and wind resources. Meteorological data from a network of meteorological stations covering a period of 30 yr are used to obtain annual energy density distributions from these two climatic sources. These results, summarizing in an abbreviated form comprehensive research efforts culminating in the last decade, are presented in an archival publication for the first time. This assessment indicates that southern and southeastern Serbia are very good regions for the solar energy utilization. Southern Banat, mountain ranges of eastern and southeastern Serbia, and the lower Danube river valley are the most promising regions for the wind power plant constructions. Final objective of this article is to show that the problem of individual intermittency of wind and solar power potentials could be compensated in Serbia by their complementary character.

Assessment of Wind and Solar Energy Resources in Bangladesh

Wind and solar energy are the alternative energy sources that can be used to supplement the conventional energy sources particularly in Bangladesh. In this work, the aim was to assess the current wind and solar energy potential in Bangladesh. The wind data for the five stations obtained from Local Government Engineering Department have been assessed, but only two of them seem to be eligible for energy production. Annual average, monthly average and hourly average wind speeds, and wind power densities were calculated from the wind data. The Weibull distribution parameters (c and k), the dominant wind directions and the frequency distributions were also determined. Experimentally measured solar radiation data are not available over Bangladesh. Measured climatological data such as cloud cover and sunshine duration data of Bangladesh Meteorological Department from 1992 to 2001 were used for the estimation of global solar radiation as they are correlated. Techno-economic feasibility analysis is done for 100 kW grid connected wind and solar photovoltaic systems. Renewable energy-based system will bring more environmental benefits than conventional power in terms of human health, reduction of air pollution, and decrease of noise, etc. However, in the above estimation, these were not considered.

Influence of solar energy resource assessment uncertainty in the levelized electricity cost of concentrated solar power plants in Chile

The deployment of renewable energy power plants is a priority of the Chilean government. A mandatory quota system requires that 5% of the electricity generated in the country must come from renewable energy sources, gradually increasing to 10% by 2024. As of 2010, solar energy has received attention only for small-scale future demonstration projects. Concentrated solar power (CSP) plants are an interesting option for the country, especially when considering the high levels of solar radiation and clearness index that are available in northern Chile. Here we present a thermal and economic analysis of CSP plants of the parabolic trough type, comparing five different configurations including thermal energy storage and fossil fuel backup. The electricity yields are obtained from hourly simulations that consider radiation levels, solar field, and power plant characteristics. An economic model that includes the costs of construction, operation and maintenance allows predicting the levelized electricity cost (LEC) as a function of plant configuration and location. The results indicate that the plants can produce dispatchable electricity at a cost that is competitive and inversely proportional to radiation levels. A sensitivity analysis is conducted in order to determine the influence of solar field area and radiation levels, and the optimal plant configuration and solar field area are obtained as a result.

Spatio-temporal assessment of dust risk maps for solar energy systems using proxy data

This paper presents a new approach for spatio-temporal assessment of dust risk map for solar energy systems in arid area using proxy open source data. The approach considers the recent NASA satellite data from the Multi-angle Imaging Spectro-Radiometer (MISR) which provides significant information about dust emission, transport, concentration and property evolution, through Aerosol Optical Depth (AOD). The analysis was conducted on Oman as a case study. The dust risk maps were developed based on the spatio-temporal evolution of MISR AOD in blue band (446 nm). These maps showed significant variations of AOD over the year. The summer season presents the highest risk of dust contamination because of the favorable regional weather synoptic conditions for the dispersion of mineral dust and creation of haze conditions. The annual average map of AOD was also developed and compared to the dust emission sources (desert sand locations), and the annual average maps of wind direction and air temperature at 100 m and 2 m above the ground, respectively. These maps show a good correlation between dust emission sources, wind and temperature profiles, and high atmospheric dust concentration captured by AOD. Finally, the impact of dust constraint on solar energy resource assessment and systems siting was investigated for Oman. It was found that a considerable reduction (64%) of the highly suitable land is obtained after consideration of dust concentration constraint.

PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation

This paper presents some preliminary results from a research study conducted on solar energy resource assessment in Oman. GIS-based spatial multi-criteria evaluation approach, in terms of the FLOWA module was used to assess the land suitability for large PV farms implementation in Oman. The tool used applies fuzzy quantifiers within ArcGIS environment allowing the integration of a multi-criteria decision analysis. Land suitability analysis for large PV farms implementation was carried out for the case study of Oman. The overlay results obtained from the analysis of the resultant maps showed that 0.5% of the total land area demonstrate a high suitability level. Different PV technologies were considered for implementation. It was found that the CPV technology provides very high technical potential for implementing large solar plants. In fact, if all highly suitable land is completely exploited for CPV implementation, it can produce almost 45.5 times the present total power demand in Oman.

Assessment of wind and solar energy resources in Batna, Algeria

Abstract Due to several climate changes caused by greenhouse gas and to the increasing need for clean energies, scientists drew attention to renewable energy sources, which are the most suitable solution in the future. Sparsely populated and flat open terrains observed in Batna region (North East of Algeria) and its semi-arid climate, make it a promising region for the development of solar and wind energies. In this article, we analyzed ten years of daily wind speed data in a remote area of Batna: Mustafa Ben Boulaid Airport. Wind power availability, as well as annual mean values of wind speed and power, were estimated. Frequency distribution of daily totals of wind speed data were counted and illustrated too. The results have been used to estimate net energy output of different wind turbines. This simulation shows a difference in wind generators production and allows us to choose the best wind turbine adapted to site conditions. Since solar and wind energy resources may be used to compensate each other, we evaluated also the solar potential of the same area.

The state of solar energy resource assessment in Chile

The Chilean government has determined that a renewable energy quota of up to 10% of the electrical energy generated must be met by 2024. This plan has already sparked interest in wind, geothermal, hydro and biomass power plants in order to introduce renewable energy systems to the country. Solar energy is being considered only for demonstration, small-scale CSP plants and for domestic water heating applications. This apparent lack of interest in solar energy is partly due to the absence of a valid solar energy database, adequate for energy system simulation and planning activities. One of the available solar radiation databases is 20–40 years old, with measurements taken by pyranographs and Campbell–Stokes devices. A second database from the Chilean Meteorological Service is composed by pyranometer readings, sparsely distributed along the country and available from 1988, with a number of these stations operating intermittently. The Chilean government through its National Energy Commission (CNE) has contracted the formulation of a simulation model and also the deployment of network of measurement stations in northern Chile. Recent efforts by the authors have resulted in a preliminary assessment by satellite image processing. Here, we compare the existing databases of solar radiation in Chile. Monthly mean solar energy maps are created from ground measurements and satellite estimations and compared. It is found that significant deviation exists between sources, and that all ground-station measurements display unknown uncertainty levels, thus highlighting the need for a proper, country-wide long-term resource assessment initiative. However, the solar energy levels throughout the country can be considered as high, and it is thought that they are adequate for energy planning activities – although not yet for proper power plant design and dimensioning.

Solar energy scenarios in Brazil, Part one: Resource assessment

The “Solar and Wind Energy Resource Assessment” (SWERA) project was an international project financed by GEF/UNEP, which aimed at providing a consistent and accessible database to foster the insertion of renewable energies on the energy matrix of developing countries. This paper presents the solar energy resource assessment generated during the SWERA project by using the radiative transfer model BRASIL-SR fed with satellite and climate data. The solar irradiation estimates were validated by comparing with the ground data acquired in several sites spread out the Brazilian territory. Maps on 10×10 km 2 spatial resolution were generated for global, diffuse and direct normal solar irradiation. Solar irradiation on a plane tilted by an angle equal to the local latitude was also generated at the same spatial resolution. Besides the solar resource maps, the annual and seasonal variability of solar energy resource was evaluated and discussed. By analyzing the Brazilian solar resource and variability maps, the great potential available for solar energy applications in Brazil is apparent, even in the semi-temperate climate in the southern region where the annual mean of solar irradiation is comparable to that estimated for the equatorial Amazonian region.

The influence of cloud cover index on the accuracy of solar irradiance model estimates

Cloud cover index (CCI) obtained from satellite images contains information on cloud amount and their optical thickness. It is the chief climate data for the assessment of solar energy resources in most radiative transfer models, particularly for the model BRASIL-SR that is currently operational at CPTEC. The wide range of climate environments in Brazil turns CCI determination into a challenging activity and great effort has been directed to develop new methods and procedures to improve the accuracy of these estimations from satellite images (Martins 2001; Martins et al. 2003a; Ceballos et al. 2004). This work demonstrates the influence of CCI determination methods on estimates of surface solar irradiances obtained by the model BRASIL-SR comparing deviations among ground data and model results. Three techniques using visible and/or thermal infrared images of GOES-8 were employed to generate the CCI for input into the model BRASIL-SR. The ground-truth data was provided by the solar radiation station located at Caico/PE, in Brazilian Northeast region, which is part of the UNEP/GEF project SWERA (Solar and Wind Energy Resources Assessment). Results have shown that the application of the bi-spectral techniques have reduced mean bias error up to 66% and root mean square error up to 50% when compared to the usual technique for CCI determination based on the straightforward determination of month-by-month extremes for maximum and minimum cloud states.

Parameterization of aerosols from burning biomass in the Brazil-SR radiative transfer model

A new aerosol parameterization was developed and implemented for operational use with the BRASIL-SR model. The goal is to improve the assessment of solar energy resources in Brazil. Optical properties of the aerosols from burning biomass were obtained using software package OPAC and are in good agreement with previous field measurements made in Brazil. Three different mixture ratios of black carbon were used to cover the full range of typical measured values. The atmospheric transport model SMOKE provided the aerosol profile. An evaluating period of 11 days in August/1995 and ground measurements from six sites situated in Amazon region was used to validate the results. The global solar irradiation estimates obtained with new aerosol parameterization, presented smaller mean bias error in all ground sites. The correlation among estimates and measured values for surface global solar irradiation improved about 2.5 times by adopting an aerosol composition with 5% of black carbon.

Selection of input parameters to model direct solar irradiance by using artificial neural networks

A very important factor in the assessment of solar energy resources is the availability of direct irradiance data of high quality. However, this component of solar radiation is seldom measured and thus must be estimated from data of global solar irradiance, which is registered in most radiometric stations. In recent years, artificial neural networks (ANN) have shown to be a powerful tool for mapping complex and non-linear relationships. In this work, the Bayesian framework for ANN, named as automatic relevance determination method (ARD), was employed to obtain the relative relevance of a large set of atmospheric and radiometric variables used for estimating hourly direct solar irradiance. In addition, we analysed the viability of this novel technique applied to select the optimum input parameters to the neural network. For that, a multi-layer feedforward perceptron is trained on these data. The results reflect the relative importance of the inputs selected. Clearness index and relative air mass were found to be the more relevant input variables to the neural network, as it was expected, proving the reliability of the ARD method. Moreover, we show that this novel methodology can be used in unfavourable conditions, in terms of limited amount of available data, performing successful results.

Selection of input parameters to model direct solar irradiance by using artificial neural networks

A very important factor in the assessment of solar energy resources is the availability of direct irradiance data of high quality. However, this component of solar radiation is seldom measured and thus must be estimated from data of global solar irradiance, which is registered in most radiometric stations. In recent years, artificial neural networks (ANN) have shown to be a powerful tool for mapping complex and non-linear relationships. In this work, the Bayesian framework for ANN, named as automatic relevance determination method (ARD), was employed to obtain the relative relevance of a large set of atmospheric and radiometric variables used for estimating hourly direct solar irradiance. In addition, we analysed the viability of this novel technique applied to select the optimum input parameters to the neural network. For that, a multi-layer feedforward perceptron is trained on these data. The results reflect the relative importance of the inputs selected. Clearness index and relative air mass were found to be the more relevant input variables to the neural network, as it was expected, proving the reliability of the ARD method. Moreover, we show that this novel methodology can be used in unfavourable conditions, in terms of limited amount of available data, performing successful results.

Levantamento dos recursos de energia solar no Brasil com o emprego de satélite geoestacionário: o Projeto Swera

O conhecimento da radiação solar incidente na Terra desempenha papel fundamental em muitas atividades humanas como, por exemplo, a agricultura, a arquitetura e o planejamento energético. A radiação solar constitui uma opção limpa e renovável de produção de energia. Para melhor conhecimento da disponibilidade desta fonte de energia e seu aproveitamento, pode-se utilizar modelos computacionais que utilizam técnicas aproximadas na resolução numérica da equação de transferência radiativa para estimar o fluxo de energia solar na superfície. Este trabalho apresenta uma revisão sobre os princípios que estão por trás desses modelos tendo como exemplo aplicado o método do modelo BRASIL-SR. Esse modelo está sendo empregado no mapeamento do potencial energético solar da América Latina através do projeto SWERA (Solar and Wind Energy Resource Assessment), financiado pela Divisão de Ambiente Global (GEF) através do Programa das Nações Unidas para o Ambiente (UNEP).

Solar energy resource assessment — Brazil

Appropriate information on solar resources is very important for a variety of technological areas, such as: agriculture, meteorology, forestry engineering, water resources and particularly for an innovating technology such as solar energy. In the market entry process of an innovating technology such as solar energy, the enlarged and sustained reproduction of this energy strongly depends on the economy and reliability of the demonstrative solar systems installed (within a restricted or wide scale). The economy and reliability of a system are the consequence of a well-prepared project, resulting from an accurate knowledge of the solar resource available. Therefore, knowing the potential of the solar resource accurately is not only a need, it is also an imperative for a larger diffusion and use of the solar energy. The existing sources of information on radiation in Brazil are quite varied, both at the institutional level and in different types of publications. At the institutional level these sources are: the National Institute of Meteorology, secretary of agriculture, research centers, universities, and electric power generating and distributing companies, among others. The publications with this information are project reports, internal reports of institutions or several magazines. Thus, the quality of the data varies considerably, the information presents spatial and temporal discontinuity and the instruments as well as the measurement units are not standardized. The general objective of this paper is to recover, qualify, standardize and make available the best information from the current existing solar resource in Brazil, either in the form of isoline charts of solar radiation, insolation, numeric tables or analytic summaries of a great part of the publications on the theme over the last forty years.

Empirical modeling of hourly direct irradiance by means of hourly global irradiance

A very important factor in the assessment of solar energy resources is the availability of direct irradiance data of high quality. Nevertheless, this quantity is seldom measured and thus must be estimated from measures of global solar irradiance, a quantity that is registered in most radiometric stations. In this work we analyze the results provided by different models in the estimation of hourly direct irradiance values. We have selected several models proposed by Orgill and Hollands, Erbs et al., Reindl et al., Skarveit and Olseth, Maxwell, and Louche et al. With the exception of the model from Louche et al. that estimates direct irradiance values from direct transmittance values, all of the models estimate direct irradiance from the diffuse fraction. The data set used in this study comprises 25 000 hourly values of global and diffuse irradiance. These values were registered in six Spanish locations with different climatic conditions. The results provided by the model depend on the clearness index, k t, and the solar elevation. The best results are obtained for cloudless skies and higher solar elevation. In those conditions we can estimate the direct irradiance with a root square mean error close to 14% of the average measured value. We have estimated the direct irradiance under cloudless sky conditions using a parametric model proposed by Iqbal. In order to analyze the effect of turbidity on the estimation of direct irradiance we have compared the results obtained by the parametric model when using hourly values of the Angstrom turbidity parameter β with those obtained when using monthly means of hourly values of β.

Assessment of solar and wind energy resources in Ethiopia. II. Wind energy

Using wind data from 21 meteorological stations with hourly or 3-hourly readings and 60 stations with monthly means, together with data from previous studies of neighbouring countries, a series of analyses were undertaken to illustrate the general availability of wind energy across Ethiopia. In order to calculate the wind energy density, firstly these 21 stations, along with 12 stations from neighbouring countries with hourly readings, were used to calculate the Weibull parameters, c and k. The Weibull distribution is shown to be a good approximation for the observed values in a majority of cases. Isopleths of the k values were then plotted, and from this the remaining 60 stations with monthly readings were then assigned k values. The wind energy density for each station was then calculated. Although the quantity of wind data is somewhat lacking, the results show that there is a potential for wind energy utilisation in some regions of Ethiopia.

Assessment of solar and wind energy resources in Ethiopia. I. Solar energy

This paper describes how data from a variety of sources are merged to present new countrywide maps of the solar energy distribution over Ethiopia. The spatial coverage of stations with radiation data was found to be unsatisfactory for the purpose of a countrywide solar energy assessment exercise. Therefore, radiation had to be predicted from sunshine hours by employing empirical models. Using data from seven stations in Ethiopia, linear and quadratic correlation relationships between monthly mean daily solar radiation and sunshine hours per day have been developed. These regional models show a distinct improvement over previously employed countrywide models. To produce a national solar-energy distribution profile, a spatial extension of the radiation/sunshine relationships had to be carried out. To do this, the intercepts ( a) and slopes ( b) of each of the seven linear regression equations and another six from previous studies, completed in neighbouring Sudan, Kenya and Yemen, were used to interpolate the corresponding values to areas between them. Subsequent to these procedures, 142 stations providing only sunshine data were assigned their “appropriate” a and b values to estimate the amount of solar radiation received, which was then used to produce annual and monthly solar radiation distribution maps for Ethiopia. The results show that in all regions solar energy is an abundant resource.