http://hdl.handle.net/10174/14413 Sun, 30 Aug 2026 04:47:13 GMT 2026-08-30T04:47:13Z http://hdl.handle.net/10174/42514 Title: Optimization and Numerical Simulation of Cs₂AgSbBr₆-Based Lead-Free Perovskite Solar Cells Using SCAPS-1D Authors: Haque, Md Ekramul; Ahmed, Md Tofael; Tlemçani, Mouhaydine Abstract: Extensive research into lead-free alternatives has been prompted by the toxicological and environmental issues around lead-based perovskite solar cells. The halide double perovskite Cs₂AgSbBr₄ has become a potential absorber material because of its non-toxic composition, good optoelectronic capabilities, and chemical durability [1]. Using the SCAPS-1D platform [2] and the device architecture FTO/ETL/Cs₂AgSbBr₄/HTL/Au, this work provides a thorough numerical modeling and optimization of Cs₂AgSbBr₆-based solar cells. To determine the ideal charge transport configuration, electron transport layers (TiO₂, SnO₂, ZnO, PCBM) and hole transport layers (Spiro-OMeTAD, CuSCN, NiO, MoO₃) are systematically screened to identify the optimal charge transport arrangement. Crucial elements influencing device performance such as absorber layer thickness, defect density, and doping concentration are investigated through parametric optimization. The results reveal that the optimal ETL/HTL combination significantly enhances power conversion efficiency, offering a viable pathway toward high-performance, environmentally friendly perovskite solar cells. Thu, 11 Jun 2026 23:00:00 GMT http://hdl.handle.net/10174/42514 2026-06-11T23:00:00Z http://hdl.handle.net/10174/42513 Title: Different PV Cooling Approaches Leading to Hybrid PVT System Development Authors: Ahmed, Md Tofael; Ali, Md Suruj; Naeema, Ashrafun; Haque, Md Ekramul; Graça, Rui; Rashel, Masud Rana; Tlemçani, Mouhaydine Abstract: Photovoltaic (PV) modules encounter major output losses during generation due to temperature increases resulting decreasing their efficiency. It does not suffer only performance losses but also creates faults, hotpots, cracks and other types of defects in the PV system module. Conventional active cooling systems like water-based, air based, phase change material (PCM) cooling are used to mitigate temperature rise in the PV system, but it requires external energy to deploy, and the recovered heat cannot be used as useful thermal energy. There are different types of photovoltaic thermal collector exists in the literature, but they mostly focus on the thermal energy generation where the improvement of electrical energy generation is significantly ignored [1]. This work discusses different existing cooling strategies and an overview of the development of hybrid PVT system. To identify sensitiveness of the model, different parameters changes impact on the PVT system is also analyzed. The mathematical model based on electrical and thermal model of the PVT system is also established [2]. Maximum power point tracking (MPPT) is an important factor to be considered in the photovoltaic energy generation and efficiency analysis which is also demonstrated for this developed model [3]. Finally, the work demonstrates the motivation of cooling techniques in the PV system leading to the development of hybrid PVT system. Thu, 11 Jun 2026 23:00:00 GMT http://hdl.handle.net/10174/42513 2026-06-11T23:00:00Z http://hdl.handle.net/10174/42512 Title: Machine Learning–Based Transient Stability Assessment of Renewable Energy Integrated Power Systems Authors: Ali, Md Suruj; Ahmed, Md Tofael; Ashrafun, Naeema; Rana, Masud Rana; Chatti, Nizar; Tlemçani, Mouhaydine Abstract: The use of renewable energy sources (RES) in modern inverter-based power systems is rapidly increasing and poses serious challenges to stability due to the reduction of system inertia and the erratic nature of power generation. Conventional time-domain methods are computationally very laborious and too slow for real-time stability assessment, and smart grids require a data-driven model for real-time monitoring of renewable energy. This paper proposes a machine-learning (ML) based method for fast and accurate transient stability assessment of modern power systems, by utilizing python based open-source simulation environment. A model of the IEEE 14-bus test system is modeled using PandaPower, where solar photovoltaic (PV) and wind generators were integrated at different penetration rates such as 20%, 40%, and 60%. The simulations were conducted considering comprehensive disruption scenarios such as line outages, load variations, and generator trips under different levels of renewable energy penetration. To classify stability, voltage magnitude, line loading, and voltage phasis deviation variables are considered as input characteristics. A Random Forest (RF) and Logistic Regression (LR) model is developed, trained and evaluated including metrics of accuracy, recall, precision, and F1-score. The simulation results demonstrate accuracy of the RF and LR models is 100% and 98.3%, respectively. The analysis reveals weak buses are most sensitive to stability degradation. The proposed models allow millisecond predictions that highlight importance of machine learning based on stability monitoring systems. The method provides modern, practical and scalable stability assessment solutions for next generation for inverter dominated smart grids. Thu, 11 Jun 2026 23:00:00 GMT http://hdl.handle.net/10174/42512 2026-06-11T23:00:00Z http://hdl.handle.net/10174/40985 Title: Using Indicator Kriging for Lead Spatial Patterns Assessment in sediments- the Caveira Mine Case Study Portugal. Authors: Fonseca, Rita; Albuquerque, Teresa; Araújo, Joana; Mota Silva, Natália Abstract: Evaluating the effectiveness of geomaterials in retaining potentially toxic elements of mine effluents is a key issue for the environmental remediation of former mining areas. The project GeoMaTre (Institute of Castelo Branco and the University of Évora, Portugal), aims at finding low-cost solutions for water and sediments rehabilitation using raw geomaterials, on abandoned mines from the Iberian Pyritic Belt, a metallogenic province in SW Portugal and Spain, hosting the largest concentration of massive sulphide deposits worldwide. One of the case studies is the Caveira mine in southwestern Portugal. Large piles of mining wastes containing significant quantities of metals, record the long history of its exploitation, which began in Roman times with the extraction of Au and Ag, having focused after the exhaustion of its reserves, on the extraction of the remaining metals (Cu, Pb, Zn) and S, until the date of its abandonment in the 1960s. These waste piles represent the main sources of metals in the streams, some with very high toxicity, such as Hg, resulting from the mixing with the gold-containing ore, widely used in the past in gold exploration. The design of the best remediation technique using the most suitable geomaterials for retaining pollutant metals started with the study and characterization of the spatial distribution of Hg in stream sediments, given its environmental hazardousness and geochemical behaviour. Sun, 01 Jan 2023 00:00:00 GMT http://hdl.handle.net/10174/40985 2023-01-01T00:00:00Z