This study is motivated by the need to identify cost-effective and efficient pathways for solar-driven hydrogen production, as existing analyses often assess individual technologies in isolation and lack consistent comparative frameworks. Direct comparisons between thermal-based and photon-based hydrogen production systems under unified modeling assumptions and cost uncertainty remain limited. Thus, this study conducts a techno-economic comparison and multi-objective optimization of two solar-based hydrogen production pathways: (1) a concentrated solar power (CSP) system integrated with a supercritical CO2 (sCO(2)) Brayton cycle and a copper-chlorine (Cu-Cl) thermochemical cycle and (2) a photovoltaic (PV) system coupled with a polymer electrolyte membrane (PEM) electrolyzer. Two CSP receiver configurations, particle-based and gas-based, are evaluated to assess the influence on system performance. A multi-objective optimization framework using the nondominated sorting genetic algorithm II (NSGA-II) algorithm is applied to minimize the levelized cost of electricity (LCOE) and hydrogen (LCOH2) while maximizing system efficiency. Cost uncertainty is addressed using Latin hypercube sampling (LHS) with AACE class-5 uncertainty ranges. Results based on mean values from the uncertainty analysis show that the optimized particle-based CSP system achieved LCOH2 of $4.13/kg (5th-95th percentile: $2.39-5.87/kg) and LCOE of $0.064/kW h ($0.059-0.069/kW h), with an efficiency of 19.8%. The gas-based CSP system yields LCOH2 of $4.87/kg ($2.93-6.80/kg) and LCOE of $0.091/kW h ($0.074-0.11/kW h), with an efficiency of 20.6%. In contrast, the optimized PV-PEM system exhibits a higher LCOH2 of $6.34/kg ($5.58-7.08/kg) and a lower efficiency of 9.6%. These findings indicate that CSP-based cogeneration systems, particularly particle-receiver configurations, offer competitive hydrogen costs and higher solar-to-useful energy efficiency when uncertainty is considered.
This study addresses the techno-economic optimization of grid-connected hybrid renewable energy systems for commercial applications in Tunisia, a sun-rich developing nation facing high diesel dependency and severe summer peak demand. A nonlinear optimization model co-optimizes component sizing and hourly dispatch over a 20-year horizon under Tunisian conditions, including 2100 kWh/m(2)/year solar irradiance, a diesel fuel cost of $1.50/L, explicit carbon pricing of $0.15/kg CO2, and time-of-use grid tariffs. The optimized system selects 150 kW of photovoltaic (PV) and a 200 kWh battery, achieving a 57.1% PV contribution, 40.5% diesel generation, and 2.4% grid imports, with a total lifecycle cost of $610,424, a payback period of 3 years, and annual CO2 emissions of 89,074 kg CO2. Diesel fuel price emerges as the dominant lifecycle cost driver, with discount rate ranking second, underscoring the importance of financing conditions alongside fuel cost management in emerging markets. The novelty of this work lies in proposing a unified optimization framework that simultaneously integrates four high-fidelity elements under Tunisian economic constraints, including nonlinear diesel efficiency modeling, state-of-charge-dependent battery degradation, explicit carbon pricing, and time-of-use grid tariffs, whereas prior studies typically address these factors in isolation. The objectives are twofold: first to quantify cost-optimal sizing and dispatch for PV-diesel-battery-grid systems; and second to identify actionable policy thresholds that shift systems toward decarbonization without compromising reliability.
Generation 3 concentrating solar power (CSP) systems use solid particles for heat transfer and thermal energy storage. Particle-based systems can use a falling particle receiver with an open cavity that allows particles to flow together as a curtain. The particle curtain is directly exposed to solar radiation, which is absorbed by the particles as they descend through the receiver. The efficiency of the particle receiver depends on curtain opacity (which is influenced by the mass flowrate of the particles), the average particle temperature, and environmental factors like wind. This research presents a free-falling particle receiver with optimized particle supply management facilitated by ten individually controlled valves. Each valve is equipped with a slide gate and an actuator, ensuring a consistent mass flowrate for a segment of the curtain. In a uniform mass flowrate curtain, the hottest particles accumulate in the center due to non-uniform flux distribution, which leads to higher radiative and advective losses. Accordingly, lower flux levels at the periphery of the curtain result in lower temperature particles. The modular valve design described here improves the solar receiver efficiency and varies the particle curtain opacity in key areas to prevent back wall overheating and improve serviceability. The outer valves have the lowest mass flowrate, while the valves near the center have the highest, allowing for a more uniform heating of the particle curtain. Engineering equation solver is used to analyze the efficiency and performance of the falling particle receiver. The performance of the receiver is optimized by adjusting the mass flowrate in each curtain section. The study aims to determine the ideal mass flowrate for each of the particle curtain valves to augment receiver performance and evaluate back wall temperature under different input flux conditions.
This study proposes an improved Sun tracking system to increase the efficiency of solar energy collection by aligning solar panels with the Sun's position. The proposed system applies image processing at the initial stage with the guided box filter (GBF) for image smoothing, noise removal, and detail reduction. A continuous feedback process is implemented for dynamic adjustment with hesitant fuzzy linguistic bi-objective clustering for image segmentation, followed by the modified circle Hough transform (MCHT) for precise circle detection and distance calculation. Numerical experiments demonstrate the system's capability to track the Sun with high accuracy at different distances. At a distance of 2.39 m between the Sun and the image center, the tracking error is negligible with a minimum altitude error of 0.4 and azimuth error of 0.5. Under normal circumstances, the system performs excellently with an altitude error of 0.15 and azimuth error of 0.25. At a distance of 0.06 m, which is close to zero, the altitude error is remarkably low at 0.15. The tracking accuracy and efficiency metrics, which were reported in the study, were obtained through image-based simulations that used processed sky images and controlled offsets instead of testing the system on actual solar panels in the field. The combination of high-quality image processing techniques and fuzzy control mechanisms provides a guaranteed way of maximizing the harvesting of solar energy, which plays a significant role in the development of renewable energy technologies.
In a parabolic trough collector (PTC), the absorber tube is subjected to substantial temperature nonuniformity due to the concentrated solar flux, resulting in thermal stresses, strains, and high failure rates, particularly in solar-based concentrated plants operating with liquid heat transfer fluids. Most failures occur from glass envelope rupture under intense thermal stress. To address this, the present study numerically analyzes the thermo-fluid and structural behavior of a PTC's absorber tube employing a gaseous heat transfer fluid. Among the gases analyzed, carbon dioxide, air, and methane, methane exhibited the highest performance improvement. High circumferential temperature gradients cause structural deflections, especially beyond 6 m of tube length, with a maximum deflection of 6.36 mm at around 7.48 m. The substitution of stainless steel with copper markedly improves structural performance, resulting in reductions of up to 87.43% in deflection, 88.39% in stress, and 79.70% in strain. Lastly, a comparison is performed to evaluate the performance of absorber tubes with and without longitudinal rectangular fins.
