Extreme weather events like droughts, floods, heatwaves, and cyclones are increasingly linked to climate change, leading to fatalities, infrastructure damage, and the displacement of thousands. CO2 emissions primarily drive this climate change from burning fossil fuels. South Africa (SA), the highest CO2 emitter in Africa, heavily relies on coal, which accounts for nearly 85% of its emissions. However, SA also has significant but underdeveloped solar energy potential. Expanding solar PV is crucial for SA and other African nations to address energy shortages, reduce GHG emissions, enhance energy security, stimulate economic growth, create jobs, and achieve long-term cost savings. The study includes a computational modelling case study to evaluate PV potential and system performance, comparing onshore and offshore scenarios. It reports a Global Tilted Irradiance (GTI) of 1866 kWh/m² for land-based PV (LPV) and 1797 kWh/m² for FPV, with a Levelised Cost of Energy (LCOE) of $0.04612/kWh for LPV and $0.05664/kWh for FPV, respectively. The results suggest that the 10-kWp LPV system slightly outperforms the FPV system, though both are within acceptable performance ranges because of harsher offshore conditions. The paper proposes hybrid RE systems including FPV to improve SA's grid stability and efficiency.

This paper reviews the most significant aerodynamic, structural, and material advances in wind turbine blades. If the market is to be more sustainable, wind turbine efficiency becomes an important consideration. The article highlights the aerodynamic innovations that refine blades to optimize performance and capture more energy in higher lift-to-drag ratios. The structural advancement is based on high-end design techniques for high performance in extreme conditions to eliminate maintenance costs. Then there are the material improvements, such as lightweight, robust composites that make for longer blades with the ability to capture more energy without compromising strength. This multidimensional approach is, overall, crucial to widespread utilization of wind as a sustainable and affordable energy source against the backdrop of increasing energy needs.

Electricity is one of the major factors that influence the level of growth of an economy, as well as human development. With applications in diverse spheres of life, it is at the core of human productivity and economic growth. Nations therefore, continually strive to ensure adequate and secured supply. Nigeria’s electric power sector experienced a major event in 2013 with the privatization of successor entities, pursuant to the enactment of the Electric Power Sector Reform Act (EPSRA) 2005. With about ten years of the electricity market in Transitional phase, this research sought to assess the impact of key operational and economic factors on the level of her on-grid electricity supply. Multivariate linear regression, a least squares approximation method was adopted considering four independent variables – Available Capacity (MW), Grid Outage Events (Total and partial), and Foreign Exchange Rate (₦/$). The Statsmodel package of python programming language was used for the 45 months’ data points for each variable. A weak relationship was found with the combined variables explaining 8.1% of the dataset for power generation from the developed model. However, Available Capacity, Grid Outage Events, and Foreign Exchange Rate are not sufficient to determine the growth of grid connected power generation.

The quest for efficient and sustainable energy solutions has propelled the exploration of novel materials and strategies for enhancing the performance of thin-film solar cells (TFSCs). This work presents a comprehensive investigation into the potential of CuBi2O4 based TFSCs as a viable candidate for high-efficiency photovoltaic devices. Through rigorous numerical simulation utilizing the SCAPS-1D software, this study delves into the intricate interplay of material properties, layer characteristics, and design strategies to unlock the untapped potential of CuBi2O4 based SCs. The study extensively investigates the influence of thickness, doping levels, and defect densities of each absorber on electrical properties like open-circuit voltage (Voc), short-circuit current density (Jsc), fill factor (FF), and power conversion efficiency (PCE). The simulation results reveal a remarkable achievement, with a recorded efficiency of 36.04%, FF of 81.11%, JSC of 32.15 mA/cm², and VOC of 1.38 V. These findings point to the potential of thin-film SC based on CuBi2O4 as a greener and more efficient photovoltaic option. As an absorber material for next-generation SC, CuBi2O4 exhibits potential with an efficiency of 36.04%. This investigation advances CuBi2O4-based thin-film SC and provides light on sustainable energy solutions.

This paper proposes an enhanced islanding detection method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a pattern recognition neural network (PANN). Negative sequence voltage data from both islanding and non-islanding scenarios were acquired through MATLAB Simulink simulations, with samples collected at a frequency of 3.84 kHz over a 2.5-second period. The voltage signals were decomposed into intrinsic mode functions (IMFs) using CEEMDAN, after which key features namely normalized max value, standard deviation, and entropy of the IMFs were extracted. The extracted features were used to train the PANN. The model was evaluated using cross-validation and several performance metrics, including accuracy, precision, recall, and F1 score. The proposed model achieved an overall accuracy of 98.6%, with a precision of 100%, a recall of 97%, and an F1 score of 98%. The detection time was found to be 0.2381 seconds, indicating the method's suitability for real-time applications. Furthermore, feature permutation importance analysis highlighted the critical role of certain features in the model's performance. The results demonstrate that the proposed method provides a reliable and efficient solution for islanding detection in grid-connected PV systems, significantly reducing the non-detection zone and ensuring high detection accuracy. This study contributes to developing of advanced detection techniques, enhancing the safety and reliability of modern power systems.

Silica (SiO2), represents a main component used in various applications such as the manufacture of photovoltaic cells and fiberglass. Despite this importance, the use of silica in Algeria remains limited due to the quality of the material or unknown for some deposit. In this work, we carried out an in-depth characterization of the siliceous sandstone samples, using various advanced qualitative and quantitative characterization techniques of metallographic microscope, granulometric analysis, DRX and XRF. The results showed that the different characterized samples have a fairly silicon dioxide (SiO2) purity of 89.15 % at 250-400 µm of size with the presence of different types of defects, namely mineral inclusions of clay and oxide minerals. The presence of impurities, in particular iron and aluminum, limit the use of this silica for the production of advanced materials.

When outflow of heavy ions such as O+ occurs, the atmospheres of planets are gradually loss. The ions being depleted in the ionosphere, under favourable conditions, upwell into the underlying magnetosphere and forms a substantial part of plasma in the magnetosphere. The motion of the heavy ions affects the Alfvén speed as a result, alters global magnetospheric dynamics. Joule heating, electron precipitation and other suprathermal energization are part of the mechanisms involved in the outflow process. Seven hundred and sixty two 762 events of periods of noticeable velocity upflow in conjunction with activities in the electron precipitation as well as enhancement in electron and/or ion temperature(s) were observed by the EISCAT Svalbard Radar (ESR) during the 2007 campaign. The 762 events were categorized by velocity strength in a colour coded plots. A further observation of periods when the ion upward velocity covered a wide range of altitude is examined, and the distribution of the events shows that about 9.2% of the upflow velocity covers a wide range of altitude. Furthermore, analysis shows that the distribution of high velocity events (≥ 200 ms-1), in conjunction with Kp ≥ 4 is peaked around local noon while other upwelling’s of moderate and low velocities with same range of Kp is skewed towards the night-side. Ion upwelling on the other hand, being a function of electron density and the corresponding velocity, shows that events of same velocity range, may belong to different flux regime, and vice versa.

Power transformers are considered the heart of power systems. The malfunction or undesirable outage of the power transformer will cause a tremendous revenue loss for the utilities. Therefore, a regular or preventive test must be accomplished on the transformer to check its state. Some standards, such as the American Transformer Diagnosis Guide and the American Society for Testing and Materials, have instructions for testing the transformers. The current works addressed which tests can be accomplished to predict the insulating paper state, which is the indicator of transformer aging. Furthermore, ANN model will be constructed to use it as a prediction tool of the paper state when the water content (WC), acidity (ACI), interfacial tension (IFT), oil color (OC), and 2-furfuraldehyde (2-FAL) were known. The ANN results indicated that the ANN's prediction accuracy was 93.87%.

Perovskite-based hybrid organic-inorganic solar cells that use the methylammonium lead tri-iodide (CH3NH3PbI3) have demonstrated ever-increasing energy conversion efficiency and low processing costs, comparable to that of high-efficiency silicon-based solar cells. However, it is suffuring from instability caused by material degradation. Recently, enhancing stability and hence decreasing the degradation process of CH3NH3PbI3based solar cells is one of the main topics of research in photovoltaic field. The poor stability of these cells prevents their commercialization despite their huge potential that exceeds conventional solar cells. The energy efficiency and economic viability of Perovskite cells depend primarily on the rate of degradation caused by light, temperature, moisture, and oxygen. This paper presents a review of different degradation sources of CH3NH3PbI3-based Perovskite solar cells (PSCs). In this work, a deposition of a CH3NH3PB1-xSnxCl3 Perovskite layer using spin coating method has been investigated. Therefore, different rotation speed have been used in layer spin coating phase to find out their effects on structural parameters characteristics of the resulting CH3NH3PB1-xSnxCl3 organic/inorganic Perovskite material.