http://ir.bdu.edu.et/handle/123456789/1844 Mon, 13 Jul 2026 14:49:26 GMT 2026-07-13T14:49:26Z http://ir.bdu.edu.et/handle/123456789/16873 Solar Energy Assessment using Data-driven and Physical Models: Application for Crystalline Silicon Photovoltaic Systems in Ethiopia Gedifew, Assaye Solar radiation, the electromagnetic energy emitted from the Sun, is a fundamental driver of Earth's weather and climate systems and represents a vast, clean energy source. Global solar radiation (GSR) is the total amount of solar radiation (both direct and diffuse) reaching a horizontal surface on Earth. It is a key measurement for evaluating the solar energy potential of a specific location, which in turn is essential for assessing the expected performance and efficiency of solar photovoltaic (PV) system. Thus, the accurate measurement and estimation of GSR is crucial for assessing and utilizing solar energy resources at both global and local scales. Hence, this study investigates estimations of GSR and assesses the performance of crystalline silicon (c-Si) PV cells/modules across Ethiopia, by utilizing a comprehensive approach that integrates data-driven and physical models. The study also implemented various optimization techniques such as determining the optimum tilt angle and tracking mechanisms. For this purpose, twelve machine learning (ML) and one stacked/ensembled model were trained and validated with hourly, daily and monthly ground-based global solar radiation data from 16 synoptic weather stations (2020-2022), supplemented by meteorological, aerosol, and sky condition data from MERRA-2 and NASA POWER archives. The three stations with distinct weather patterns were withheld from the model development process for model transferability/generality test. A stacked/ensemble model (i.e., constructed by stacking better performing separate models) showed exceptional predictive performance with error metric values ranging (R²: 0.956-0.963; RMSE: 9.938-11.784 W/m²) for all time scales. With this performance capability we generated a high-resolution (1° x 1°) global solar radiation data across Ethiopia for the year 2022, and the distribution showed a precise spatial and seasonal dependence with the highest in spring (i.e., 594 - 641 W/m2; eastern and northeastern) and lowest in summer (i.e., 359 – 405 W/m2; western and southern parts of the nation). Such analogs were also observed on the peak sun hours and plane-of-array (POA) irradiance distribution with their annual value ranging from 4.83 – 6.57 kWh/m2/day and 0.65 – 1.05 kW/m2, respectively, across the nation. Here it’s worth noting that to model POA irradiance, we implemented five decomposition and six transposition models (i.e., thirty different independent combinations). Furthermore, we incorporated POA irradiance into a single diode PV cell model to evaluate c-Si PV cell performances. Consequently, the annual PV cell temperature, ranging vii from 38.84°C to 55.45°C, significantly impacted device parameters. The short-circuit current (Jsc) mirrored POA irradiance trends, while the open-circuit voltage (Voc) showed an inverse temperature dependence. The annual PV cell efficiency varied from 13.02% to 22.35%, with clear average seasonal variations such as the highest in spring (20.72%) and the lowest in summer (16.01%). Besides, optimal PV module tilt angles and implementation of different tracking mechanisms were determined. The monthly optimal tilt angles ranged from 0° (July) to 47.90° (January), while seasonal averages were observed as 29.40° (winter), 21.65° (autumn), 12.34° (spring), and 8.8° (summer). The annual optimal tilt angle varied from 14.51-21.52o. In addition, the performance of different tracking mechanisms (dual/full axis: DAT, vertical-axis: V-axis, east-west/incline east-west: EW/IEW, north-south: NS) were also evaluated. Dual/full axis tracking yielded the highest annual average efficiency (44.89%), while NS tracking resulted in a 28.46% energy loss compared to horizontal mounting. On the other hand, PV module mounted at optimal tilt angle resulted in a 4.12% gain, while EW/IEW and vertical axis tracking yielded 43.12% and 24.94% energy gains, respectively compared to horizontally mounted. Overall, this study provides a valuable resource for selecting, comparing, and designing future solar PV systems in Ethiopia. It contributes to strategic PV deployment by aiding in energy assessment and forecasting. Moreover, the study offers an optimal tilt angle model, guiding the selection and implementation of the best tracking mechanisms for PV modules/panels in Ethiopia. This information is essential for effective energy assessment and forecasting across the nation Sat, 01 Nov 2025 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16873 2025-11-01T00:00:00Z http://ir.bdu.edu.et/handle/123456789/16832 Effect of Fresnel First Zone on Trans-ionosphere Propagation of GNSS Signal Cherinet, Assefa The trans-ionospheric propagation of Global Navigation Satellite System (GNSS) signals is significantly influenced by ionospheric irregularities, particularly at equatorial and low-latitude regions. This study investigates the effect of the Fresnel First Zone a fundamental concept in wave diffraction on GNSS signal scintillation. The Fresnel scale defines the spatial dimensions of ionospheric irregularities that most strongly scatter GNSS signals, causing amplitude and phase scintillations that degrade signal quality. Using theoretical models and observational data, including S4 index measurements, the research analyzes how variations in electron density and irregularity drift affect signal propagation. The findings underscore the importance of the Fresnel First Zone in understanding diffractive scattering processes and provide insight into the mitigation of GNSS signal disruptions, especially in space weather-sensitive regions. This work contributes to enhancing GNSS reliability for communication and navigation applications. Sun, 01 Jun 2025 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16832 2025-06-01T00:00:00Z http://ir.bdu.edu.et/handle/123456789/16831 Solar Activity Impact on the Earth’s Ionosphere over East Africa during 2009 - 2019 Shumet, Workie The ionosphere, a vital layer of the Earth’s atmosphere, plays a significant role in influ- encing radio communication, satellite navigation, and space weather prediction, with its behavior being profoundly affected by solar activity, including EUV flux, sunspots, so- lar radio flux, and geomagnetic activity. Understanding the ionospheric response to these solar and geomagnetic activity changes is crucial for space weather research, particularly as these responses vary spatially and temporally, necessitating extensive study to mitigate their impacts on human technologies. This dissertation investigates the impact of solar and geomagnetic activity on the Earth’s ionosphere over East Africa from 2009 to 2019, during solar cycle 24 and it focuses on the medium- and long-term variations in ionospheric Total Electron Content (TEC) using GPS-derived TEC data from eight stations at low/equatorial latitudes; and solar and geomagnetic indices (EUV, F10.7, SSN, Dst, and Kp) observa- tions. We have applied statistical analysis and quadratic fits with solar proxies (EUV, F10.7, and SSN). Daily mean solar and geomagnetic indices and vertical Total-Electron-Content (vTEC) were analyzed using statistical methods and quadratic fits to identify trends, fore- cast vTEC, and describe its daily, monthly, and seasonal variations. The research highlights that while equinoxes exhibit higher vTEC values compared to solstices, the influence of so- lar activity varies significantly across different timescales. Notable findings include peak vTEC values during equinoxes, especially in March, October, and April 2014, and a strong correlation between vTEC and solar parameters, with 45% to 81% of vTEC variations explained by these indices. The variations of vTEC showed positive associations with the solar parameters. The study reveals that EUV flux has the strongest association with vTEC, particularly during solar maxima, while F10.7 serves as a better proxy for EUV flux. In the predictions of vTEC, the maximum deviations and number of errors were observed during solar maxima years compared to solar minima. The quadratic model effectively captures the dependency of vTEC on solar activity, emphasizing the need for continuous monitoring and modeling of ionospheric conditions to mitigate the impacts on technological systems. Insights into ionospheric behavior enhance the understanding of solar activity’s effects on the ionosphere, contributing to improve space weather prediction models and communica- tion systems in the region, and suggesting future research to integrate these findings into global models. v Fri, 01 Nov 2024 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16831 2024-11-01T00:00:00Z http://ir.bdu.edu.et/handle/123456789/16826 Spatio-Temporal Variability Of Aerosols Over East Africa-Ethiopia Using Modis Satellite Data Ambachew, Abeje Aerosols are tiny mixtures of liquid-solid particulate matter suspended in the atmosphere that play significant roles in human health and climate dynamics, directly, indirectly, and semi-directly. There have been large spatiotemporal variations in the optical properties of aerosols, clouds, precipitation, and radiation due to environmental and meteorological conditions, industrial and agricultural influences, and other human and natural influences in each ecological functional area. This study was conducted on the spatiotemporal variability of aerosols in sixteen selected stations clustered into four regions over East Africa-Ethiopia using satellite-based data that have not yet been studied for periods 2001–2022. This PhD thesis work reports the spatiotemporal variability of aerosol particles and their optical interactions with the cloud parameters and radiation budget over East Africa, with particular interest in Ethiopia. The study covers sixteen selected stations in East Africa-Ethiopia with neighbouring doughters Eritrea, Djibouti, and South Sudan countries clustered into four regions for the periods of 2001–2022 to obtain detailed information on the spatiotemporal behaviours of aerosol particles and their effects on clouds and radiation budget. The aerosol optical parameters, Ångström exponent AET calculated from the aerosol optical depth AOD, cloud top pressure CTP, cloud top temperature CTT, mean cloud fraction MCF, and atmospheric water vapor AWV were extracted from the Moderate Resolution Imaging Spectroradiometer MODIS satellite data. We collected precipitation PPT data from the Tropical Rainfall Measuring Mission TRMM, and outgoing long-wave radiation OLR flux is collected using clouds and the Earth’s Radiant Energy System CERES satellites. According to the results, there is a significant variation in the daily AOD and AET, with maximum values most likely occurring between August 11 and September 15 for Aqua and between June 22 and July 24 for both Terra and Aqua in the southeast and northeast clusters. The results range from 0.00 to 2.10 and 0.67 to 1.23. The OLR, CTP, and CTT parameters are out of phase with AOD and increase-decrease swings with AET Mon, 01 Jul 2024 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16826 2024-07-01T00:00:00Z