Solar Maps Research Articles

Solar eclipse maps – historical and contemporary methodologies

ABSTRACT The first part of this paper examines the history of solar eclipse maps of the world from the seventeenth century to present. It compares the path of centrality (totality or annularity) on a few antique maps with the corresponding path given by modern astronomy programs. The research examines the connections between cartography, astronomy, ancient history, chronology, and archaeology. Since the uncertainties of Delta-T are accountable for the accuracy of eclipse maps, special attention has been devoted to ancient key eclipses. Through the identification of the earliest solar eclipse traditions in the Near East, it recommends new chronological anchors to help astronomers, mapmakers, and editors of historical atlases. It suggests the acceptance of four eclipses of the Long Chronology between June 2353 B.C. and February 1659 B.C. for the rate of Earth’s rotation. Optimal combined selection of ancient historical eclipse records and traditions is presented, to obtain the best-fitting curve of Delta-T (clock-time error) that is the key for the accuracy of solar eclipse maps. Several early historical solar eclipses are identified with high probability.

Optimizing Solar Potential Analysis in Cuba: A Methodology for High-Resolution Regional Mapping

The development of solar energy at a regional scale necessitates a thorough understanding of available resources. Cuba, facing prolonged economic, environmental, and energy crises, urgently needs to enhance its sustainability through solar energy. Although solar resource mapping is widespread, Cuba lacks extensive field measurements, often relying on models that may not be ideally suited for large regions, like Matanzas province. Spanning over 12,000 km² with nearly 150 km between its northern and southern extremes, Matanzas presents challenges for high-resolution solar mapping. This study introduces a methodology that integrates various methods and databases to achieve the maximum resolution in the resulting solar map. This approach is designed for large areas, where conventional high-resolution models fall short. By optimizing calculation times and parameterizing the entire surface latitudinally, a high-resolution solar resource map for Matanzas has been developed. This map significantly enhances the understanding of solar resources in Cuba and enables the proposal of new methodologies for analyzing solar potential in similarly large regions.

Notes on Measuring Concentration Ratio Distribution for a Solar Tower Using Moonlight

The authors' original concept of indirect solar flux mapping of a heliostat field measures CRD using a compact stationary array of moonlight illuminometers on the receiver aperture and a reference moonlight illuminometer on the dual-axis moon tracker. Two sets of moonlight concentration experiments (CCD camera + white target; concentrated lunar beam passing across the linear array of illuminators) were carried out on 63 heliostats at Badaling Solar Tower Power Plant in Beijing on a full moon night in 2018. How the sun and moon shapes differ for CRD as light sources on a solar dish is investigated. Solar/lunar CRDs are similar. Another lunar flux mapping model is also presented, allowing different moon shapes to estimate the solar CRD and contribute improvements in extrapolating measured lunar CRDs to a solar tower working with the real Sun by repeated smooth-filtering. In this paper, some unknown factors, effects, and improvements are carefully considered to enhance the CRD measurement accuracy of a solar tower power plant by using moonlight concentration.

Photovoltaics Energy Potential in the Largest Greek Cities: Atmospheric and Urban Fabric Effects, Climatic Trends Influences and Socio-Economic Benefits

This comprehensive study explores the influence of aerosols and clouds on solar radiation in the urban environments of nine of Greece’s largest cities over the decade from 2014 to 2023. Utilizing a combination of Earth Observation data, radiative transfer models, and geographic information systems, the research undertook digital surface modeling and photovoltaic simulations. The study meticulously calculated the optimal rooftop areas for photovoltaic installation in these cities, contributing significantly to their energy adequacy and achieving a balance between daily electricity production and demand. Moreover, the research provides an in-depth analysis of energy and economic losses, while also highlighting the environmental benefits. These include a reduction in pollutant emissions and a decrease in the carbon footprint, aligning with the global shift towards local energy security and the transformation of urban areas into green, smart cities. The innovative methodology of this study, which leverages open access data, sets a strong foundation for future research in this field. It opens up possibilities for similar studies and has the potential to contribute to the creation of an updated, comprehensive solar potential map for continental Greece. This could be instrumental in climate change mitigation and adaptation strategies, thereby promoting sustainable urban development and environmental preservation.

GIS-Based Digital Twin Model for Solar Radiation Mapping to Support Sustainable Urban Agriculture Design

GIS-Based Digital Twin Model for Solar Radiation Mapping to Support Sustainable Urban Agriculture Design

Prediction of solar activities: Sunspot numbers and solar magnetic synoptic maps

Prediction of solar activities: Sunspot numbers and solar magnetic synoptic maps

Solar energy potential mapping in Ukraine through integration of GIS, remote sensing, and fuzzy logic

ABSTRACT The Green Deal strategic plan for the development of renewable energy until 2030 is of particular importance in the context of the restoration of Ukraine’s post-war energy infrastructure. One of the key topics is the analysis of the possibilities of installing large solar power plants in Ukraine. In this article, a multi-criteria analysis of the suitability of the territory of Ukraine is carried out on the basis of climatic, topographic and land use criteria. To assess land suitability, criteria standardized using fuzzy logic with weights determined by experts through the method of pairwise comparisons were combined using a weighted sum model. Upon completing the study, a suitability map was generated, depicting zones with varying levels of suitability (ranging from 0 to 1) for solar power plant placement. It was found that more than 35.68% of the country has average values of the suitability index (0.65–0.7), and approximately 18.82% show high indicators (<0.7). Conditions are especially favorable in the south of Ukraine.

Solar potential for social benefit: Maps to sustainably address energy poverty utilizing open spatial data in data poor settings

Access to affordable sustainable energy is a significant challenge for many low-income countries experiencing energy poverty. The United Nations (UN) Sustainable Development Goal (SDG) 7 aims to “ensure access to affordable, reliable, sustainable and modern energy for all.” Simultaneously, the European Union (EU) seeks to reduce emissions by 55% by 2030. Decarbonization policies must be carefully considered to avoid adverse effects on vulnerable groups experiencing energy poverty. Solar technology offers a viable solution to decarbonize the building sector, reduce energy dependence on fossil fuels, and provide financial benefits to the public. Mapping solar potential is crucial to determine where investment in solar photovoltaic (PV) technology is most advantageous to the populations who stand to benefit the most. We combine a solar potential mapping approach incorporating socio-economic indicators indicative of energy poverty, using off-the-shelf Geographic Information Systems (GIS) tools that are easily replicated across cities facing energy poverty. Utilizing lowest common denominator data and analysis approaches, we offer creative and innovative mapping solutions. The socio-economic factors help to contextualise the benefits of distributed PV systems and highlight the need for mapping solar potential, in combination with energy poverty indicators for sustainable planning and policymaking. Our results for a case study in the city of Plovdiv, Bulgaria, demonstrate high solar energy potential that could meet 29% of the city's electricity needs, save citizens about M€43.84 annually, and pinpoint where to invest first for the highest gains. Finally, we offer suggestions on how to use these results to inform decarbonization policies to benefit low-income populations that are often missed in existing energy policies.

Multi-criteria solar power plant siting problem solution using a GIS-Taguchi loss function based interval type-2 fuzzy approach: The case of Kars Province/Turkey

The determination of the areas where the solar power plant will be installed is of great importance for the performance of the solar power plant. Solar and hydroelectric energy are the most widely used renewable energy sources in Kars province. Site selection for these power plants is an important factor in terms of reducing the installation cost of the solar power plant and achieving maximum efficiency during operation. Determining the areas where the power plants will be installed is a very complex and difficult to analyse spatial decision making problem. In this study, firstly GIS is used as a mapping method to obtain the locations of both solar power plants in Susuz, Arpaçay, Akkaya, Kars city centre, Selim, Digor, Kağızman and Sarıkamıș districts of Kars province and then Taguchi loss function based interval type-2 fuzzy approach is applied to the problem. In order to obtain more accurate results, the results of the two methods (GIS and Taguchi loss function based interval type-2 fuzzy approach) were also compared. According to the solar power plant map obtained, it was determined that the total area of suitable areas is 78600 km2.

Study of solar brightness profiles in the 18–26 GHz frequency range with INAF radio telescopes

Context. One of the most important objectives of solar physics is to gain a physical understanding of the solar atmosphere, whose structure can also be described in terms of the density (N) and temperature (T) distributions of the atmospheric matter. Several multi-frequency analyses have shown that the characteristics of these distributions are still under debate, especially for outer coronal emission. Aims. We aim to constrain the T and N distributions of the solar atmosphere through observations in the centimetric radio domain. We employed single-dish observations from two of the INAF radio telescopes at the K-band frequencies (18–26 GHz). We investigated the origin of the significant brightness temperature (TB) detected up to the upper corona (at an altitude of ∼800 mm with respect to the photospheric solar surface). Methods. To probe the physical origin of the atmospheric emission and to constrain instrumental biases, we reproduced the solar signal by convolving specific 2D antenna beam models. We performed an analysis of the solar atmosphere by adopting a physical model that assumes the thermal bremsstrahlung as the emission mechanism, with specific T and N distributions. We compared the modelled TB profiles with those observed by averaging solar maps obtained at 18.3 and 25.8 GHz during the minimum of solar activity (2018–2020). Results. We probed any possible discrepancies between the T and N distributions assumed from the model and those derived from our measurements. The T and N distributions are compatible (within a 25% of uncertainty) with the model up to ∼60 mm and ∼100 mm in altitude, respectively. Conclusions. Our analysis of the role of the antenna beam pattern on our solar maps proves the physical nature of the atmospheric emission in our images up to the coronal tails seen in our TB profiles. Our results suggest that the modelled T and N distributions are in good agreement (within 25% of uncertainty) with our solar maps up to altitudes of ≲100 mm. A subsequent, more challenging analysis of the coronal radio emission at higher altitudes, together with the data from satellite instruments, will require further multi-frequency measurements.

Study of solar brightness profiles in the 18–26 GHz frequency range with INAF radio telescopes

Context. The Sun is an extraordinary workbench, on which several fundamental astronomical parameters can be measured with high precision. Among these parameters, the solar radius R⊙ plays an important role in several aspects, for instance, in evolutionary models. Moreover, it conveys information about the structure of the different layers that compose the solar interior and its atmosphere. Despite the efforts to obtain accurate measurements of R⊙, the subject is still debated, and measurements are puzzling and/or lacking in many frequency ranges. Aims. We determine the mean, equatorial, and polar radii of the Sun (Rc, Req, and Rpol) in the frequency range 18.1 − 26.1 GHz. We employed single-dish observations from the newly appointed Medicina Gavril Grueff Radio Telescope and the Sardinia Radio Telescope (SRT) in five years, from 2018 to mid-2023, in the framework of the SunDish project for solar monitoring. Methods. Two methods for calculating the radius at radio frequencies were employed and compared: the half-power, and the inflection point. To assess the quality of our radius determinations, we also analysed the possible degrading effects of the antenna beam pattern on our solar maps using two 2D models (ECB and 2GECB). We carried out a correlation analysis with the evolution of the solar cycle by calculating Pearson’s correlation coefficient ρ in the 13-month running means. Results. We obtained several values for the solar radius, ranging between 959 and 994 arcsec, and ρ, with typical errors of a few arcseconds. These values constrain the correlation between the solar radius and solar activity, and they allow us to estimate the level of solar prolatness in the centimeter frequency range. Conclusions. Our R⊙ measurements are consistent with the values reported in the literature, and they provide refined estimates in the centimeter range. The results suggest a weak prolateness of the solar limb (Req &gt; Rpol), although Req and Rpol are statistically compatible within 3σ errors. The correlation analysis using the solar images from the Grueff Radio Telescope shows (1) a positive correlation between solar activity and the temporal variation in Rc (and Req) at all observing frequencies, and (2) a weak anti-correlation between the temporal variation of Rpol and solar activity at 25.8 GHz.

City-scale analysis of PV potential and visibility in heritage environment using GIS and LiDAR

Increasing the share of renewables, especially utilizing solar power in our energy mix is a highly prioritized aim of the EU. Budapest, the largest city and the capital of Hungary, contains almost 1 million flats in more than 190 thousand buildings, organized in various characteristic urban fabric types. Although on-site renewable energy production is severely limited in dense urban environments, the roofs offer a considerable potential to generate energy on-site.The present paper introduces a method to estimate the PV potential of rooftops on a large scale applying a GIS approach. Using LiDAR data, a Digital Surface Model (DSM) was created. The DSM was utilized to evaluate roof slope, orientation, and global irradiation. Solar potentials, available roof area, photovoltaic (PV) system capacities and estimated annual electricity production were derived from the GIS model. The method was used to develop an open access website called the Budapest Solar Map, which provides decision-makers with solar PV data. However, the nominal PV potential is limited by layers of heritage protection regulations that safeguard the sight of our case study area, Budapest, which is a World Heritage Site. Visibility is also surveyed with GIS and geometrical modeling from designated high points and from the street level, respectively.

The Significance of Stakeholders in the Rooftop Solar Power Plant Ecosystem Industry in Indonesia

Stakeholder analysis in an ecosystem is important for managers to planning the most efficient strategic steps for their organization. On the other hand, there is lack of research that mapping the significance of actors inside the ecosystem of an industry. This study attempts to utilize the network analysis as a method to examine the significance of stakeholders. We demonstrate the usage and effectiveness of this method in the rooftop solar power plant ecosystem industry in Indonesia. This study used a qualitative research methodology. Data were obtained through in-depth interviews with stakeholders who formed the industry. The result of this study are Indonesia’s rooftop solar power plant ecosystem map and power-interest grid of the stakeholders.

New Model for the Estimation of Solar Radiation on Façades in Urban Environments

This paper presents a new solar irradiance model for the estimation of the solar radiation on façades of buildings in urban environments. A model and a computer tool, using Visual Basic Application of Excel, have been developed to analyse in detail the radiation on façades. It can be used to determine, in a very intuitive, easy and fast way, using solar radiation contour maps, the best areas for the installation of photovoltaic systems. Finally, using the data obtained by the solar irradiance model for an application example, the electricity production of a photovoltaic system located at the selected façade is analyzed and discussed.

Building a Better Roadmap toward a Green Economy through Advanced Rooftop Solar Mapping and Enhanced Energy Yield

Objective: This study aims to develop a transparent roadmap for the implementation of rooftop solar (RTS) systems to boost solar energy adoption, addressing the lack of a definitive solar roadmap. The objective is to utilize Helioscope solar software to envision the maximum shadow-free area over building rooftops and simulate energy generation potential using fixed tilt-based and monthly optimum tilt-angle control-based solar photovoltaics systems. Methods: The research employs HelioScope software to estimate shadow-free rooftop areas of government buildings in an Indian state, considering both fixed-tilt and optimum tilt angle control-based solar tracking systems. The study validates monthly optimum tilt angles for different districts and presents an experimental setup with a 2kWp RTS system. Results: The district-wise analysis reveals the useful rooftop area and energy generation potential, indicating an increase in annual solar energy yield with the implementation of an optimum tilt angle control-based tracking system. The results suggest that chronological implementation based on available rooftop area can aid in achieving the mandated RTS target. Conclusion: The proposed methodology provides a guideline for developing a transparent RTS installation roadmap. The study highlights the potential of an 8% increase in annual solar energy yield by incorporating monthly optimum tilt angle control. The district-wise spatial differences in solar energy production serve as a prototype for other states and countries, facilitating effective solar mapping and policy planning for RTS installations.

Delineating suitable zones for solar-based groundwater exploitation using multi-criteria analysis: A techno-economic assessment for meeting sustainable development goals (SDGs)

While several articles have focused on determining a suitability map for groundwater exploitation by assigning weights to different thematic layers, this technique suffers from a lack of worldwide application because it focuses on the features of a specific region (terrain features, vegetation, and climate) during the investigation. To overcome this drawback, we expanded the evaluation method of groundwater exploitation by integrating the region characteristics and topography with the three pillars of sustainability outlined by the SDGs agenda. Seven thematic layers, reflecting the economic and technical characteristics of El-Saloum depression, Egypt, were prepared to develop a solar energy-based groundwater suitability map. It was depicted that about 11.5%, 29.3%, and 44.0% of the total depression were classified into “Most’, “Moderate”, and “Marginal” suitable locations, respectively. Based on the sensitivity analysis, the southeastern zone of the depression emerged as the most suitable site for solar-groundwater utilization due to its low salinity (<5000 ppm), reasonable groundwater depths (less than 50 m), and land availability (undeveloped regions). Substituting a diesel power system (DPS) with a photovoltaic system (PVS) in groundwater pumping and/or reverse osmosis (RO) desalination would reduce 1.2 kg CO2/kWh and maintain a payback period of 6.4 years with a cost of energy (COE) of ∼0.25 US$/kWh. Applying PVS for groundwater management could fulfill about 25.0%, 37.5%, 40.0%, and 20.0% of sustainable development goals (SDGs) 2 “Zero hunger”, 6 “Clean water and sanitation”, 7 “Affordable and clean energy”, 13 “Climate action”. The achievement of these SDGs was equivalent to 22.7%, 15.4%, and 13.2% of the environmental, economic, and social pillars of sustainability, respectively. Consequently, the study's findings are crucial for stakeholders and policymakers involved in the sustainable management of groundwater resources within the SDGs umbrella.

Weakly Supervised Solar Panel Mapping via Uncertainty Adjusted Label Transition in Aerial Images.

This paper proposes a novel uncertainty-adjusted label transition (UALT) method for weakly supervised solar panel mapping (WS-SPM) in aerial Images. In weakly supervised learning (WSL), the noisy nature of pseudo labels (PLs) often leads to poor model performance. To address this problem, we formulate the task as a label-noise learning problem and build a statistically consistent mapping model by estimating the instance-dependent transition matrix (IDTM). We propose to estimate the IDTM with a parameterized label transition network describing the relationship between the latent clean labels and noisy PLs. A trace regularizer is employed to impose constraints on the form of IDTM for its stability. To further reduce the estimation difficulty of IDTM, we incorporate uncertainty estimation to first improve the accuracy of noisy dataset distillation and then mitigate the negative impacts of falsely distilled examples with an uncertainty-adjusted re-weighting strategy. Extensive experiments and ablation studies on two challenging aerial data sets support the validity of the proposed UALT.

Suitability Analysis for Solar PV Farm Installation using GIS and Analytical Hierarchy Process (AHP) in Simara Island, Province of Romblon, Philippines

Finding suitable installation sites for renewable energy technologies requires careful planning and consideration of multiple factors and not just relying on the location’s energy potential. This research work presents a suitability analysis of solar PV farm installation using GIS and Analytical Hierarchy Process (AHP) in Simara Island, Province of Romblon, Philippines. The study gathered key important details of the island from various sources and then categorized them in terms of climatology, location, environment, meteorology, and disaster susceptibility. Meanwhile, a pairwise comparison was obtained after a panel of experts ranked the above-mentioned parameters. A multi-criteria decision analysis (MCDA) using AHP were then applied to generate new sets of suitability maps, which were combined through weighted overlay analysis using QGIS to produce the necessary solar PV suitability map. The map reveals the spatial distribution of suitable solar PV farm installation sites, including highly suitable, suitable, moderately suitable, marginally suitable, and unsuitable locations. Results show that most of the island is suitable for solar PV farm installation at 42.81%, while 39.73% accounting for highly suitable locations. Moderately suitable and marginally suitable sites account for 8.76% and 1.07%, respectively, and 7.63% is deemed unsuitable. This study successfully identifies suitable locations for solar PV farm installations on Simara Island, demonstrating the effectiveness of the GIS and AHP combined methodology. This approach holds great potential for guiding RE planning and development in similar island regions in the Philippines.

Impact of Photovoltaic (Pv) Solar Power for Reducing Carbon Dioxide (Co2) Emission in Kakuri Industrial Area, Kaduna

This study offers a solar energy road map to entice investors to fund clean energy technology in Kaduna, Nigeria, which has abundant and underutilized solar energy. The goal is to both improve the region’s sustainable technological development and lessen the impact of global warming caused by the burning of wood. Up order to do this, the techno-economic and environmental sustainability of putting up a grid-connected solar PV system in the area is verified using RETScreen Expert software. RETScreen Expert software aids in evaluating the financial viability of renewable energy projects through benchmark, feasibility, and performance analyses. It utilizes climate data, energy performance comparisons, and detailed financial assessments to provide a comprehensive evaluation. In designing a photovoltaic system for Kakuri Industrial Area in Kaduna, Nigeria, key considerations include PV module size, inverter and battery sizing, and energy demand calculations. A proposed 3MW system would cater to the energy needs of five industries, ensuring reliability even during cloudy days. The study also highlights the economic and environmental benefits, demonstrating significant potential for greenhouse gas emission reductions and financial returns. The project underscores the importance of thorough feasibility studies and sustainable design in implementing solar PV systems, showcasing their role in reducing reliance on fossil fuels and promoting renewable energy adoption.

Novel GIS-based fuzzy TOPSIS and filtration algorithms for extra-large scale optimal solar energy sites identification

Solar energy stands as an increasingly attractive and environmentally responsible energy source, possessing the potential to meet the burgeoning power needs of the Sarawak region. This paper proposes a novel methodology that combines Geographic Information System-based fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and filtration algorithms to identify the top 100 optimal Solar Energy Sites (SES). The research encompasses the extra-large scale potential SES comprising 19,237 coordinated data points. It evaluates SES based on 12 diverse criteria spanning climatic conditions, technical feasibility, accessibility, environmental considerations, and social factors. This research employs a meticulous double-layer filtration process to systematically eliminate unsuitable locations, resulting in a refined list of 1,862 potential SES. Subsequently, the fuzzy TOPSIS algorithm has further narrowed down the selection to the top 100 SES, constituting the core results of this research. The results reveal an interesting distribution of the identified SES, which mainly clustered in 3 huge categories (Kuching-Samarahan, Sibu-Kapit-Mukah and Bintulu-Miri). The identified 100 SES possess high closeness coefficients, which range from 0.7 to 0.85, where 1 indicates the best solution of the fuzzy TOPSIS algorithm. Additionally, the paper presents a spatial distribution analysis of the top-ranking sites across various divisions and districts. To validate the results obtained from the proposed model, a solar suitability map has been developed in ArcGIS Pro. When comparing the results from the proposed model to those obtained from the solar suitability map, most SES have consistent relative percentages, with only one SES falling below 50 %. To provide an overview of the similarity between the two models, the average relative percentage is computed at 69.01 %, signifying the proximity of SES to the optimal value of the solar suitability map. Furthermore, the developed source code in this research exhibits flexibility, featuring filtration algorithms that can accommodate any raster maps. It serves as an asset for researchers interested in conducting comprehensive large-scale SES identification in future case studies.