Solar Power Technology for Electricity Generation

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (10 January 2024) | Viewed by 6277

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Guest Editor
Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
Interests: concentrated solar power; photovelteic; optics and thermology for solar power; solar thermal power
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Special Issue Information

Dear Colleagues,

Modern human civilization is based on energy, especially electric energy. At present, electric energy production relies heavily on fossil fuels, and there are huge problems, including resource depletion and environmental pollution. It is urgent to develop new energy sources. Solar energy is the most abundant energy source, and the solar energy reaching the Earth's surface is 10,000 times of the energy consumed by human beings at present. Developing solar power generation technology is an indispensable technology to solve the future energy supply of human beings.

We are inviting submissions to the Special Issue on Solar Power Technology for Electricity Generation, including various related technology and science, application and environmental and economic influence, especially recent advances for both theoretical and experimental studies, as well as comprehensive review and survey papers.

Dr. Weidong Huang
Guest Editor

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Published Papers (3 papers)

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Research

24 pages, 5437 KiB  
Article
A Comprehensive Methodology for the Statistical Characterization of Solar Irradiation: Application to the Case of Morocco
by Naoufal Bouhorma, Helena Martín, Jordi de la Hoz and Sergio Coronas
Appl. Sci. 2023, 13(5), 3365; https://doi.org/10.3390/app13053365 - 06 Mar 2023
Cited by 1 | Viewed by 1495
Abstract
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the [...] Read more.
The prediction and characterization of solar irradiation relies mostly on either the use of complex models or on complicated mathematical techniques, such as artificial neural network (ANN)-based algorithms. This mathematical complexity might hamper their use by businesses and project developers when assessing the solar resource. In this study, a simple but comprehensive methodology for characterizing the solar resource for a project is presented. It is based on the determination of the best probability distribution function (PDF) of the solar irradiation for a specific location, assuming that the knowledge of statistical techniques may be more widely extended than other more complex mathematical methods. The presented methodology was tested on 23 cities across Morocco, given the high interest in solar investments in the country. As a result, a new database for solar irradiation values depending on historical data is provided for Morocco. The results show the great existing variety of PDFs for the solar irradiation data at the different months and cities, which demonstrates the need for undertaking a proper characterization of the irradiation when the assessment of solar energy projects is involved. When it is simply needed to embed the radiation uncertainty in the analysis, as is the case of the techno-economic valuation of solar energy assets, the presented methodology can reach this objective with much less complexity and less demanding input data. Moreover, its application is not limited to solar resource assessment, but can also be easily used in other fields, such as meteorology and climate change studies. Full article
(This article belongs to the Special Issue Solar Power Technology for Electricity Generation)
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12 pages, 6134 KiB  
Article
Soil Characterization and Soiling Impact to Facilitate Photovoltaic Installation
by Douglas Olivares, Abel Taquichiri, Pablo Ferrada, Aitor Marzo, Mauro Henríquez, Darío Espinoza, Edward Fuentealba and Jaime Llanos
Appl. Sci. 2022, 12(20), 10582; https://doi.org/10.3390/app122010582 - 20 Oct 2022
Cited by 1 | Viewed by 1407
Abstract
There is currently an energy crisis that has led to photovoltaic operators maximizing their resources, making soiling a problem to consider in order to ensure project profitability. Energy production costs are strongly affected by the use of scarcely efficient cleaning techniques that are [...] Read more.
There is currently an energy crisis that has led to photovoltaic operators maximizing their resources, making soiling a problem to consider in order to ensure project profitability. Energy production costs are strongly affected by the use of scarcely efficient cleaning techniques that are not suitable for a particular type of contaminant, climate, and installation. This paper introduces a technology that is suitable for studying soiling, thus decreasing the number of variables studied and reliable results were obtained. Our attention is focused on deposited material physicochemistry, local geology, and installation effects. Analysis via scanning electron microscopy and pits revealed a similarity between local geological processes and module soiling, with gypsum being responsible for soil and module cementation. Analysis with Atomic Force Microscopy confirms the cementation effect and crust formation on the lower part of the photovoltaic glass, the latter concentrating in the greatest amount of cemented material. Using a solar simulator, the characteristic curves produced by the cemented material were studied, and it was determined that the lower part of the glass produced the greatest losses (27%). Thus, a non-uniformity deposition was generated, creating resistance between the cells. From the data obtained, it was possible to make recommendations regarding making decisions about plant cleaning, instead of only considering the physicochemical analysis of the deposited material. Full article
(This article belongs to the Special Issue Solar Power Technology for Electricity Generation)
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8 pages, 397 KiB  
Article
Solar Position Algorithm Based on the Kepler Equation
by Weidong Huang and Bowen Liu
Appl. Sci. 2022, 12(11), 5449; https://doi.org/10.3390/app12115449 - 27 May 2022
Cited by 2 | Viewed by 2644
Abstract
When calculating the position of the sun, earth’s motion can be assumed to be an ellipse if the accuracy of calculation is required to be 0.01 degrees. Then, Kepler’s equation can be applied from the mean anomaly of the sun at a specific [...] Read more.
When calculating the position of the sun, earth’s motion can be assumed to be an ellipse if the accuracy of calculation is required to be 0.01 degrees. Then, Kepler’s equation can be applied from the mean anomaly of the sun at a specific time to calculate the true anatomy of the sun at the time, and the sun’s position can be calculated. The average absolute error of calculating the sun’s altitude and azimuth is only 0.04 and 0.06 mrad, respectively, which can meet the requirements of a concentrated solar tracking system. This method only needs to correct the length of the regression year and the near point year for every 100 years, so it can be used for a long time. Full article
(This article belongs to the Special Issue Solar Power Technology for Electricity Generation)
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