Search Results (152)

This paper presents an experimental comparison of the instantaneous power generation of standard and bifacial photovoltaic modules under real operating conditions. The study focuses on short-term effects caused by spatially variable albedo and tracker-induced changes in module orientation. Both modules were installed on the same mobile single-axis tracking platform and had identical rated front-side power, which ensured nearly identical operating conditions and independent MPPT operation. The experimental campaign included five ground surfaces: grass, river sand, grey paver, light aggregate, and dark aggregate. For each surface, electrical parameters and albedo were recorded over the full investigated geometrical range, covering relative solar azimuth from −60° to +60° and module tilt from 0° to 90°. The measured increase in power generation of the bifacial module relative to the standard module depended strongly on the ground surface. Over the full investigated range, the gain was 6.4% for grass, 11.3% for river sand, 5.9% for grey paver, 13.6% for light aggregate, and 4.5% for dark aggregate. These results confirm that, in bifacial photovoltaic systems with tracking, the ground surface and its reflective properties significantly affect the rear-side contribution and instantaneous power output. Consequently, albedo should not be treated as a constant or spatially homogeneous parameter when assessing short-term bifacial PV performance. Full article

This paper aims to evaluate the eco-profile of a building-integrated concentrating photovoltaic system (photovoltaic-cell electrical efficiency: 21.6%; geometrical concentration ratio: 12.5×), extending previous work on the design and energetic/optical performance of this system (University of Lleida, Spain). There is a lack of studies on the eco-profile of these technologies; for this reason, this study is based on environmental life cycle assessment (case study: a building in Barcelona; tools: SimaPro/ecoinvent, inventory-of-carbon-and-energy). Focusing on global warming potential and cumulative energy demand, the impacts range from 341 to 507 kg CO_2.eq/m² and from 5660 to 7505 MJ_prim/m². Energy and greenhouse-gas payback times vary between 2.5 and 6.7 years and are shorter than the useful life of this energy-generating element (pessimistic scenario: 15 years). Avoided-impact calculations have also been performed, verifying the benefits of this system during the use phase. Overall, the results are comparable to those of traditional photovoltaic systems. The additional advantage of the proposed modules is that they serve as an atrium and offer illumination, successfully combining the benefits of concentrating photovoltaics (high efficiency; reduction in the amount of solar-cell material required), two optical media (achromatic doublets), hexagonal solar concentrators (high packing efficiency) and micro-tracking (overcoming limitations of bulky external trackers). Full article

The photovoltaic (PV) sector is at present one of the crucial components of renewable power engineering and one of the key pillars in the global power system transformation. This article compares the annual energy yields from real-life PV installations built in Częstochowa (Poland)—three stationary PV installations and one tracker PV installation. The PV installations are located within a 2 km radius, and except for very early morning and late evening hours, there is no shading, thus identical solar exposure conditions can be assumed for all analyzed PV installations. In the case of stationary PV installations, maximum energy production may be achieved if the PV modules are southward oriented and related to their tilt angles. In the case of installations on buildings, PV modules are rarely installed in their optimal orientation. Most often, the orientation of PV modules is directly related to the location of the building and the geometric structure of the roof. A tracking system, which involves mounting PV modules on platforms that track the sun’s path, increases energy yield per module power. Limitations for tracking PV systems include the requirement for adequate, shade-free space for their construction as well as high costs of the structure itself and its maintenance. During the period analyzed (2022–2025), no PV system outages resulting from exceeding the permissible voltage in the distribution network were recorded. The energy produced by individual PV systems was also compared with the values calculated in a simulation program used to estimate annual energy yields during the system design phase. Full article

To investigate the wind-induced vibration of a single-axis solar tracker, this study employs a combination of rigid model pressure measurement wind tunnel tests and finite element calculations. This study addresses the critical gap of full-array wind-induced response analysis and provides region-specific dynamic amplification factor recommendations applicable to comparable tracker configurations. The wind load distribution on the solar tracker surface is obtained through rigid model pressure measurement tests; the natural frequency and mode of the solar tracker are determined via finite element calculations; and the wind-induced response of the solar tracker is computed by integrating the wind load and its self-vibration characteristics. At small tilt angles, a shielding effect is observed, with the wake region exhibiting a lower standard deviation of the torque coefficient than the windward region, whereas at large tilt angles, an amplification effect is observed, with the wake region exhibiting a higher standard deviation. The wind-induced vibration of the solar tracker is predominantly characterized by torsional vibration around the main axis, with larger torsional displacements observed in the end regions and the area between the two drive posts. Furthermore, recommended dynamic amplification factors are provided: 2.07~2.41 for the corner regions, 1.85~1.92 for the mid-span regions, and 1.98~2.23 for the end regions. Full article

Smart power management practices are needed for a sustainable EV charging infrastructure due to the fast use of renewable energy resources. An innovative power management structure for a small grid-connected solar PV system-based AC and DC charging station, combined with a backup purpose battery energy system (BESS), is demonstrated in this paper’s study. The sustainability transition is associated with integrating renewable energy resources with a battery storage system, providing a helpful solution for managing large power-demanding entities (EV, microgrid, etc.). In this study, a solar PV system takes 500 datasets (based on data availability or to prevent overfitting) of PV voltage, solar irradiance, and air temperature, and the performance of controlling for the maximum power point tracker by training these datasets using Levenberg–Marquardt (LM), which was implemented in the ANN toolbox and created this technique in MATLAB 2016 or Simulink. Also, using this technique for the estimation and forecasting of the datasets of solar PV systems and EVs obtains better results for achieving further targets. To enhance decision-making capability through optimized technique, we have to find it before forecasting PV power generation and EV datasets throughout the day (24 h). The optimized power flows among solar PV power generation, EV charging demand (including AC charging and DC fast charging), the BESS, and the utility/small grid under several priority operating scenarios. A famous technique for optimization, mixed-integer linear programming (MILP), is applied. In this technique, the objective function is used for the solution of problem formation and compliance with system constraints such as the power balancing equation, charging/discharging limits, SOC limits, and grid export/import exchange limits: basically, equality, inequality, and bounds limits. Optimized results show that the coordinated power flow operations are consented to by EV users, by prioritizing some key points, such as solar PV use at the maximum, reducing the grid power dependency, and the first power flow towards EV charging demand. The verified MILP-based solutions boost the maximum utilization of renewable energy resources, feasible EV charging demand, and scaling power flow among these entities. The key contribution of this study is suitable for different powered EV charging stations based on both AC and DC, with different ratings of EVs (including fast and slow charging). Most solar PV-based generation supports the EVCS and backup for ranking-wise BESS, and grid support for the EVCS. Also, the key contribution of hybrid techniques in this article is divided into two stages: in the first stage, an artificial neural network (ANN) is utilized for estimating the PV voltage at the maximum point and forecasting, while in the second stage, mixed-integer linear programming (MILP) employs optimal power management. Full article

Agrivoltaics offer a sustainable solution to the growing competition between food and energy production. However, their adoption is often constrained by the design and operation challenges associated with optimising the complex trade-off between crop yield and photovoltaic (PV) output. Digital twins can mitigate these risks, yet most agricultural digital twins operate as fragmented digital shadows, lacking high-fidelity modelling, advanced simulation, and bidirectional control capabilities. This study presents a comprehensive, end-to-end digital twin framework to address these limitations. The framework integrates a high-resolution 3D orchard model, reconstructed via UAV photogrammetry, with a CesiumJS-based web interface linked to a modular IoT architecture built on Node-RED, Message Queuing Telemetry Transport (MQTT) protocol and InfluxDB for real-time monitoring and control. A PV simulation engine supports the design, simulation and optimisation of agrivoltaic systems. Bidirectional communication was validated through remote actuation of a physical solar tracker, demonstrating integration among the 3D environment, sensor data and control systems to achieve a closed-loop digital twin. Simulation analyses suggested that panel orientation and row spacing exert a dominant influence on crop-level light distribution. Simulation results demonstrated that a 90° azimuth configuration achieved the highest daily energy yield of 53.97 kWh but reduced peak crop-level irradiance to 205 W/m². In contrast, the baseline 0° configuration offered a balanced output of 40.86 kWh with a peak light availability of 338 W/m². The validated, interoperable digital twin architecture provides a reference model for the design, simulation, monitoring and control of an agrivoltaic system, reducing investment uncertainty and supporting sustainable food–energy co-production. Full article

As the global energy transition accelerates toward low-emission and sustainable industrial energy systems, green hydrogen produced from renewable sources has emerged as a promising alternative to natural gas in energy-intensive sectors. This study presents the design, implementation, and experimental validation of a rooftop photovoltaic–proton exchange membrane (PV–PEM) hydrogen energy system developed as a proof-of-concept for textile industry applications. The proposed system integrates monocrystalline photovoltaic panels with east–west solar tracking, a 4 kW inverter, and a PEM electrolyzer with a hydrogen production capacity of 3.6 L/h, enabling on-site solar-to-hydrogen conversion. Produced hydrogen is stored in a high-pressure metal tank and utilized for downstream energy applications, demonstrating a complete renewable energy pathway. System performance is monitored in real time and evaluated using an experimental methodology supported by GUM-based and Monte Carlo uncertainty analysis. A carbon reduction assessment is conducted under representative industrial operating scenarios, including uncertainty quantification. The results indicate that the prototype system achieves an energy output corresponding to an average monthly emission reduction of approximately 222 kg CO₂e. The modular and scalable architecture allows flexible expansion to support gradual natural gas substitution in textile processes such as drying, heating, and steam generation. Overall, the study demonstrates the technical feasibility and environmental potential of integrating rooftop PV–PEM hydrogen systems into textile manufacturing, providing a transferable framework for industrial decarbonization. Full article

Single-axis solar tracking maximizes photovoltaic energy production under clear-sky conditions; however, its effectiveness decreases under cloudy and overcast skies, where diffuse irradiance dominates and the optimal module orientation changes. Conventional tracking algorithms either neglect sky conditions or rely on simplified diffuse-response strategies that may trigger frequent tracker repositioning under variable cloud cover, leading to increased mechanical wear with marginal energy gains. This work proposes an enhanced diffuse-response tracking algorithm that explicitly accounts for both the intensity and temporal persistence of cloudiness. By requiring overcast conditions to persist for a minimum duration before reorienting the tracker to a diffuse-stow position, the proposed approach reduces unnecessary movements while preserving the benefits of diffuse-response operation. The algorithm is evaluated through numerical simulations based on historical meteorological data and validated using field measurements on monofacial and bifacial photovoltaic strings. The results show that the proposed strategy reduces excess tracker movement from 114% to 0.16% while maintaining nearly the same energy yield. Compared to a conventional diffuse-response algorithm, the associated energy reduction is minimal (≈0.17%) relative to the ≈0.37% yield gain observed at the studied location. These findings demonstrate that incorporating cloudiness duration enables a practical compromise between energy performance and tracker durability, particularly for monofacial photovoltaic systems. Full article

Solar energy is a widely available renewable source suitable for diverse applications, including residential, industrial and aerospace sectors. To maximize energy capture, solar tracking systems adjust panels to maintain perpendicular alignment with sunlight. Various tracking techniques are employed to adjust these trackers, such as sensors, predefined algorithms, deep learning, and image-processing techniques. Image processing-based trackers have gained prominence for their precision and accuracy. This approach uses cameras as sensors to capture real-time sky images and analyze them to detect the sun and its coordinates, orienting solar panels toward its center. This technology can be integrated with other techniques to enhance energy output with high accuracy, minimal tracking error, and low maintenance requirements. This review examines computer vision methods used in solar tracking systems, synthesizing findings from 26 studies published between 2009 and 2024. The paper discusses main system components, methods utilized, and results obtained. Findings demonstrate that the robustness and accuracy of these tracking systems have increased compared to other tracking systems, while tracking error has decreased. Full article

In grid-connected photovoltaic systems, improving power quality is necessary for assuring constant energy delivery, consistent voltages, and current, as well as being compliant with the standards of the grid. Yet, today’s PV control systems have to deal with serious problems, for example, slow MPPT reactions to changes in irradiation, significant harmonic distortion, weak reaction to voltage changes, and being unable to adapt well to different situations. For this reason, these problems lead to less efficient electricity, unstable connections to the power grid, and an altered quality of electricity, as solar power and load levels vary in real conditions. A way to solve these problems is introduced in this paper: (1) the Hippopotamus-based Solar Power MPPT Tracker and (2) a SyBel embedded controller for controlling the inverter. This kind of optimization mimics nature to control the duty cycle and enables the boost converter to deliver maximum power while responding quickly and maintaining accurate tracking. Meanwhile, the SyBel controller makes use of a hybrid technique by using SNN, DBN, and synergetic logic to sensibly manage the inverter switches and increase the power quality. The framework is novel because it uses biological optimization plus deep learning-based embedded control to instantly handle error reduction and harmonic suppression. The whole process records energy from solar panels, follows the maximum power point, changes its schedule as needed, and uses sophisticated controls in the inverter. We found that the proposed MPPT tracker achieves an impressive tracking efficiency of 98.6%, surpassing PSO, FLC, and ANFIS, and lowering the time required for tracking by 72%. The SyBel inverter controller provides outstanding results, keeping the voltage THD at 1.2% and current THD at 1.3%, which matches power quality standards. Full article

The sun tracker plays a major role in improving the energy efficiency of a solar power system. To address this role, this study experimentally explores the energy efficiency of three sun-tracking systems with three types of degrees of freedom (DOFs)—namely, single-axis for both elevation (1DOF_Elev) and azimuth (1DOF_Azim), and dual-axis (2DOF)—integrated in photovoltaic (PV) panels. The three sun-tracking configurations are assessed and compared with the fixed system (0DOF), considering both the net electricity output of the studied photovoltaic system and the energy consumption of each configuration during operation. To accomplish this objective, hardware and software tools were deployed to create a prototype. The sun-tracking techniques are based on the sun position algorithm (astronomical calculations). The different data (time, voltage, current, power, azimuth, and elevation) are stored in real time within a locally developed database which represents crucial data within SCADA systems embedded in smart grids. The results revealed that the 2DOF system exhibits the highest energy efficiency (37.23%), followed by 1DOF_Azim (12.86%), and then by 1DOF_Elev (10.05%), when compared to 0DOF. Overall, this study provides solutions for optimizing photovoltaic energy production and could be integrated into battery-powered devices to accelerate battery recharging, achieving time savings of over 30%. Full article

Hybrid PV-TEG systems can harvest both solar electrical and thermoelectric power, but their operating point drifts with irradiance, temperature gradients, partial shading, and load changes—often yielding multi-peak P-V characteristics. Conventional MPPT (e.g., P&O) and fixed-structure integer-order PID struggle to remain fast, stable, and globally optimal in these conditions. To address fast, robust tracking in these conditions, we propose an adaptive fractional-order PID (FOPID) MPPT whose parameters (K_p, K_i, K_d, λ, μ) are auto-tuned by the red-billed blue magpie optimizer (RBBMO). RBBMO is used offline to set the controller’s search ranges and weighting; the adaptive law then refines the gains online from the measured ΔV, ΔI slope error to maximize the hybrid PV-TEG output. The method is validated in MATLAB R2024b/Simulink 2024b, on a boost-converter–interfaced PV-TEG using five testbeds: (i) start-up/search, (ii) stepwise irradiance, (iii) partial shading with multiple local peaks, (iv) load steps, and (v) field-measured irradiance/temperature from Shanxi Province for spring/summer/autumn/winter. Compared with AOS, PSO, MFO, SSA, GHO, RSA, AOA, and P&O, the proposed tracker is consistently the fastest and most energy-efficient: 0.06 s to reach 95% MPP and 0.12 s settling at start-up with 1950 W·s harvested (vs. 1910 W·s AOS, 1880 W·s PSO, 200 W·s P&O). Under stepwise irradiance, it delivers 0.95–0.98 kJ at t = 1 s and under partial shading, 1.95–2.00 kJ, both with ±1% steady ripple. Daily field energies reach 0.88 × 10⁻³, 2.95 × 10⁻³, 2.90 × 10⁻³, 1.55 × 10⁻³ kWh in spring–winter, outperforming the best baselines by 3–10% and P&O by 20–30%. Robustness tests show only 2.74% power derating across 0–40 °C and low variability (Δv^max typically ≤ 1–1.5%), confirming rapid, low-ripple tracking with superior energy yield. Finally, the RBBMO-tuned adaptive FOPID offers a superior efficiency–stability trade-off and robust GMPP tracking across all five cases, with modest computational overhead. Full article

This paper investigates the reliability of a dual-axis solar tracking system using Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and Reliability Block Diagrams (RBD). The system’s control and data transfer subsystems are evaluated under indoor and outdoor conditions using failure rate data. Key vulnerabilities—particularly sensor degradation—are modeled through probabilistic analysis. Results show a significant drop in reliability (to 15.02%) in harsh environments, primarily due to light sensor failures. However, mitigation strategies such as Built-In Self-Test (BIST) architectures improve test coverage, thereby increasing the chance of fault detection. The findings highlight the need for reliability-focused design in solar trackers to ensure long-term energy efficiency and fault resilience. Full article

The transition to sustainable electricity grids, particularly in countries with high renewable potential, such as Brazil, requires integrated assessments of hybrid and single-source configurations. This study analyzed the technical and economic feasibility of hybrid plants and isolated wind and solar systems in the Brazilian Northeast, focusing on Macaíba (RN) and Casa Nova (BA), regions characterized by high resource availability. The work addresses a gap in the literature by integrating detailed technical modeling and financial analysis of hybrid configurations, considering both local and operational constraints. Hourly simulations were performed using the HyDesign software (v1.1.0), with optimization based on the ratio between net present value (NPV) and invested capital (CAPEX), covering seven different scenarios by location, including hybrid combinations and systems with solar trackers. The results indicated that systems with solar tracking achieved superior economic performance. In Macaíba, the optimal configuration was the hybrid scenario with trackers, which increased the NPV/CAPEX by 27.69% compared to the relevant baseline. In Casa Nova, the best solution was the pure solar plant with trackers, which increased the NPV/CAPEX by 50.0% compared to fixed solar. Hybridization showed moderate gains in scenarios without tracking. It is concluded that while solar trackers are highly beneficial, the optimal plant configuration (pure solar or hybrid) is site-specific and depends on the local renewable resource profile. Notably, battery storage was not economically justified under the evaluated cost assumptions. The study contributes to the planning of renewable projects in contexts of high source complementarity. Full article

The main objective of this paper is to develop a maximum power point tracker (MPPT) for a photovoltaic module array (PVMA) under conditions of partial shading and sudden changes in solar irradiance. PVMAs exhibit nonlinear characteristics with respect to temperature and solar irradiance conditions. Therefore, when some modules in the array are shaded or when there is a sudden change in solar irradiance, the maximum power point (MPP) of the array will also change, and the power–voltage (P-V) characteristic curve may exhibit multiple peaks. Under such conditions, if the tracking algorithm employs a fixed step size, the time required to reach the MPP may be significantly prolonged, potentially causing the tracker to converge on a local maximum power point (LMPP). To address the issues mentioned above, this paper proposes a novel MPPT technique based on the nature-inspired idols algorithm (IA). The technique allows the promotion value (PM) to be adjusted through the anti-fans weight (afw) in the iteration formula, thereby achieving global maximum power point (GMPP) tracking for PVMAs. To verify the effectiveness of the proposed algorithm, a model of a 4-series–3-parallel PVMA was first established using MATLAB (2024b version) software under both non-shading and partial shading conditions. The voltage and current of the PVMAs were fed back, and the IA was then applied for GMPP tracking. The simulation results demonstrate that the IA proposed in this study outperforms existing MPPT techniques, such as particle swarm optimization (PSO), cat swarm optimization (CSO), and the bat algorithm (BA), in terms of tracking speed, dynamic response, and steady-state performance, especially when the array is subjected to varying shading ratios and sudden changes in solar irradiance. Full article