Search Results (878)

Owing to its inherent flight safety, low takeoff and landing requirements, and favorable economic efficiency, the autogyro UAV, especially its electric and hybrid-electric variants, has become a core platform for low-altitude aviation missions such as transportation, inspection, and surveillance in plateau and offshore regions. However, the low air density and low Reynolds number conditions encountered in plateau regions can induce aerodynamic issues such as premature laminar flow separation, dynamic stall, and increased induced drag, which directly reduce payload capacity and endurance of small electric autogyro UAVs. In offshore environments, strong winds, turbulence, and gust disturbances intensify rotor–wake interactions, cause abrupt variations in aerodynamic loads, and reduce control margins, which severely restricts the mission reliability and flight safety of low-altitude unmanned platforms. These environmental effects collectively degrade rotor performance, including reduced aerodynamic efficiency and insufficient lift generation, and further amplify the energy constraint of electric/hybrid-electric propulsion systems. In response to bottlenecks that restrict the practical application of autogyro UAVs in extreme environments, this paper systematically reviews research progress on lift vector control for autogyro UAV rotors operating under such conditions. First, the typical aerodynamic problems encountered by autogyro UAVs in plateau and offshore environments are summarized, and their underlying physical mechanisms are analyzed from both system-level and local-flow perspectives, with a focus on how environmental factors affect the autorotation stability of unmanned platforms. Subsequently, the development of passive lift vector control technologies is reviewed, with an emphasis on the aerodynamic benefits of passive pitch mechanisms, vortex generators, and blade-tip winglets, as well as their engineering feasibility for small autogyro UAV blades. Active lift vector control technologies are then examined, including air-jet flow control, synthetic jets, and trailing-edge flaps, with discussions of their potential to delay flow separation and stall, enhance rotor aerodynamic efficiency, and an assessment of their adaptability to the energy and structural constraints of unmanned platforms. Finally, a lift vector control strategy suitable for autorotating rotors of autogyro UAVs is proposed, based on careful consideration of energy consumption, structural constraints, and control effectiveness. It provides a reference for aerodynamic optimization and flight control research on electric and hybrid-electric autogyro UAVs operating in extremely low-altitude environments. Full article

Accurate detection of surface defects in wind turbine blades is critical for condition monitoring and preventive maintenance of wind energy systems. Defects such as cracks, burns, deformation, and peeling are characterized by small dimensions, irregular morphologies, and low contrast, limiting the effectiveness of conventional feature extraction methods. Although YOLOv13 enhances high-order feature correlation and information flow, its fixed-grid spatial sampling and content-agnostic upsampling operations remain limited in adapting to irregular defect geometries and preserving fine-grained boundary information. This study proposes YOLOv13-ADR, an enhanced detection framework integrating Adaptive Deformable Convolution (ADConv) and a Nearest Neighbor Content Perception Recombination (NNCPR) module. ADConv applies a geometry-driven kernel permutation strategy to strengthen multi-scale feature representation, while NNCPR improves neighborhood-aware perception for modeling geometric deformations. A Focus-IoU loss function incorporating an anchor-quality perception mechanism is introduced to accelerate training convergence and improve bounding box regression precision. Additional optimizations include modifications to the DS-C3k2 module and upsampling strategy. Experiments on a wind turbine blade defect dataset demonstrate that YOLOv13-ADR achieves a 7.26-percentage-point improvement in mean average precision over YOLOv8n, with enhanced small-defect recognition and reduced localization errors, demonstrating improved detection precision and localization performance relevant to early fault detection and structural health monitoring of wind turbine blades. Full article

This study investigates how offshore wind farm layout geometry influences farm-level performance using a computationally efficient Jensen–Park wake model combined with directionally resolved Weibull wind-speed statistics. A fixed-capacity 1.8 GW case study, consisting of 120 V236-15.0 MW turbines, is used to examine the effects of grid aspect ratio, inter-turbine spacing, cumulative row skew, and global layout rotation on wake losses, annual energy production (AEP), and capacity factor under representative offshore screening assumptions. Structured layouts with identical turbine count and installed capacity are compared with a regular baseline grid to isolate geometric effects within a consistent modelling framework. For the nominal offshore Jensen wake-expansion coefficient, k = 0.04, the highest sampled AEP is obtained for the 5 × 24 configuration, which produces 8930.69 GWh yr⁻¹ and a capacity factor of 56.64%. The regular baseline produces 7397.50 GWh yr⁻¹ and a capacity factor of 46.91%, corresponding to a 20.73% AEP increase for the highest sampled layout. However, the performance differences among Layouts D–F are small, indicating a high-performing layout plateau rather than a clearly separated optimum. The contribution of this paper is therefore not a new wake model, optimisation algorithm, or general offshore design rule. Instead, this study provides an auditable screening workflow that documents modelling assumptions, parameter bounds, coordinate transformations, convergence checks, sensitivity analyses, and spatial-efficiency indicators for one turbine model, one turbine count, one synthetic wind rose, and a limited set of structured row–column layouts. Full article

The increasing integration of distributed photovoltaics and wind power in rural grids necessitates enhanced peak-regulation flexibility, for which small Francis turbines offer a promising solution. This study investigates the effect of long–short blade number on the hydraulic performance and energy losses of a representative rural small Francis turbine under constant runner material usage. Five configurations (N = 13–17) are evaluated using SST-DES-based CFD simulations and entropy production theory. At the rated condition, the N = 15 configuration achieves the highest overall efficiency of 93.65%, exceeding N = 17 by 0.19 percentage points and N = 16 by 0.61 percentage points; at high-flow conditions, it maintains a similar advantage of approximately 0.26 percentage points over N = 17. In the low-flow region, the N = 17 scheme exhibits slightly higher efficiencies, with advantages of 0.85 percentage points over N = 15. The N = 15 scheme demonstrates more uniform velocity streamlines, gentler pressure gradients, and smaller high-entropy-production regions across all flow components, particularly at the rated point. Overall, N = 15 provides the best balance between rated-point performance and off-design stability and is recommended for engineering applications. Full article

Virtual synchronous generator (VSG) control is widely used to improve the frequency stability of low-inertia microgrids. However, most existing adaptive VSG strategies tune the virtual inertia and damping coefficient mainly according to local frequency deviations of the energy storage converter, while the effect of supplementary wind turbine frequency support on the admissible VSG parameter range is rarely considered. To address this limitation, this paper proposes a wind–storage coordinated frequency control strategy that combines an energy storage fuzzy VSG with active-power-frequency droop support from a doubly fed induction generator (DFIG). The scientific contribution of this study is that the DFIG droop support term is incorporated into a reduced-order wind–storage small-signal model, and an admissible scheduling region for the virtual inertia and damping coefficient is constructed according to prescribed damping ratio and natural angular frequency constraints. This region is used to constrain the online fuzzy parameter scheduling of the energy storage VSG. In addition, bell-shaped membership functions are introduced to obtain smoother parameter variation and are compared with triangular membership functions under the same operating conditions. MATLAB/Simulink simulations are conducted under grid-connected/islanded transition, load switching, and renewable-power fluctuation conditions. Compared with the benchmark strategies, the proposed method reduces the maximum and average frequency deviations to 0.181 Hz and 0.016 Hz, respectively. The maximum discharge power, RMS power, and cumulative energy throughput of the energy storage system are reduced to 236.853 kW, 155.822 kW, and 5.751 kWh, respectively. These results indicate that the proposed coordinated strategy improves frequency regulation while reducing the transient regulation burden of the energy storage system within the investigated operating conditions. Full article

This paper investigates the use of a hybrid renewable heat-supply system based on photovoltaic–thermal collectors, an industrial heat pump, thermal energy storage, and electrical energy storage for a small- to medium-scale district-heating network. A dynamic lumped-parameter model was developed and applied to hourly data from an existing network. The photovoltaic–thermal collector model accounts for low-temperature operation, wind effects, precipitation, and condensation-related heat gains, while the heat pump is represented using compressor performance characteristics under variable source and sink temperatures. The analysis focuses on whether the proposed configuration can meet summer heat demand and reduce reliance on a conventional peak or backup source during shoulder periods. The results show that, during an extended non-heating season, the system can supply approximately 90–100% of the district-heating demand while maintaining a daily mean coefficient of performance in the range of approximately 2.0–3.1. The photovoltaic–thermal field and electrical energy storage do not provide full electrical self-sufficiency, but they reduce grid electricity import; in July and August, the electricity autarky coefficient is approximately 48–49%. The results indicate that the proposed system can serve as a seasonal renewable heat source for district heating. Further refinement of the configuration, operating setpoints, and control strategy could improve its shoulder-season performance. Full article

Urban air mobility depends on small aerial vehicles threading through dense, wind-swept cities, yet most sampling-based planners treat the urban wind field as noise to reject rather than structure to exploit—and pay for it in flight energy. We take the opposite view. Behind every building lies a sheltered wake where the air slows and aerodynamic drag drops, and this work turns that physical fact into a planning principle. We present an energy-aware, wind-shadow-aware framework that routes a single quadrotor, at the planning level, through these low-wind corridors. The wind model couples a power-law shear profile with Ekman directional veer and a frozen-turbulence gust component, grounding the planner in realistic boundary-layer physics. A feed-forward neural energy surrogate, trained to approximate a cost field that aggregates wind exposure and obstacle clearance, then guides a two-stage refinement—energy-aware, collision-checked shortcutting followed by Laplacian and energy-guided smoothing—so that every accepted change stays collision-free. Against classical sampling-based baselines (RRT, goal-biased RRT, Informed RRT*, and BIT*) over a 50-run Monte-Carlo study, evaluated with multi-criteria metrics and Pareto-dominance analysis, the framework characterizes how wind-shadow-aware routing balances route energy against smoothness and clearance, offering a reproducible, wind-informed basis for flying robots navigation. Full article

This study develops and experimentally validates a battery-coupled wind–photovoltaic power model for auxiliary electrical supply in small-vessel systems. The prototype integrates a 395 W CS6R-395MS monocrystalline photovoltaic module (CSI Solar Co., Ltd., Suzhou, Jiangsu, China), a 200 W FA200W horizontal-axis wind turbine (VEVOR, Rancho Cucamonga, CA, USA), maximum power point tracking (MPPT) power-conditioning stages, a 24 V/28 Ah AGM VRLA battery bank composed of four BAT212120086 batteries (Victron Energy B.V., Almere, The Netherlands), a 24 V DC bus, and a Phoenix 24/500 pure sine-wave inverter (Victron Energy B.V., Almere, The Netherlands), targeting non-propulsion navigation, communication, and lighting loads on a 5.7 m length overall (LOA) vessel. Field-acquired irradiance, cell temperature, incidence angle, PV voltage, wind speed, and rotor-speed data were used as time-dependent model inputs and compared with synchronized active-power measurements. Across the full 15–24 September 2025 experimental campaign, the maximum absolute relative error remained below 2.69%, while the aggregate statistical validation indices were ME = −0.1041 W, MAE = 0.3988 W, RMSE = 0.4931 W, and MAPE = 0.5946%. For the representative cloud-adverse case study conducted on 21 September 2025, the measured hybrid generation reached $E_{\mathrm{h}\mathrm{y}\mathrm{b}}=611.3 \mathrm{W}\mathrm{h}$ over 8.28 h, corresponding to $C_{\mathrm{R}\mathrm{E}\mathrm{S}}=102.1\%$ of the selected $E_{\mathrm{l}\mathrm{o}\mathrm{a}\mathrm{d}}=599 \mathrm{W}\mathrm{h}/\mathrm{d}\mathrm{a}\mathrm{y}$ auxiliary-load profile and to $C_{\mathrm{h}\mathrm{y}\mathrm{b}+\mathrm{b}\mathrm{a}\mathrm{t}}=158.1\%$ when the usable battery reserve at 50% depth of discharge (DOD) was included. Full article

The main objective of the current study is to assess the techno-economic feasibility, climate change adaptability, and sustainability of photovoltaic energy systems in six large hospitals in Turkey (Adana, Başakşehir, Bursa, Elazig, Gaziantep, and Yozgat) to achieve United Nations recommendations as Sustainable Development Goal 7 (affordable and clean energy) and Sustainable Development Goal 13 (climate action). This study aims to determine the impact of long-term climate change on the availability of photovoltaic (PV) energy resources. To achieve this goal, this research was conducted through a multi-step approach combining (1) the detection of long-term climate trends using linear regression on the TerraClimate database, (2) the spatial analysis of photovoltaic solar energy potential using high-resolution satellite imagery (Google Maps) for roof suitability and parking areas, (3) the estimation of photovoltaic electricity generation and the calculation of the capacity factor, (4) the application of the Response Surface Methodology (RSM) based on NASA Giovanni data to model the nonlinear reciprocal relationships between precipitation (R), aerosol optical thickness (AOT), photovoltaic solar energy production, and (5) the techno-economic analysis using the Levelized energy cost (LCOE), payback period, and CO₂ emission reductions. The results show statistically consistent warming trends across all sites with trends for Tmax ranging from +0.0205 to +0.0268 °C/year and for Tmin from +0.0208 to +0.0300 °C/year. The temperature of PV cells increases at a rate of +0.0197 °C/year and the wind speed decreases by −0.0031 to −0.0149 m/s/year, which indicates a reduction in convective cooling. Solar radiation, on the other hand, is relatively constant with small trends ranging from +0.0002 to +0.0566 W/m²/year, and confirms the consistent solar resource availability. Seasonal PV resource potential varies from ~70–95 W/m² in winter to 290–310 W/m² in summer. Furthermore, the installed PV capacities are between 6 MW (Yozgat) and 47 MW (Başakşehir) with capacity factors of 17.0–19.7% and payback periods of 4.31–4.88 years. RSM models have high explanatory power (R² = 0.57–0.74) with AOT as the most important negative driver of PV performance. Consequently, the results show that while the solar resource of Türkiye is stable and highly exploitable, PV efficiency is increasingly determined by climate-induced thermal stress and reduced wind cooling. The study highlights the economic viability, environmental advantages, and strategic relevance of PV systems at hospitals for resilient, low-carbon healthcare infrastructure in future climate scenarios. Full article

Subsynchronous oscillation (SSO) is a critical stability issue in grid-following direct-drive wind farms connected to weak grids. To mitigate this issue, this paper proposes a phase-shift subsynchronous damping control strategy based on grid-forming energy storage (GF-ES). First, a small-signal state-space model of a grid-connected wind-storage system incorporating GF-ES is established, and eigenvalue analysis is conducted to examine the effects of GF-ES capacity share, virtual synchronous control parameters, and grid strength on the dominant SSO mode. The results show that, under weak-grid conditions, the coupling among point of common coupling (PCC) voltage disturbances, the wind turbine Phase-Locked Loop (PLL), and grid-side current control reduces system damping, causing the dominant SSO mode around 22.1 Hz to exhibit weak or even negative damping. To enhance damping under low-capacity conditions, a phase-shift subsynchronous damping controller (PS-SDC) is designed, and its additional damping voltage signal is superimposed onto the q-axis voltage command of the GF-ES inner current control loop. Eigenvalue analysis shows that, under conventional virtual synchronous generator (VSG)-controlled GF-ES, increasing the GF-ES capacity share from 2% to 20% shifts the dominant SSO eigenvalue from 1.0128 ± j138.8370 to −1.7111 ± j138.8097, and increases the damping ratio from −0.0073 to 0.0123. At the baseline 10% GF-ES capacity share, the proposed PS-SDC further shifts the dominant eigenvalue from −0.4780 ± j138.8223 to −1.5691 ± j138.8224, increasing the damping ratio from 0.0034 to 0.0113. The small-signal stability boundary is also improved from between 6.5% and 10% GF-ES capacity share to between 4% and 6.5%, demonstrating that the proposed PS-SDC provides enhanced damping capability for the 22.1 Hz dominant SSO mode under weak-grid and low-capacity GF-ES conditions. Full article

Supplying shore-side electricity to ships at berth, a practice known as cold ironing, removes the emissions of their auxiliary engines, yet the resulting electricity demand is large, highly seasonal and hard to serve economically from the grid at the small and medium-sized ports that make up most of the European network. This study asks how to meet that demand affordably and cleanly. It develops a smart-sizing and energy-management framework for a grid-connected hybrid renewable energy system that jointly optimizes solar photovoltaic and wind capacity together with a combined battery-and-hydrogen storage envelope. An energy-conserving stochastic reconstruction of the hourly cold-ironing demand is embedded within a genetic algorithm that minimizes the levelized cost of energy and the carbon footprint, and the system is operated by a transparent, priority-based controller. On a full year of real operational data from a Mediterranean port, the optimizer selects 380 kilowatts of photovoltaic capacity and a 2064 kilowatt-hour, battery-dominated storage envelope, reaching a renewable penetration equal to 76 percent of annual demand, with 57 percent of demand met without the grid. Relative to grid-only cold ironing it lowers the levelized cost of energy by about 10 percent on a screening basis, before life-cycle costs bring it to roughly grid parity, while cutting greenhouse-gas emissions by 45 percent; emissions fall 72 percent relative to auxiliary engines. Storage capacity, not oversized renewable generation, proves decisive for deep decarbonization, and battery storage dominates the cost-optimal design for this diurnal load. The framework gives port operators a transferable, data-driven decision-support tool. Full article

Vibration energy technology holds promise for self-powered miniature wireless sensor devices in underground coal mines. This study proposes a magnetically coupled bistable composite-beam wind energy harvester (BCBWEH) to enhance the response threshold for harvesting weak ambient wind energy. A nonlinear magnetic model based on magnetic dipoles is established, and the system’s dynamic equations are formulated using the lumped parameter method. Numerical simulations analyze the effect of magnetic spacing on static bifurcation, and discuss the influences of initial static position, wind excitation, and magnetic moment on the system’s dynamic behavior; experimental results validate the accuracy of the numerical predictions. By adjusting the magnetic spacing under the same level of excitation, the system’s motion can transition from single-well oscillation to efficient inter-well vibration. When the initial position lies closer to the shallower potential well, relatively small wind excitation can trigger large-amplitude inter-well vibrations, thereby increasing output power. This study offers guidance for optimizing structural configurations and tuning design parameters of piezoelectric energy harvesters based on composite-beam architectures. Full article

The roll equation of a port–starboard symmetric ship is a clean physical realization of an order-two reflection (${\mathbb{Z}}_2$)-equivariant nonlinear oscillator: odd restoring and damping make the upright state a symmetric equilibrium whose two angles of vanishing stability form a heteroclinic-connected pair. A steady heeling action—beam wind, off-center load or list—enters as a single symmetry-breaking parameter c. Although the qualitative effect of such a bias is known, we show that this one parameter organizes the whole capsize problem in closed form. Equivariant singularity theory identifies c as the imperfection that unfolds the symmetric pitchfork of equilibria into a cusp, turning the heteroclinic pair into a homoclinic loop. The biased Melnikov boundary then yields two directional capsize thresholds and a damping-independent asymmetry index $\Delta f_{cr}=2c{I}_c/A\left(\mathsf{\Omega }\right)$, exactly linear in the bias: for a lightly damped hull a heel below $0.1°$ already halves the port/starboard split. For parametric roll, Floquet analysis gives the bias-corrected stability boundary, recovering $\Delta GM/GM>4\zeta$ in the symmetric limit and translating the principal tongue; for the dead-ship condition, the stationary Fokker–Planck solution—exact for the adopted one-degree-of-freedom (1-DOF) model—shows that, in the light-damping energy-diffusion regime, lightly damped capsize occurs over the lowered barrier with probability approaching one. A small-bias expansion reveals a sensitivity hierarchy—beam-sea capsize and dead-ship survival are first-order in the heel, and parametric detuning is only second-order—and a two-parameter cusp links the bias to pure loss of stability. All results are validated against safe-basin erosion, Floquet multipliers and Monte-Carlo simulation for a real vessel, offering the International Maritime Organization (IMO) second-generation intact-stability criteria (SGISC) a transparent, analytically based correction for the port–starboard asymmetry their symmetric assumption omits. Full article

Despite Nigeria’s vast and diverse untapped potential in solar, wind, biomass, and small-scale hydropower, a significant and persistent gap remains between national policy ambition and the practical implementation of renewable energy projects. This study investigates the underlying structural reasons why existing sustainable energy strategies have failed to significantly reduce fossil fuel dependency or resolve chronic electricity shortages, particularly within underserved semi-urban and rural communities where energy poverty remains a major barrier to development. Through a comprehensive thematic analysis of current regulatory frameworks, international development reports, and peer-reviewed academic literature, this research identifies critical bottlenecks in the energy transition process, with a specific focus on the deployment of solar mini-grids and decentralized energy systems as viable alternatives to the struggling national grid. The findings reveal that progress is hindered not by a lack of natural resources or high-level policy intent but by fragmented institutional coordination, weak regulatory enforcement, and a lack of robust de-risking mechanisms necessary to attract essential private sector investment. To bridge this implementation gap, this paper proposes a multi-dimensional strategic framework centered on fostering inter-agency synergy, implementing specialized capacity-building programs, and stabilizing financial foundations for renewable infrastructure. Full article

We formulate and analyze a 26-dimensional nonlinear dynamical system governing a doubly-fed induction generator (DFIG) wind energy conversion system coupled to an infinite bus through a dynamic transmission line. Seven interacting subsystems—aerodynamics, a two-mass drivetrain, a fourth-order machine, rotor- and grid-side converter controllers, a phase-locked loop, and a pitch regulator—are assembled into a single vector field $\dot{\mathbf{x}}=\mathbf{f}(\mathbf{x},\mathbf{u})$ on ${\mathbb{R}}^{26}$, derived in dimensionless coordinates. Strict positivity of the determinant $\mathrm{\Delta }=L_s{L}_r-L_m^2=\sigma L_s{L}_r$ for every physically admissible machine renders the flux–current map invertible, so the right-hand side is well defined; the nodal Kirchhoff constraint forms a semi-explicit differential-algebraic relation that we eliminate to obtain an explicit ordinary differential equation. The central contribution is a constructive scheme for the equilibria: the 26 stationarity conditions $\mathbf{f}({\mathbf{x}}^{\star },\mathbf{u})=\mathbf{0}$ are solved by an iterative voltage-matching procedure converging to a residual below ${10}^{-11}$ per unit—essentially machine precision—which removes the spurious start-up transients common in reported simulations. Analytically chosen feedback gains induce a hierarchy of well-separated time scales, placing the closed loop in the multiple-time-scale class; the separation is made quantitative through explicit small parameters ${\epsilon }_i$ formed from the ratios of subsystem time constants. Numerical integration of a GE $3.6$ MW configuration confirms the construction: under stationary forcing, the rotor speed stays within $1.32\times {10}^{-5}$ pu of the equilibrium, and under a large-amplitude wind program ($11\to 14\to 9$ m/s) spanning the full operating envelope, it is regulated to within $0.065\%$, while the DC-link voltage deviation remains below $2.4\times {10}^{-5}$ pu and the power balance closes with residual below ${10}^{-3}$ pu, the ≈2% mechanical–electrical gap being the modeled losses. Linearization about the computed equilibrium yields a Jacobian whose spectrum lies entirely in the open left half-plane, establishing local asymptotic stability and exposing the individual electromagnetic, torsional, and control modes. The model furnishes a rigorously initialized, analytically transparent basis for linearization, spectral stability analysis, and bifurcation study. Its practical value is that a consistent equilibrium and a certified spectrum remove the start-up transients and undocumented tuning that otherwise let initialization artifacts masquerade as genuine dynamics, so that the model can serve as a trustworthy building block for weak-grid and wind-farm stability studies. Full article