Solar Radiation Values Research Articles

City-wide Solar Radiation Potential Analysis by Coupling Physical Modelling and Machine Learning

Abstract. Addressing the challenges posed by climate change and meeting urban energy demands is of utmost importance in today's world. Building Integrated Photovoltaics (BIPV) emerges as a crucial solution for energy conservation and carbon emissions reduction in urban environments. However, traditional methods of assessing solar radiation on buildings using physical models are often computationally intensive and time-consuming. This paper introduces a novel hybrid approach that integrates physical model-based solar radiation calculation with machine learning techniques to analyze Solar Radiation Potential (SRP) across city-wide building infrastructure. The proposed approach precisely evaluates the SRP of representative blocks by leveraging computing-intensive physical models integrated with 3D building data. Subsequently, two machine learning models are developed to effectively predict the SRP of building roofs and facades across the entire city. To validate the efficacy of this approach, an experiment was conducted in Shenzhen, China, yielding insightful results. The findings reveal that Shenzhen has a huge potential for BIPV solar power generation, with mean annual total building roof and facade solar radiation values of 9.22*107 kwh and 2.47*108 kwh, respectively. It can be further observed that relying solely on rooftop installations is insufficient to meet electricity demand. This study not only provides an innovative alternative for city-wide SRP estimation by combining physical modeling and machine learning but also offers valuable insights for fostering low-carbon urban environments and informing data-driven and model-driven urban planning and management strategies.

Effect of Atmospheric Mixing on Spectral Reflectivity in Sentinel Images of Baghdad Province

The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September, and 22 December) 2021. Their spectral reflectance was calculated at the NIR band using a mathematical equation in the ArcGIS program for Sentinel 2 satellite images that had been processed and analyzed. Also, atmospheric boundary layer height and solar radiation values were downloaded for the same date as the satellite images and compared with the spectral reflectivity values of the land covers(agriculture area, residential area, open area, and river) and knowing the effect of the mixing layer and solar radiation on the spectral reflectance values. The highest value of spectral reflectivity, mixing layer height, and solar radiation was in June at (0.065, 1965.524629, and 897.7088) respectively. The spectral reflectivity of plants at near-infrared (NIR) was higher than the rest of the earth’s features because plants reflect near-infrared radiation and absorb the red and blue parts of the spectrum.

Integrating hydrogen into a hybrid system to meet a laboratory's electricity demand

Providing quality electricity to improve the living conditions of rural and urban populations in Africa, particularly in Cameroon, represents a challenging but achievable task. Indeed, Cameroon has the second largest hydrographic network in Central Africa, and thanks to this network, over 90% of electricity comes from aging hydroelectric dams that cause permanent power outages. The desire to take advantage of other benefits that nature has given this country has directed this work towards renewable energies. Thanks to the HOMER Pro software, a renewable energy hybrid system with hydrogen gas serving as storage and energy vector was adopted. Photovoltaic panels and wind turbines are proposed as primary energy sources for the permanent, low-cost supply of the IRAD laboratory at the University of Maroua. The software proposes three systems, one with the wind turbine as the only primary source, and considered as the most optimal. It has an energy cost equal to $0.0633, an NPC of $20330, and an initial capital of $8500. The other two systems are hybrids with a renewable fraction equal to 100%, and a load distribution strategy that is the charge cycle (CC) like the first system. The first less expensive hybrid system has an energy cost and an NPC respectively of $0.0778 and $24986. As for the second hybrid system, it has an NPC and an energy cost respectively of $26195 and $0.0778. Hydrogen fully plays its role as an energy vector and storage in all three systems. A sensitivity analysis was conducted in this work to ensure that the system proposed for the laboratory can also be adapted in the 9 other regions of the country. It appears that the values of wind resources, solar radiation, and temperature have a significant impact on the energy cost. The cities of Yaoundé and Ebolowa, displaying respective wind speeds of 2.07 m/s and 1.76 m/s, are recognized for having the lowest wind speeds in the country, which hinders the overall energy production and profitability of the system. The hybrid system suggested for these cities proves to be expensive, with energy costs exceeding the standard electricity price set by the energy distribution and marketing organization in the country.

Pre-Launch Calibration of the Bidirectional Reflectance Distribution Function (BRDF) of Ultraviolet-Visible Hyperspectral Sensor Diffusers

An Ultraviolet-Visible Hyperspectral Sensors (UVS) instrument is an ultraviolet-visible imaging spectrograph equipped with two-dimensional charge-coupled device detectors. It records both the spectrum and the swath perpendicular to the flight direction, offering a wide 112° swath. This configuration enables global daily ground coverage with high spatial resolution. The absolute values of in-orbit solar irradiance can be evaluated using the bidirectional reflectance distribution function (BRDF), with the measurement accuracy directly affecting the accuracy of constituent inversion. This paper outlines the calibration process for the BRDF of the UVS, detailing the calibration methods and equipment used. It also proposes a BRDF model and discusses key coefficients. The accuracy levels of the UVS in the UV1, UV2, and VIS channels were 2.162%, 2.162%, and 2.173%, respectively.

Variations in solar irradiance caused by solar cycle affect the temporal stability of ETM+ (LS7) ToA reflectance values at pseudo-invariant calibration sites (PICS)

ABSTRACT The aim of this study is to quantify the impact of the effect of long-term solar cycle variations in solar irradiance on the accuracy and temporal stability of ToA reflectance values from Enhanced Thematic Mapper Plus (ETM+/L7) sensor images. We used 1382 ETM+ scenes corresponding to five Pseudo-Invariant Calibration Sites (PICS), obtained between 2003 and 2020. Solar irradiance data from the Spectral Irradiance Monitor (SIM/SORCE) were used to calculate daily values of mean exoatmospheric solar irradiance (ESUN), implemented in the radiometric correction of ToA reflectance. Enhanced temporal stability coefficients and variance tests were calculated to evaluate the stability of the time series obtained. The results indicate that the use of daily SIM/SORCE solar spectra has a significant impact (alpha <0.001) on radiometric correction and the accuracy of ToA reflectance values. In radiometric calibration, the percentage of top of atmosphere temporal stability that can be recovered based on 5 Sahara PICS ETM+/L7 scenes can exceed 0.75%, 0.50%, 0.39%, 0.45%, 0.30% and 0.25% in the blue, green, red, NIR, SWIR-1 and SWIR-2 spectral bands, respectively, and is not considered statistically significant (alpha >0.05). We concluded that considering the effects of solar cycles during the radiometric calibration of multispectral sensors contributes to improving the long-term stability of ToA reflectance products.

Assessment of Theoretical and Test Performance Considerations of Concentrated Solar Water Purification System “Parabosol” in Underserved Regions

Water is a fundamental human right and a prerequisite for sustainable development because it is an essential element of existence. Notwithstanding, a huge part of the world’s population continues to face challenges in accessing clean and safe drinking water. This situation is particularly pronounced in arid and underdeveloped regions where there is a global water crisis that is a huge threat to human health, economic development, and environmental stability. Designed with solar energy, the award-winning “Parabosol” enhances water evaporation and purifies it simultaneously. Parabosol does not require any expensive machines or complicated infrastructural frameworks, making it both cost-effective and efficient for such vulnerable communities. Transporting it easily allows for quick deployment in remote areas during emergencies, ensuring a clean, dependable water supply for basic household use. This innovative measure, which reduces the risk of waterborne diseases and increases access to safe water resources within communities, could greatly contribute to public health promotion efforts. It is intended for daily performance that corresponds to the minimum needs of one family unit (no less than 35 L per person). The processing capacity of each station varies between 120 and 180 L of water per day (depending on geographical and environmental conditions), depending on geographical and meteorological (solar radiation values) factors. However, experimental values are around 250 L. Parabosol illustrates a novel model with its distinctive design and functionality, highlighting the critical role of clean energy in the development of a more sustainable and resilient future. Additionally, unlike macrosystems that require a substantial initial investment and ongoing operating costs, Parabosol is a portable solution that has the potential to address the issue of clean water scarcity in the future.

Numerical study of the thermal performance of a single-channel cooling PV system using baffles and different nanofluids

The present numerical study reports the performance of a cooling system for solar photovoltaic panels (PV) using different nanofluids (Al2O3, CuO, and ZnO). A novel parallel flow channel with strategically placed baffles was analyzed to improve the heat transfer between the back of PV and the nanofluid. The nanoparticles' Brownian motion and the nanofluid temperature effect were considered. Computational fluid dynamics was used to simulate the interaction between the fluid in motion and panel materials. Various nanoparticle concentrations, Reynolds numbers (18–1800), and solar radiation values (200–1000 W/m2) were examined. The results showed that the nanofluid composed of CuO was the most effective, improving thermal efficiency by 5.67 % compared to pure water in the lowest Re range. A 10 % vol. concentration of Al2O3 reduced temperature by up to 15 % and increased electrical efficiency by 4 % when the Re varied from 18 to 42. However, increasing the Re number and having low solar radiation values decreased the contribution of the nanofluid. Additionally, using baffles in the flow channel improved electrical efficiency by 2 %.

Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm

In recent years, the share of renewable energy sources in current energy production has been increasing due to the depletion of fossil fuel resources, increasing energy needs and environmental concerns. Solar energy, one of the most important renewable energy sources depending on being clean, sustainable and environmentally friendly energy source. Understanding the solar radiation value is crucial for maximizing the potential of solar energy and ensuring the efficient operation of solar energy systems. In this paper, it is aimed to develop a new global solar radiation (GSR) prediction model by using simulated annealing algorithm (SAA). Modeling solar radiation data with significant variability is a challenging task that necessitates the use of nonlinear approaches. Although the SAA is widely used in engineering and natural sciences, it has not previously been used to develop a GSR prediction model. While developing the SAA forecast model for the Adana region, long-term sunshine duration and solar radiation data obtained from the Turkish General Directorate of State Meteorology were used, as well as geographical features such as latitude and longitude of the selected region. The performance and applicability of the proposed model was examined by comparing it with different GSR estimation methods developed in the literature. The primary contribution of this study lies in the introduction of an inventive model, which has been constructed for the first time in the assessment of GSR, to the current collection of literature. The produced results were statistically compared with the observed data using six separate performance and error measures. The results of all years showed that the relative percentage error (RPE) less than 11.66 %, the mean percentage error (MPE) does not exceed 12.55 %, the correlation coefficient (R2) greater than 0.98, the mean absolute percentage error (MAPE) test results appear to vary close to the value 10, the sum of squared relative error (SSRE) test results seem to approaching 0 and the t-statistic test less than 4.06 for the annual GSR. It has been observed that the developed SAA GSR forecasting model has a successful performance when compared to different forecasting models popularly used in the literature. According to the statistical error results, the estimated GSR data from the novel SAA-GSR forecast model aligns well with the measured meteorological values. Given the efficacy of the established SAA model in GSR estimation, this study is anticipated to offer valuable insights and contributions to the application of the SAA approach in other energy applications.

Power Factor Analysis of Grid-Connected Solar Inverter under Different Irradiance Levels throughout the Day

The power factor (PF) plays a crucial role in determining the quality of energy produced by grid-connected photovoltaic (PV) systems. When irradiation levels are high, typically during peak sunlight hours, the PV panels generate more electricity. In this scenario, the PF tends to be higher because the real power output closely matches the apparent power drawn from the grid. Whereas, when irradiation levels are low, such as during cloudy weather or nighttime, the PV panels produce less electricity. In these conditions, the power factor may decrease because the real power output diminishes compared to the apparent power drawn from the grid. This could be due to reduced efficiency or increased reactive power flow. PF decreases linearly at solar irradiance values lower than 220 (W/m2). At the same time, it approaches unity at higher solar irradiance values than 220 (W/m2). In this study, the variation of the power coefficient of the grid-connected PV solar system depending on solar irradiation was modeled and analyzed using MATLAB/Simulink 41016490. The analytical expression of the power factor depending on the change in solar irradiation was found using the curve fitting method.

Influencing Factors Used for Performance Evaluation of Solar Dryers

Due to the rapid growth in human energy demand, research and development in renewable energy sources have become a top priority. Solar energy, as a renewable energy source, is widely used in the drying industry. This study examines the factors that influence the performance evaluation of solar dryers. The dryer consists of an air collector, a drying chamber, and a chimney. Experiments were conducted at the Solar Energy Laboratory of the Hungarian University of Agriculture and Life Sciences in Hungary (47.59° N, 19.36° E). The drying behaviour of single-pass and double-pass solar dryers was compared under the same environmental conditions. The analysis results indicate that the maximum solar radiation value is 950 W/m2 at 12:00. The maximum temperature difference between the top and bottom channels of the double-pass solar air collector is 9.5 °C. The average humidity in the environment, single-pass, and double-pass drying chambers is 31%, 26.5%, and 24%, respectively. The instantaneous efficiency of the single-pass solar collector reaches a peak of 56%, while the double-pass collector’s instantaneous efficiency peaks at around 60%. The collector performance curves show that the double-pass collector has a more stable performance.

Building Mass Optimization to Reduce Solar Radiation in High Rise Building by Using Parametric Approach

Buildings use 40% of global primary energy, therefore their design and use affect climate change. Building performance analysis can assist architects predict performance before construction with parametric design tools. Radiance can be reduced via a parametric mass, lowering cooling load and energy use. The study uses theoretical and computational research to explain, forecast, and analyze events, whereas parametric design optimizes complicated geometries using mathematical parameters and algorithms. Environmental analysis in Grasshopper with the Ladybug plugin uses Rhinoceros. This plugin provides solar radiation, and climate analysis capabilities. To determine the most energy-efficient building design, the research links independent and dependent variables such solar radiation intensity and building mass. The study uses Surabaya weather data and high rise buildings. The land is formed like a square, with a 15-degree slope to the north and is flanked by low-rise buildings. As a result, the location receives the most direct sunlight during the day. Then, solar radiation analysis. It helps optimize passive solar design solutions. According to the modelling results, solar radiation on the top and west sides are particularly large and dominant in 65.37 and 32.69 kWh/m2. Meanwhile, the north, east and south sides receive very little solar radiation. The following simulation considers the optimal direction, which is to extend west-east and face to the south. A multi-towered megastructure is a high-rise building that responds best to solar radiation. The total solar radiation value is 3,718,100 kWh. It can accommodate large spaces with large mass composition but relatively low total solar radiation values. The building towers provide shade to each other, thereby reducing direct radiation from the sun to the building. The sides of the building's podium are also shaded, so the top of the building is partially red.

Temporal Variation in and Influence of Environmental Variables on a Lepidopteran Community in a Mediterranean Mid-Mountain Area

The temporal variation in a community of nocturnal and diurnal Lepidoptera was studied in a Mediterranean mid-mountain area of the SW Iberian Peninsula between 2017 and 2019. Monthly samplings that allowed for the identification of 3528 specimens, belonging to 373 species from 40 different families, also provided data on the temporal and seasonal variation in richness and the abundance (dominated by Geometridae and Noctuidae), diet type (mainly oligophagous), voltinism (mostly univoltine) and biogeography of the community, primarily Mediterranean in scope. Richness, abundance and diversity were also found to be highly positively correlated with temperature and solar radiation, and less negatively correlated with precipitation and humidity. Canonical correspondence analyses (CCAs) also indicate that temperature and radiation are the climatic variables with the greatest influence on species occurrence over the different months of the year. The CCAs gave a cumulative variance value of 84.79% when using the monthly mean values of temperature, solar radiation and minimum relative humidity, and 86.4% if only monovoltine species were considered. Guidelines to maintain diversity in the environment of the study area are provided. It is possible that the area may function as a refuge area for Lepidoptera in the face of climate change and deforestation that are occurring in the geographical environment.

Mathematical modeling of an integrated photovoltaic-assisted PEM water electrolyzer system for hydrogen production

This work provides a new mathematical model of photovoltaic (PV) solar panels integrated with proton exchange membrane (PEM) water electrolyzer cells for optimal hydrogen production. The proposed mathematical model evaluates the operating temperature of the PV solar panel and PEM water electrolyzer and the effect of membrane thickness on hydrogen production performance. In the model results, when the operating temperature of the PEM water electrolyzer increased from 25 °C to 80 °C, the hydrogen flow rate of about 1.44 and 1.82 mL/min at 2 A/cm2, respectively. Moreover, the maximum flow rate of hydrogen produced in a 7-cell and 14-cell PV-assisted PEM water electrolyzer stack is around 349.98 mL/min and 699.91 mL/min, respectively. The total efficiency of the integrated PV-assisted PEM water electrolyzer stack is around 6.0–6.5%, depending on the solar irradiance values. This mathematical model significantly contributes to green hydrogen production using the integrated PV-assisted PEM water electrolyzer system. Moreover, the mathematical model of PV-assisted PEM water electrolyzer will be a pioneer in determining the hydrogen production potential of the PEM water electrolyzer systems.

Solar global irradiance from actinometric degree data for Filaret Observatory (Bucharest), 1892–1903

Long-term series of solar irradiation measured at ground level are not available in the old times. However, long-term series of actinometric degree data obtained by using the Arago-Davy instrument have been recorded in the second half of the 19th century in several locations of the world. We have developed recently a method to estimate global solar irradiance on horizontal surface from actinometric degree data (doi.org/10.1007/s00704-023-04485-2). This opens a way of finding proxy information about the incident solar irradiance on various areas of the globe before the 20th century. Hourly actinometric degree data for the years 1892–1903 are available at the Filaret Observatory (Bucharest, Romania, South-Eastern Europe). The observed series have a systematic decreasing tendency, which has been removed by using a correction procedure. The proposed method is used here to evaluate solar global irradiance at Filaret Observatory. Solar irradiance data provided by the Twentieth Century Reanalysis Project version 3 (20CRv3) are used as a reference. The expected hourly and daily average solar irradiance values show reasonable qualitative consistency with the 20CRv3 data. This consistency is notably stronger during the warmer months from April to September. Much better agreement is found for the monthly averaged solar global irradiance values. At this level, the proposed method and the procedure of the 20CRv3 project seem to validate each other.

Analysis of the drying kinetics of sargassum using direct solar dryer and solar energy direct

This paper presents the analysis of the kinetics of sargassum drying using a direct solar dryer and the direct energy from the sun. Four mathematical models were applied: Newton, Page, Henderson and Pabis; and Midilli et al. The seaweed was brought from the coast of Cancun, Q. R, Mexico. With the direct solar dryer, a total of 6 hours were required to dry it, the final humidity ratio was 0.013. In the case of solar energy without dryer, i. e., in open air, 12 hours were required in two non-consecutive periods, and the final humidity ratio was 0.025. The solar radiation values, temperatures and mass variation were obtained as a function of time. The kinetic model that best simulated the drying process was that of Anderson and Pabis, obtained after the statistical analysis was performed, the activation energy was also obtained.

A Comparative Study of Data Mining Methods for Solar Radiation and Temperature Forecasting Models

Photovoltaic (PV) energy systems are a leading type of renewable energy systems globally. Predicting PV energy production accurately is crucial for maintaining efficient energy grids, making informed decisions in the energy market, and reducing maintenance costs. To ensure high accuracy and optimal production, it is essential to monitor and analyze these variables regularly. Solar radiation and temperature are two meteorological variables that directly affect the quantity of PV energy generated in PV facilities. The Performance Ratio (PR) is a critical parameter for assessing PV plant performance. A comprehensive model was constructed in this study to forecast solar radiation and temperature using multiple machine learning methods, including Instance-Based K-Nearest Neighbor Algorithm (IBK), Linear Regression, Random Forests, Random Tree, Multilayer Perceptron (MLP), and MLP Regression. Moreover, we used time series approaches, such as Simple Exponential Smoothing (SES), Error-Trend-Seasonality (ETS), Autoregressive Integrated Moving Average (ARIMA) and Holt Winter&amp;#39;s Seasonal Method (HWES) models for PV systems prediction. Initially, we conducted daily forecasts as well as 1-step ahead forecasts at 5-minute intervals for both solar radiation and temperature. It is crucial to subject both variables to the same methodology in order to construct precise models for forecasting PV. Secondly, we compared the predicted values of solar radiation and temperature with the actual energy yield of the power plant to calculate energy production. Subsequently, a relative analysis of data mining models and time series models have been performed depending on the statistical error criteria like RMSE, MAPE, MABE, MAE, MSE, and direction accuracy (DAC).&amp;nbsp;

Utilization of vortex flow pattern in the design of an efficient solar air heater

In this work, numerical and experimental analyses of a new model of circular solar air heater are carried out to examine the effect of employing vortex flow inside the air vessel of collector for convection enhancement. In three-dimensional numerical CFD-based analysis, the COMSOL Multi-physics is used to solve the flow equations for the turbulent forced convection airflow and conduction equation for the solid parts of the solar heater at different air mass flow rates in the range of 0.003 to 0.012 kg/s. In the calculation of turbulent stresses and heat fluxes, the RNG κ-∊ turbulence model is employed. The surface to surfaces (S2S) radiation model is used to consider the radiations emitted by the hot surfaces in collaboration with the energy equation. For validation, the theoretical findings are evaluated against the experiment. For the studied test cases with different values of solar irradiation and air mass flow rate, thermal efficiencies of up to 80 % are found. In comparison to the conventional rectangular-shaped solar air heaters with smooth ducts, more than 100 % increase in the value of thermal efficiency is delineated from the theoretical and experimental findings. This gain is attributed to the unique flow pattern in the developed solar collector.

Evaluation of a grid-connected PV power plant: performance and agrivoltaic aspects

AbstractThe performance ratio, a globally recognized metric that correlates with reported global solar radiation values, serves as a crucial indicator for evaluating the efficiency of grid-connected PV plants. Also, a large scale PV power plant alone can afford some agricultural irrigation energy requirement of a region. In this study, the actual generation data from a power plant located in Bursa province in northwestern Türkiye, during its initial six years of operation have been analyzed. The analysis reveals that the annual electricity production of the power station reaches approximately 10 GWh. Notably, the time period between April and September witnesses a monthly electricity generation exceeding 1 GWh, with September emerging as the most productive month, characterized by an average performance ratio of 94.5% during this six-year period. However, over the span of six years, the highest average electricity generation occurs in July, peaking at 1.34 GWh. Also, the power plant alone can meet the agricultural irrigation energy requirement of the region in the range of 6.7–2.3%. From an environmental impact and global warming perspective, it is noteworthy that during the 36-month period in the summer season, the performance ratio exceeded 100% only three times. However, within the 32-month period in the winter season, the performance ratio exceeded 100% 19 times. This situation indicates that while the reported radiation rates by the managements are consistent with the actual values for the summer months, they need to be revised, especially for the winter months.

Improve The Conversion Efficiency and Electrical Output of The Solar PV System by Developing and Implementing a Cooling System

The performance of the grid-connected solar photovoltaic (PV) system in the present study is improved using cooling technology. This technology reduces the temperature of solar PV modules and thus increases their efficiency and lifespan. The current solar PV system has been installed in northern Baghdad in the city of Taji. This study included improving electrical power, conversion efficiency, and performance ratio. All of these improvements are achieved by cooling using water. The performance ratio (PR) and efficiency maximum values of the reference (unimproved) and improved solar PV modules are at 10:10 am at 88.30% &amp; 96.30% and 13.4% &amp; 14.6%, respectively. Improved and reference PV modules maximum solar radiation values occur at 12:00 pm at 1.91 W and 1.566 W, respectively. The maximum solar radiation values of the reference and improved PV modules are at 12:00 pm at 922.9 W/m2 and 1012.22 W/m2, respectively. The maximum daily gain of the power and solar irradiance are 22% and 10%, respectively. The significant innovation in the study is the successful performance optimization of the grid-connected solar PV system. Using different equations to study performance by following different behaviors. Along with improving and studying CIGS PV module performance.

A Multi-Stage Approach to Assessing the Echo-Tech Feasibility of a Hybrid SAM-CREST Model for Solar PV Power Plants in Maryland, USA

Maryland is actively working towards doubling its Renewable Portfolio Standard (RPS) target, aiming to increase the share of renewable energy from 25% by 2020 to 50% by 2030. Furthermore, Maryland stands out as a state that strongly supports solar initiatives, offering incentives and specialized programs to assist residents in adopting solar energy solutions. The paper presents a multi-stage approach: Stage 1—Location Selection Process, Stage 2—Technical Feasibility Study, and Stage 3—Economical Feasibility Study. In Stage 1, the study focuses on three potential solar farm locations in Maryland: Westover, Princess Anne, and Eden. Stages 2 and 3 involve a feasibility assessment with detailed technical analysis using the NREL System Advisor Model (SAM) and PVWatts to determine monthly power to the grid and Energy Yield. Subsequently, economic feasibility is assessed using the NREL Clean Renewable Energy Estimation Simulation Tool (CREST), focusing on competitive levelized costs of energy (LCOE), payback time, and cumulative cash flows. Results indicate that all three locations exhibit promising solar irradiance levels, system outputs, and potential energy yields. Due to high solar irradiation, the Westover area has the highest energy yield at 1583.13 kWh/kW, while Princess Anne boasts the highest system output at 333.59 GWh. The economic evaluation suggests that all three locations become profitable within a two-year payback time, with competitive levelized costs of energy (LCOE). Westover emerges as the most cost-effective option at 5.99 cents/kWh, attributed to its higher solar irradiation values and energy yield compared to Princess Anne and Eden. Cumulative cash flows provide insights into long-term profitability, with Princess Anne, MD, having the highest Cumulative Cash Flow over 25 years at $183,383,304. By evaluating technical and economic aspects, this feasibility study offers quantitative insights to guide decision-making for the installation of Solar PV, considering both technological and economic feasibility.