Coskun Firat

Partial shading and non-uniform surface conditions can cause severe photovoltaic (PV) power loss that is not always reflected by scalar indicators such as fill factor. This study evaluates R _I,G = ( I _sc / G )/( I _sc / G ) _ref as an irradiance-normalized current-collapse index for screening current-limited electrical states. The primary analysis used 17 experimental I – V traces from two crystalline-silicon PV modules under clean, soiled, and partially shaded conditions. An additional validation dataset provided 112 outdoor I – V measurements from 19 ZW 86 × 82 mini-panels under three irradiance levels and two 50%-area partial-shading geometries. In the primary dataset, partial shading reduced mean relative irradiance-normalized power, R _P , by approximately 73% and 83% for the two modules, and R _I,G was strongly associated with R _P ( r = 0.983, R ² = 0.966, slope = 0.967). The additional dataset reproduced this relationship in Test 1 ( r = 0.987, R ² = 0.974, slope = 1.021) and Test 3 ( r = 0.998, R ² = 0.997, slope = 1.006); attenuated/shaded-only subsets remained strongly correlated. Over the broader Test-1 irradiance range, R _I,G also outperformed the irradiance-unadjusted ratio R _I in R ² and RMSE. The illustrative threshold R _I,G = 0.5 remains dataset-specific and is not proposed as universal. Overall, R _I,G provides a simple, dimensionless, and physically interpretable current-collapse metric whose continuous current-power relationship transfers to additional PV hardware and operating conditions.

Urban heat stress is intensifying under climate change, particularly in outdoor public spaces where conventional mechanical cooling is impractical. This study develops a climate-driven, system-level numerical framework to evaluate the pre-deployment feasibility of modular, solar-powered spray cooling canopies across 110 cities in Türkiye. Hourly Typical Meteorological Year (TMYx) weather files, representing a single typical year constructed from 2009 to 2023 source data, are used to estimate photovoltaic (PV) energy yield, electrical load, feasible misting duration, water demand, and PV-to-load autonomy under summer daytime conditions. The misting operation is governed by a rule-based adaptive control strategy based on air temperature, relative humidity, and plane-of-array irradiance. To support transferable comparison, the cities are classified into six summer climate-archetype zones using k-means clustering of standardized climate variables, including temperature, humidity, irradiance, wind speed, and summer precipitation. Results show that evaporative cooling feasibility is governed primarily by humidity rather than temperature alone. Hot–Dry Inland cities exhibit the longest mean misting duration (501.90 h) and highest water demand (30,152 L per module), but the lowest PV-to-load autonomy ratio (1.55) because of high pump-driven electrical demand. In contrast, Humid Black Sea cities show minimal misting duration (11.43 h) and water use (465 L per module), but the highest autonomy ratio (39.68) due to very limited system activation. Thus, high autonomy does not necessarily indicate high cooling usefulness. The proposed framework provides a reproducible screening tool for identifying where PV-powered spray cooling canopies are climatically suitable, where water and PV sizing become limiting, and where alternative outdoor heat-mitigation strategies may be more appropriate.

This research examines how climate change intensifies urban heat stress, particularly in public spaces where mechanical cooling is impractical. A climate-driven, systems-level numerical model is developed to evaluate the pre-installation feasibility of portable, solar-powered misting canopies. Hourly Typical Meteorological Year data (TMYx, 2009–2023) are analyzed for each city to estimate photovoltaic (PV) energy yield, electrical load, potential misting duration, water demand, and PV-to-load autonomy under summer daytime conditions. Misting operation is governed by an adaptive, rule-based control strategy based on air temperature, relative humidity, and solar radiation. To enable systematic comparison, K-means clustering is applied to classify the cities into six archetypal summer climate zones. Results indicate that evaporative cooling feasibility is driven more by ambient humidity than by air temperature. Hot-dry interior cities achieve the longest average misting duration (502.65 hours) and highest water consumption (30,486 L per module), but exhibit the lowest PV-to-load autonomy ratio (1.53) due to high energy demand for pumping. In contrast, humid Black Sea cities show minimal misting duration (13.11 hours) and water use (478 L) yet achieve the highest autonomy (40.91) because of limited system operation. It is important to note that the autonomy ratio reflects a seasonal energy balance rather than continuous off-grid capability. Overall, the adaptive control approach effectively aligns water and energy use with climatic suitability across all clusters. The proposed framework offers a scalable and quantitative screening tool to inform the design and deployment of PV-powered outdoor cooling systems across diverse urban environments.

This study evaluates the proton radiation shielding efficacy of various materials, with a focus on ALON, for satellite solar arrays in LEO across the 0.1-200 MeV energy range using SRIM/TRIM simulations. Key metrics, ion penetration, vacancies per ion, range, displacements per atom, non-ionizing energy loss, Bragg curves, and transmission, were analyzed for aluminum, SiO2, polyimide, ALON, and Ta2O5/Al2O3 at thicknesses from 0.01 mm to 4 mm. ALON demonstrates moderate stopping power and damage resistance, with penetration exceeding 20 µm and 100 µm at 0.5 MeV and 5 MeV, respectively, and 2000 µm and 4000 µm providing protection up to 50 MeV and 100 MeV, while maintaining high optical clarity (>80%) for photovoltaic (PV) applications. Thinner layers mitigate high-energy proton damage but are vulnerable to low-energy (

Lithium-ion batteries are critical for modern energy storage systems, yet their capacity degradation under high temperatures remains a significant challenge. This study investigates the long-term capacity fade of lithium-ion batteries subjected to a consistent high-temperature environment using spline regression to model non-linear degradation trends. Utilizing the Oxford Battery Degradation Dataset, eight lithium-ion pouch cells were analyzed over extended cycles, and complex degradation behaviors and temperature-induced capacity losses were measured. Results demonstrated a strong correlation between elevated temperatures and accelerated degradation, with spline regression achieving near-perfect fits (R² = 1.0000) to the observed data, highlighting its efficacy in modeling non-linear fade patterns. The analysis revealed uniform degradation trends across cells, with minor variations attributed to manufacturing inconsistencies. Temperature profiles during initial cycles underscored the role of thermal dynamics in accelerating side reactions like lithium plating and Solid Electrolyte Interface (SEI) growth. These findings emphasize the necessity of robust thermal management systems to mitigate degradation and extend battery lifespan. The study provides actionable insights for optimizing battery design and management strategies in high-temperature applications, such as electric vehicles and grid storage.

This study investigates the feasibility and economic viability of off-grid photovoltaic systems in the Mediterranean region, specifically focusing on a detached house located in Üçoluk Plateau, Antalya Province. The research employs dual simulation software, PVSyst and Homer Pro, to model and analyze the PV system's performance and cost effectiveness. The designed system incorporates a PV panel, battery storage, and an inverter, facilitating energy generation and storage to enhance reliability during periods of low solar radiation. The findings underscore the importance of energy storage solutions in off-grid applications and demonstrate that the proposed system can significantly reduce energy costs while minimizing greenhouse gas emissions. Overall, this study advocates for the adoption of PV systems as a sustainable and economically advantageous energy source in regions with high solar potential, highlighting their role in promoting renewable energy initiatives and supporting environmental sustainability goals.

Concentrated Photovoltaic‑Thermal (CPVT) systems combine concentrated photovoltaics and thermal energy recovery. This lets them produce electricity and heat from sunlight at the same time. This paper looks at the latest progress in optical concentrators, thermal management methods, and spectral beam splitting techniques. These advances have boosted the system’s overall efficiency to between 60% and 80% under different operating conditions. Particular attention is given to Linear Fresnel Reflectors (LFRs), thermal‑fluid simulations, and the use of artificial intelligence (AI) to improve system design and performance. Modeling methods, such as computational fluid dynamics and ray tracing, are examined to connect theoretical expectations with actual experimental data. The discussion includes major obstacles, like the systems’ reliance on high direct normal irradiance (DNI) and their comparatively high initial expenses. Policy changes that could encourage broader use are suggested. Unlike earlier studies, this review incorporates research from 2024–2025 on AI‑driven controls, hybrid energy storage solutions, and strategies for functioning in areas with low DNI. A meta‑analysis is offered, showing how these changes can lower the levelized cost of electricity (LCoE) to between $0.08 and $0.15 per kilowatt‑hour. The article concludes by exploring potential future research areas, such as creating scalable hybrid systems that can support sustainable energy grids. These developments are aimed at assisting the transition toward energy infrastructures with lower carbon emissions.