Deployment Of Solar Energy Technologies Research Articles

Assessing the environmental health and safety risks of solar energy production

Solar energy production has gained significant traction as a promising alternative to fossil fuels, yet its widespread adoption raises questions regarding its environmental health and safety (EHS) risks. This review presents an overview of the current state of research in assessing these risks associated with solar energy production. Firstly, it examines the environmental impacts of solar energy, including the life cycle assessment of photovoltaic (PV) panels and solar thermal systems. Key considerations include the energy and resources required for manufacturing, transportation, installation, operation, and end-of-life disposal or recycling of solar panels. Furthermore, the potential for land use change, habitat disruption, and biodiversity loss due to large-scale solar installations is addressed. Secondly, the review discusses the safety risks associated with solar energy production, focusing on occupational health and safety hazards for workers involved in manufacturing, installation, maintenance, and decommissioning of solar energy systems. It examines exposure to hazardous materials such as lead, cadmium, and silicon during the manufacturing process, as well as the risks of falls, electrical hazards, and other workplace accidents during installation and maintenance activities. Moreover, the review highlights emerging technologies and best practices aimed at mitigating EHS risks in solar energy production. These include advancements in PV panel recycling technologies, improvements in manufacturing processes to reduce environmental impacts, and enhanced safety protocols and training for workers in the solar energy industry. While solar energy offers numerous environmental and economic benefits as a renewable energy source, it is essential to comprehensively assess and manage its EHS risks throughout the life cycle of solar energy systems. This review underscores the importance of ongoing research, innovation, and regulatory oversight to ensure the sustainable and safe deployment of solar energy technologies in the transition towards a low-carbon future.

Recent innovations in solar energy education and research towards sustainable energy development

The essential requirements of our everyday lives are fresh air, pure water, nourishing food, and clean energy in a most sustainable manner. The present review article concisely discusses recent innovations in solar energy education, research, and development toward providing clean and affordable energy and clean water to some extent. This article primarily addresses the Sustainable Development Goal 7 of the United Nations (SDG 7: Affordable and Clean Energy). Over the past few decades, many research activities have been carried out on solar energy conversion and utilization. The deployment of solar energy technologies has been witnessed to combat global warming and the betterment of the planet. Drivers and barriers to implementing solar energy systems from school to master's level through real-time deployments are discussed for further development and innovations. Mainly, expedited solar energy education and research are essential to improve solar energy utilization. The advancements in solar energy education and research towards sustainable energy development and circular economy are highlighted along with further directions required.

Performance Analysis of Clear Sky Global Horizontal Irradiance Models: Simple Models Adapted for Local Conditions

Evaluation of the maximum solar energy potential of a given area for possible deployment of solar energy technologies requires assessment of clear sky solar irradiance for the region under consideration. Such localized assessment is critical for optimal sizing of the technology to be deployed in order to realize the anticipated output. As the measurements are not always available where they are needed, models may be used to estimate them. In this study, three different models were adapted for the geographical location of the area under study and used to estimate clear sky global horizontal irradiance (GHI) at three locations in the subtropical desert climate of Namibia. The three models, selected on the basis of input requirements, were used to compute clear sky GHI at Kokerboom, Arandis, and Auas. The models were validated and evaluated for performance using irradiance data measured at each of the sites for a period of three years by computing statistical parameters such as mean bias error (MBE), root mean square error (RMSE), and the coefficient of determination (R2), normalized MBE, and normalized RMSE. Comparative results between modelled and measured data showed that the models fit well the measured data, with normalized root mean square error values in the range 4–8%, while the R2 value was above 98% for the three models. The adapted models can thus be used to compute clear sky GHI at these study areas as well as in other regions with similar climatic conditions.

A Robust Methodology for Assessing the Effectiveness of Site Adaptation Techniques for Calibration of Solar Radiation Data

Abstract The abundant spatial and temporal availability of solar energy has been fueling many researches and have been the reason for the proliferation of solar energy applications in the past decades. Many of these applications involve heavy investments and thus require highly accurate and reliable long-term average solar data for efficient deployment of solar energy technologies. Since ground stations are costly, site-specific, scarce and cannot provide long-term solar data, satellite-derived data is the next best alternative. However, satellite models are often unable to capture the complex local climatological variations of a given site. As such, short-term high precision solar ground measurements are used to train the satellite model so as to improve the accuracy of long-term solar estimates. There exist several site adaptation techniques to perform this task. However, to the knowledge of the researchers, no comparative study has been conducted to establish which site adaptation technique is the most effective. In this study, a robust methodology has been proposed to compare the effectiveness of four site adaptation techniques for monthly and yearly data sets using novel key performance indicators. Ground measurements from 12 stations in the tropical islands of Mauritius, Rodrigues, and Agalega were used to adapt satellite data obtained from HelioClim-3 database using different techniques. Three new nonlinear site adaptation techniques have been proposed: adjustment technique (Technique 2), compensation technique (Technique 3), and relationship technique (Technique 4). The first part of the study showed that 67–100% of the data sets were best approximated with sixth-order polynomials for the three nonlinear techniques. The second part revealed that Technique 1 (linear method) and Technique 2 were most appropriate for maximum and average data sets, respectively. The results were such that Technique 2 and Technique 1 provided best approximations for77.9–83.3% and 40.7–58.3% of average and maximum data sets, respectively. In the third part of the study, only Technique 2 provided remarkable improvements for all statistical metrics with respect to the original monthly data sets (113–118 data sets). The analysis reported 57.6–89.9%, 49.8–68.0%, 67.4–87.3%, 53.8–63.1%, 45.0–64.0%, 7.7–9.6% and 2.7–4.7% mean improvements for mean bias error (MBE), mean absolute bias error (MABE), mean percentage error (MPE), mean absolute percentage error (MAPE), root-mean-square error (RMSE), Nash–Sutcliffe (NSE), and coefficient of determination (COD), respectively, for Technique 2. Similar results were observed for yearly average data sets while the appreciation was shared among all four techniques for yearly maximum data sets, with Technique 1 having a slight advantage.

Exploratory evaluation of solar radiation and ambient temperature in twenty locations distributed in United Kingdom

Solar radiation and ambient temperature is a foundation resource programs of large-scale deployment of solar energy technologies. This paper summarizes the analysis of a weather station network in United Kingdom. Whistle 3 years (January 2015 – December 2017) of data from twenty weather stations distributed across the country. The data comprises of Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (DHI), Direct Normal Irradiance (DNI), ambient temperature, wind speed, and the humidity. Network design, implementation, and data quality assurance are described, in order to document the network extent and quality. From all observed datasets, it was found that Plymouth (located in southwest England) has the dominant GHI, and ambient temperature among all other 19 locations. The least GHI is observed for Aberdeen (located in northeast Scotland) estimated at 77.3 kWh/m2. However, the least average ambient temperature is equal to 9.1 °C, this data was detected from the weather station located in the capital of Scotland (Edinburgh). Although continued measurements are needed to understand the interannual resource variability, the current study provides significant guidance for preliminary technology selection, power plant modeling, and resource forecasting.

Preliminary assessment of the solar resource in the United Kingdom

Abstract Solar radiation resources data are the foundation of knowledge for programs of large-scale deployment of solar energy technologies. This article summarizes the analysis of a new weather stations network in the United Kingdom. The analysis used three years (January 2015–December 2017) of data from 27 weather stations distributed across the country. The data comprises global horizontal irradiance (GHI), diffuse horizontal irradiance, direct normal irradiance and the ambient temperature. Network design, implementation and data quality assurance are described to document the network extent and quality. From all observed datasets, we found that Plymouth (located in southwest England) has the dominant GHI and ambient temperature among all other 26 locations. The least GHI is observed for Aberdeen (located in northeast Scotland) estimated at 77.3 kWh/m2. The least average ambient temperature is equal to 9.1°C; the data were detected by the weather station located in the capital of Scotland (Edinburgh). Although continued measurements are needed to understand the interannual resource variability, the current study should have significant applications for preliminary technology selection, power plant modeling and resource forecasting.

SOLAR DEVELOPMENT IN UZBEKISTAN. STEP 1: SOLAR DATA COMPILATION

Solar radiation resource data serve as fundamental information for programs of large-scale deployment of solar energy technologies. While solar resources in the Republic of are estimated to be significant based on limited information, comprehensive understanding requires considerably more data and analysis in order to optimize the process of planning and siting solar energy power plants. This paper highlights the analysis of the four-year of solar resource measurements from new ground meteorological stations in which were installed within the framework of the project of the Asian Bank TA 8008 Development of solar energy in Uzbekistan in 2013.The current study should have significant applications for preliminary technology selection, power plant modeling, and resource forecasting. The analysis uses4-year (January 2013–December 2016) data from 6 stations located in the south-eastern part of the republic based on ten-minute measurements of Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (DHI), Direct Normal Irradiance (DNI), and related meteorological parameters.

Assessment of Solar Energy Source Distribution and Potential in Zambia

Zambia is vastly endowed with a wide range of energy resources. Yet, to date, Zambia has not fully exploited its potential in solar energy utilisation for electricity generation due to various reasons such as lack of understanding of the distribution of solar energy potential in the country and limitation of access to solar energy resource information. This paper assess the solar energy distribution and potential in Zambia. Nine provinces with different geographical and climatic regions that makes up Zambia were assesed. The distribution of solar radiation within the country were assessed using spatial analysis in ArcGIS Software. The 22year period solar datasets were considered for assessment. These datasets were obtained from NASA Atmospheric Science Data Center using Surface Meteorology and Solar Energy. The analyzed results indicate that Zambia has approximately 20,442TWh/year technical solar energy potential and receives 2109.97kWh/m2 of solar energy per year with 4403.12hours of sunshine. The country has 186,121km2 available and suitable land area for RETs implementations. This study is important as it present an overview of the technical solar energy potential for Zambia which is vital for decision making, energy mix and sustainable deployment of solar energy technologies in the country

Evaluation of relative impact of aerosols on photovoltaic cells through combined Shannon's entropy and Data Envelopment Analysis (DEA)

One of the biggest challenge before the world today is to find a trade-off between high energy demand and mitigation of greenhouse gas emissions. Researchers and energy policy makers around the world are now resorting to renewable energy (RE), as a solution to this crisis with special focus on solar energy, as it is the most abundantly available RE source. However, the requirement of high upfront capital investment is an inhibiting factor behind seamless deployment of solar energy technologies. Hence it is of paramount importance to increase the techno-commercial viability of the projects by leveraging on the environmental factors specific to project sites. In the present work, the impact of different kind of aerosols, which characterize different distinct geographical regions, on the performance of Photovoltaic (PV) cells have been investigated experimentally under different irradiation levels. The complex set of data generated by the experiment has been analysed and indexed by application of combined Shannon's entropy and Data Envelopment Analysis (DEA) to quantify the relative performance of the system under different environmental conditions, different TSPs at their different concentration levels. Through this work a comprehensive approach is proposed for the decision makers to enhance the techno-commercial viability of the PV projects.

Assessing the potential of random forest method for estimating solar radiation using air pollution index

Simulations of solar radiation have become increasingly common in recent years because of the rapid global development and deployment of solar energy technologies. The effect of air pollution on solar radiation is well known. However, few studies have attempting to evaluate the potential of the air pollution index in estimating solar radiation. In this study, meteorological data, solar radiation, and air pollution index data from three sites having different air pollution index conditions are used to develop random forest models. We propose different random forest models with and without considering air pollution index data, and then compare their respective performance with that of empirical methodologies. In addition, a variable importance approach based on random forest is applied in order to assess input variables. The results show that the performance of random forest models with air pollution index data is better than that of the empirical methodologies, generating 9.1–17.0% lower values of root-mean-square error in a fitted period and 2.0–17.4% lower values of root-mean-square error in a predicted period. Both the comparative results of different random forest models and variance importance indicate that applying air pollution index data is improves estimation of solar radiation. Also, although the air pollution index values varied largely from season to season, the random forest models appear more robust performances in different seasons than different models. The findings can act as a guide in selecting used variables to estimate daily solar radiation and improve the accuracy of solar radiation estimation.

Assessment of solar radiation resources in Saudi Arabia

Solar radiation resource data are the foundation of information for programs of large-scale deployment of solar energy technologies. While the solar resource in Saudi Arabia and the Arabian Peninsula was believed to be significant based on limited past data, understanding the spatial and temporal variability requires significantly more data and analysis in order to optimize planning and siting solar energy power plants. This paper summarizes the analysis of the first year of broadband solar resource measurements from a new monitoring network in Saudi Arabia developed by the King Abdullah City for Atomic and Renewable Energy (K.A.CARE). The analysis used twelve months (October 2013–September 2014) of data from 30 stations distributed across the country based on one-minute measurements of Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (DHI), Direct Normal Irradiance (DNI), and related meteorological parameters. Network design, implementation, and data quality assurance are described to document the network extent and quality. For the 30 stations, the annual average daily GHI ranged from about 5700Wh/m2 to 6700Wh/m2 with consistently higher values inland and lower values along the coasts. This indicates that photovoltaic technologies would perform well at any location although extreme high temperatures (over 30°C annual average in some locations) may degrade the performance of some types of photovoltaic technologies. Annual average daily DNI was much more variable across the stations, ranging from about 4400Wh/m2 to over 7300Wh/m2 with the highest values and clearest skies in the northwest part of the country. While most regions have sufficient solar resources for concentrating solar technologies, the western inland sites with average daily totals of over 6474Wh/m2 (average yearly totals of 2400kWh/m2/year) are superior to the eastern sites with average daily totals closer to 5510Wh/m2 (average yearly totals of 2000kWh/m2/year). This first year of data represents the beginning of a deeper understanding of solar resource characteristics in Saudi Arabia and the Middle East. Although continued measurements are needed to understand the interannual resource variability, the current study should have significant applications for preliminary technology selection, power plant modeling, and resource forecasting.

SAURAN: A new resource for solar radiometric data in Southern Africa

A new resource for sun strength data in Southern Africa has been established with the commissioning of a regional network of solar monitoring stations. The Southern African Universities Radiometric Network (SAURAN) is an initiative of Stellenbosch University and the University of KwaZulu-Natal (UKZN), and consists of an initial set of ten ground stations equipped with secondary standard thermopile radiometers. SAURAN’s aim is to provide a long-term record of sun strength in a region that shows excellent potential for the deployment of solar energy technologies. Instruments measuring direct normal irradiance (DNI), diffuse horizontal irradiance (DHI) and global horizontal irradiance (GHI) feed time-averaged data over 1-minute, hourly and daily intervals to a central archive from where they are accessible to the public via a website interface. Meteorological data is also provided by most of the stations. This paper gives a brief background to the SAURAN project and describes the network’s operation, coverage and future expansion. Examples of solar energy irradiance plots are also provided to illustrate the information available from the SAURAN database.