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Although the global market for wind energy is growing rapidly, leading-edge erosion is a critical issue hindering the development of wind power. The impact force of a droplet colliding with flat surfaces has been investigated in previous studies. However, the impact force exerted on curved surfaces, such as that experienced by eroded wind turbine blades, is not well understood. This study discusses the relationship between the impact force generated on a solid surface by a water droplet and the radius of curvature of the impacting surface. The impact force by a droplet was measured using a force sensor mounted on semi-cylindrical caps with different radii of curvature. The measurement results showed that the impact force decreased as the radius of curvature decreased. A computational fluid dynamics model solving incompressible flows showed that, unlike the case of a curved surface, the initial momentum of the droplet was mostly transferred to the flat surface. This resulted in a high impulse for an impact with a flat surface. The falling droplet was blocked by the surface, and the lateral jet was accelerated sideward. This acceleration was moderate for curved surfaces. When colliding with a flat surface, a higher impact force was generated owing to the wider area of the excited surface pressure compared with that of the curved surface. Finally, the relationship between the peak of the impact force and the surface curvature was derived, suggesting that the force peak is inversely proportional to the curvature. [ABSTRACT FROM AUTHOR]

With increasing environmental concerns and energy crisis, a variety of renewable energy sources (RES) are being increasingly utilised worldwide. However, the integration of RES such as wind power and photovoltaics in large-scale can lead to increased load fluctuations, which can undermine the overall environmental benefits and pose risks to the secure and stable operation of the power system. To mitigate this challenge, a two-stage electricity production scheduling is developed incorporating energy storage system (ESS) and dynamic emission modelling (DEM). In the first stage, a multi-objective mixed integer programming model schedules the production of RES, increasing penetration rate and system stability. In the second stage, a data-driven dynamic emission model is developed to optimise the load allocation of thermal power unit to reduce the carbon emissions. Furthermore, a flexible operating reserve strategy is proposed to handle the uncertainty resulting from the intermittent character of RES. Experimental results demonstrate that the proposed method effectively schedules the production of RES thereby alleviating the contradiction between high RES utilisation and stable system operation. Compared to the benchmark model, the proposed method can reduce the carbon emissions and total cost of the system by 20.34% and 10.65%, respectively. [ABSTRACT FROM AUTHOR]

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. We developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m2/MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m2 and 0.05 ± 0.01 m2/MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

The stand-alone wind-energy storage integrated hydrogen production technique is becoming a key and emerging technique to achieve carbon neutrality. However, the conflict between the random wind power fluctuation and the stable power demand of the electrolyzer lowers the system's operation stability and reliability. To address this issue, a modified output power smooth control strategy for the wind turbine that considers the dynamic performance of the electrolyzer is proposed. The output power of the wind turbine can be smoothed following the need of the electrolyzer, which helps reduce the electrolyzer's start-stop times and the battery's charging and discharging cycles. Eventually, the efficiency and life span of the hydrogen production system is enhanced. Afterward, an operational strategy for the hydrogen production system is provided, and a coordinated sizing strategy for the wind turbine, energy storage system, and electrolyzer is proposed. The results of case studies, which use the real data obtained from a hydrogen production demonstration project, prove that the overall lifecycle revenue for the hydrogen production system is remarkably increased. Finally, a long-term simulation model for a stand-alone wind-energy storage integrated hydrogen production system was developed. Simulation results validate the effectiveness of the proposed method. • The proposed method smooths wind turbine power in line with electrolyzer dynamics. • A coordinate sizing method fully considering practical factors is constructed. • The proposed method can reduce the electrolyzer's annual shutdown time by 4.37%. • The proposed method can help increase the annual hydrogen production by 6.06%. • The proposed method can help enhance the overall lifecycle revenue by 32.92%. [ABSTRACT FROM AUTHOR]

While Iran has notable renewable energy potentials, the renewable energy sector of this country has remained underdeveloped, mostly because of easy access to cheap fossil fuels. This paper discusses and analyzed the possibility for hydrogen generation from wind resource in urban city which is suffered from air pollution and is located in northwestern Iran. Wind energy and power density estimations were performed using the 2-parameter Weibull probability distribution function. These estimates were used to predict the power output, hydrogen output, economic viability, and environmental benefit of building a wind power-hydrogen production unit in one of several candidate sites in the studied area. Ultimately, the most suitable site for such a project was determined using the SWARA/WASPAS method. After investigating 16 different conventional wind turbines, the best one in terms of achievable power and hydrogen output and economic feasibility was determined. The results showed that Gamesa G80 with a capacity of 2 GW was the best wind turbine for the urban area. Gardaneh-Almas with a wind power density of 1252W/m2 was identified as the best site for power generation in the region. Potential wind-powered hydrogen output at this site was estimated to 97 ton/yr. LCOE and LCOH for this site were estimated to 0.047 $/kWh and 4.6 $/kg-H 2 , respectively. • Hydrogen production integrated urban area toward sustainable cities are discussed. • 3E analysis of wind energy for hydrogen production (WHP) is investigated. • A multi-aspect analysis of WHP is analyzed by WASPAS. • A sensitive analysis on wind energy integrated hydrogen system is performed. • The results showed the wind-hydrogen system is best solution in Iranian cities. [ABSTRACT FROM AUTHOR]

This work assesses a chemical plant for the conversion of biogas into negative emission "emerald hydrogen" via electrified reforming and CO 2 separation. Electrification of the reformer allows for enhanced syngas production, compact reactor designs and flexible operation, thanks to the avoidance of combustion and heat transfer through pressure walls. The integration of the process with solar and wind power generation has been assessed by part-load process simulations and plant sizing and operation optimization through yearly simulations with hourly discretization. Different European locations with different wind and solar availabilities were assessed considering (i) short- and long-term cost scenarios for renewables and battery technologies and (ii) different plant size (from 390 to 3900 Nm3/h of biogas capacity). The overarching scope of the paper is to calculate the cost of the produced hydrogen and the economic value of flexibility for plants installed in different locations, under different cost scenarios. At design load, the assessed process consumes 17.7 kWh of electricity per kg H2 and retains 96% of the biogas chemical energy in the produced hydrogen. Additionally, 76% of the biogenic carbon is recovered as high-purity liquid CO 2 , achieving up to −9 kg CO2 /kg H2 negative emissions. When powered with 95% of renewable energy, hydrogen production cost ranges from 2.5 to 2.9 €/kg for a long-term REN cost scenario and large-scale flexible plant to 5.9–7.1 €/kg for a short-term REN cost scenario and small-scale inflexible plants. For small-scale plants, flexibility allows to reduce the hydrogen production cost by 11–16% with respect to the inflexible plant in the short-term renewables cost scenario and by 1–4% in the long-term cost scenario. For large-scale plants, the adoption of a flexible plant leads to a reduction of 17–23% of the hydrogen cost in the short-term scenario and of 6–22% in the long-term scenario. Operational flexibility of electrified reforming allows reducing the cost of negative-emission bio-hydrogen by 1–23%, depending on location and cost scenario. [Display omitted] • Process engineering study with off-design model. • Economic optimization of flexible process with PV, wind, BESS and gas storages. • 17.7 kWh/kg H2 of electric consumption and up to −9 kg CO2 /kg H2 negative emissions. • H 2 cost of 2.5–6.2 €/kg depending on location, REN cost scenario and plant capacity. • Flexibility reduces H 2 cost by 1–23% depending on location and REN cost scenario. [ABSTRACT FROM AUTHOR]

Because of its inherent properties, the use of thermoplastic composites is expanding in a number of industries, including aerospace, rail transportation, and wind power generation. However, the development of 2D and 3D reinforced thermoplastic composite structures is hampered by the high viscosity and poor wetting of thermoplastic matrices, resulting in their application being mainly limited to nonload‐bearing components. This article provides a comprehensive overview of the technology and current applications of thermoplastic composites, covering materials, preform structures, manufacturing methods, process parameters, performance, and applications. It also provides an outlook on their future development. Highlights: Thermoplastic composite has economic and environmental benefits.Summarized the current technology and application of thermoplastic composites.The manufacturing difficulty is the thermoplastic polymers wet fibers.One promising approach to the issue is prepreg technology.Prepreg technology make 3D thermoplastic composites become possible. [ABSTRACT FROM AUTHOR]

Improving wind power generation efficiency and lowering maintenance and operational costs are possible through the early and efficient diagnosis and repair of surface defects in wind turbines. To solve the lightweight deployment difficulty and insufficient accuracy issues of the traditional detection methods, this paper proposes a high-precision PC-EMA block based on YOLOv8 using partial convolution (PConv) combined with an efficient multiscale attention (EMA) channel attention mechanism, which replaces the bottleneck layer of the YOLOv8 backbone network to improve the extraction of target feature information from each layer of the network. In the feature fusion phase, GSConv, which can retain more channel information, is introduced to balance the model's complexity and accuracy. Finally, by merging two branches and designing the PConv head with a low-latency PConv rather than a regular convolution, we are able to effectively reduce the complexity of the model while maintaining accuracy in the detection head. We use the WIoUv3 as the regression loss for the improved model, which improves the average accuracy by 5.07% and compresses the model size by 32.5% compared to the original YOLOv8 model. Deployed on Jetson Nano, the FPS increased by 11 frames/s after a TensorRT acceleration. [ABSTRACT FROM AUTHOR]

This research examines the enhancement of low power electronic systems, such as low power wide area networks (LPWANs), by incorporating a mix of renewable energy sources like solar and wind in China. It addresses the challenges posed by the variability of these sources due to climatic and temporal factors by merging diverse energy harvesting (EH) methods to bolster power stability and availability. The study assesses the most effective combination of solar, wind, and rain EH for steady power supply. A novel algorithm is introduced for energy input management based on real‐time resource availability, with the goal of prolonging battery life by avoiding complete charge or discharge cycles. The feasibility of this multisource approach in possibly reducing the need for extra energy storage is evaluated. The investigation includes simulations using Chinese weather data to explore different combinations of energy sources. A real‐life system utilizing solar and wind energy, guided by the developed algorithm, was also implemented for empirical comparison. Findings suggest that solar and wind energies have a higher power yield than rain harvesting, with actual wind energy collection often falling short of simulated forecasts. The solar–wind energy mix achieves a 99% system availability and facilitates a more compact design owing to their high power density. Although the input‐switching algorithm lessens the frequency of complete battery drainage, a small degree of energy storage is still essential for maintaining system reliability. This integrated EH method, compared to single‐source options, allows for a smaller energy storage requirement. Moreover, the algorithm limits battery charging to 80%, significantly enhancing battery lifespan. [ABSTRACT FROM AUTHOR]

With the rapid development of wind power generation in recent years, the demand for detecting weak signals of wind turbine faults has become more urgent. This paper introduces a novel memristor chaotic circuit constructed based on third-order magnetically memristors. The Melnikov chaotic condition of this circuit is analyzed, and its dynamical characteristics are studied through phase trajectory diagrams, bifurcation diagrams, Lyapunov exponent spectra, and Poincaré maps. Leveraging the initial value sensitivity and noise immunity of chaotic systems, the memristor chaotic circuit is employed for the detection of weak signals in wind turbine faults. Using the chaotic system state transition method, we find the threshold for the circuit state to transition from chaotic state to large-scale periodic state, adjust the parameters to make the system in a critical state, input the wind turbine fault vibration signal, and detect the fault signal based on its state transition. Subsequently, the chaotic resonance method is employed, introducing the signal under test, which contains high-intensity chaotic noise, into this novel memristive circuit. This results in chaotic resonance, causing the noise components to be concentrated toward the frequency region where the weak signal under test is located, thereby enhancing the fault signal and facilitating fault identification. The results indicate that this novel memristor chaotic circuit possesses advantages such as high accuracy, strong noise immunity, straightforward operation, and clear judgment in the field of weak signal detection. This circuit shows promising applications in the field of weak signal detection. [ABSTRACT FROM AUTHOR]

Providing sustainable electricity access to remote areas is critical for economic development and environmental preservation. This study investigates the performance of single‐source and hybrid renewable energy systems for the town of Zahedan, Iran, which has significant solar and wind energy potential. Using TRNSYS software, eight configurations were simulated and analyzed, comprising two single‐source (photovoltaic [PV] and wind turbine [WT]) and six hybrid systems incorporating combinations of PV panels, WTs, alkaline fuel cells, and diesel generators. The analysis revealed that hybrid systems, particularly those combining PV and WT, outperformed single‐source configurations. For instance, a hybrid system with 800 kW of PV and a 50 kW WT reduced diesel consumption by 35% and CO2 emissions by 45% compared to a system relying solely on a diesel generator. Conversely, the configuration involving WTs, fuel cells, and diesel generators showed high energy dumping (1,821,776 kWh) and considerable diesel usage, underscoring the challenges of maintaining energy balance without solar integration. Overall, hybrid renewable systems generally provide enhanced reliability and environmental benefits, although their performance heavily depends on the specific energy source mix. This study offers insights into optimizing renewable energy systems for remote locations, highlighting the necessity of a balanced solar‐wind combination to achieve optimal sustainability and cost‐effectiveness. The findings are applicable to regions with similar climatic conditions and contribute to global sustainable energy solutions, providing crucial information for policymakers and investors focused on supporting sustainable energy projects in isolated areas. [ABSTRACT FROM AUTHOR]

Human safety is the most important factor to determine any grounding system, therefore low‐frequency grounding resistance (LFGR) of wind power generation systems should be very low. Lightning protection is another factor for the grounding system design. Grounding conductors (GCs) are used to reduce the LFGR. A long GC however, does not reduce peak voltages for lightning currents with steep‐front waveshapes. Thus, the GC length is an important factor for an effective grounding system. This paper proposes a method for determining the effective length of GC based on traveling wave theory in time domain. Based on this calculation, it describes a grounding system design for wind power generation systems that considers both, the LFGR and the lightning protection. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Reliable and highly resolved information about onshore wind energy potential (WEP) is essential for expanding renewable energy to eventually achieve carbon neutrality. In this pilot study, simulated 60 m wind speeds (ws60m) from a km‐scale, convection‐permitting 3.3 km‐resolution ICON‐LAM simulation and often‐used 31 km‐resolution ERA5 reanalysis are evaluated at 18 weather masts. The estimated ICON‐LAM and ERA5 WEPs are then compared using an innovative approach with 1.8 million eligible wind turbine placements over southern Africa. Results show ERA5 underestimates ws60m with a Mean Error (ME) of −1.8 m s−1 (−27%). In contrast, ICON‐LAM shows a ME of −0.1 m s−1 (−1.8%), resulting in a much higher average WEP by 48% compared to ERA5. A combined Global Wind Atlas‐ERA5 product reduces the ws60m underestimation of ERA5 to −0.3 m s−1 (−4.7%), but shows a similar average WEP compared to ERA5 resulting from the WEP spatial heterogeneity. Plain Language Summary: Onshore wind energy is expected to play a major role in the global energy transition. However, reliable and highly resolved information on the onshore wind energy potential (WEP) crucial for expansion planning is missing over southern Africa. This study evaluated high resolution 3.3 km ICON‐LAM atmospheric simulations and 31 km ERA5 reanalysis against 60 m wind speed (ws60m) observations and compared the corresponding derived WEPs. The results show that ERA5 underestimates ws60m by 27%, resulting in a 48% lower WEP assessment than ICON‐LAM, whose ws60m simulation results show a very small bias. Underestimation of wind energy yields may hinder further expansion of wind energy, as less economic performance is expected, which underlines the importance of highly resolved weather data. Key Points: Simulated ERA5 and km‐scale ICON‐LAM wind speeds are evaluated and corresponding southern Africa wind energy potentials are calculatedERA5 underestimates 60 m wind speed, whereas ICON‐LAM produces lower biases in the wind speed simulationsHigher wind energy potentials are revealed from wind speeds simulated by ICON‐LAM compared to ERA5, which is often used for such assessments [ABSTRACT FROM AUTHOR]

In response to growing reliance on electricity and gas systems, this paper introduces a stochastic bi‐level model for the optimized integration of these systems. This integration is achieved through sizing and allocating of power‐to‐gas (P2G) and gas‐to‐power (G2P) units. The first level of the model focuses on decisions related to P2G and G2P unit installations, while the second level addresses optimal system operation considering decisions made from first level and stochastic scenarios. The primary aim is to enhance energy‐sharing capabilities through coupling devices and mitigate wind generation curtailment. An economic evaluation assesses the model's effectiveness in reducing costs. N − 1 contingency analysis gauges the integrated system's ability to supply load under emergency conditions. Two new indices, performance of the electricity system and performance of the natural gas system, are proposed for N − 1 contingency analysis. These indices quantify the proportion of the supplied load to the total load, thereby illustrating the system's capacity to meet demand. For numerical investigation, the proposed model is applied to a modified IEEE 14‐bus power system and a 10‐node natural gas system. Numerical results demonstrate a 9.426% reduction in investment costs and a significant 10.6% reduction in wind curtailment costs through proposed planning model. [ABSTRACT FROM AUTHOR]

The power-to-gas (P2G) technology transforms the unidirectional coupling of power network and natural gas network into bidirectional coupling, and its operational characteristics provide an effective way for wind and solar energy accommodation. The paper proposes a bi-level optimal dispatch model for the integrated energy system with carbon capture system and P2G facility. The upper model is an optimal allocation model for coal-fired units, and the lower model is an economic dispatch model for the integrated energy system. Moreover, the upper model is solved by transforming the model into a mixed-integer linear programming problem and calling CPLEX, and the lower model is a multi-objective planning problem, which is solved by improving the small-habitat particle swarm algorithm. Finally, the simulation is validated by the MATLAB platform, and the results show that the simultaneous consideration of carbon capture system and P2G facility improves the economics of the integrated energy system and the capacity of wind and solar energy accommodation. [ABSTRACT FROM AUTHOR]

Profit maximization is crucial for both producers and customers in power grids, particularly in deregulated energy markets. By focusing on profit maximization measures, power grids can improve economic viability and sustainability for all stakeholders. The growing demand for electricity in modern civilization poses a significant challenge to the power grid's ability to meet it. To address these difficulties, the power industry is attempting to integrate renewable sources into existing power facilities. Because of its unpredictable character, the presence of renewable energy in the electricity system becomes increasingly important and adds complexity to the grid. Given the intermittent nature of renewable sources, an energy storage device is required in this scenario. During the low-power use phase, the grid has ample power. Meanwhile, energy storage devices can be utilized to store extra power in the low power demand phase while maintaining the safety and stability of the power network during peak demand periods. V2G (Vehicle-to-Grid) technology is commonly employed to address the uncertainty of renewable resources while maintaining system stability. By using automobiles as transportable storage devices, V2G can make the best use of excess electricity during low-energy hours. Wind energy's volatility causes imbalances, lowering system profitability. With wind energy integration, power system profitability can be improved by analyzing uncertainties and employing mitigation strategies. To overcome the issue, the research optimizes the use of V2G and TCSC (thyristor-controlled series compensator). V2G permits bidirectional power flow, lowering imbalance pricing (IP) while considering power demand. TCSC can increase the transient stability of transmission lines, hence reducing line faults. TCSC's involvement in the system increases profitability by lowering congestion expenses. Strategic TCSC placement increases overall profitability. The approach strives to offer efficient, environmentally friendly power at a reasonable price while addressing the needs of both power providers and customers. This study also looks into the effects of V2G mixing on voltage stability, LMP (locational marginal price), and the effectiveness of a TCSC in a deregulated electrical system. MiPower software is used to simulate operation and find the optimal placement of the storage unit within the IEEE 14-bus system. [ABSTRACT FROM AUTHOR]

Power transformers are essential elements in power systems and thus their protection schemes have critical importance. In this paper, a scheme is proposed for accurate discrimination and location of internal faults in power transformers using conventional measuring devices attached to the transformer. Different types of internal winding faults are intensely considered: partial discharge, inter-disk faults, series and shunt short circuit faults and axial displacement. Depending on the transformer measured output voltage, input voltage and the input current, the construction of a locus diagram (ΔV-Iin) serves as an indicator for any physical modification to the winding. Using five suggested features extracted from the developed locus, an artificial neural network (ANN) technique is applied to accurately distinguish any deviation from the transformer healthy condition. The exact location of each fault inside the windings of power transformer is then determined. The obtained results validate the usefulness of the proposed scheme for different internal faults. The superiority of the proposed scheme is extensively examined by comparing its results with some published schemes. [ABSTRACT FROM AUTHOR]

Wind speed is one of the main control factors of wind erosion and dust emissions, which are major problems in arid and semiarid regions of the world. Accurately simulating highly precise hourly wind speeds is critical and cost-efficient for land management decisions with the goal of mitigating wind erosion and land degradation. The Wind Erosion Prediction System (WEPS) is a process-based, daily time-step model that simulates changes in the soil–vegetation–atmosphere. However, to date, relatively few studies have been conducted to test the ability of the WEPS in simulating hourly wind speeds. In this study, the performance of the WEPS model was tested in the Inland Pacific Northwest (iPNW), where wind erosion is a serious problem. Hourly wind speeds were observed and simulated by the WEPS at 13 meteorological stations from 2009 to 2018 using the WEPS hourly wind speed probability histogram. Owing to increasing wind shear, the model is not as precise in reproducing high wind speeds. The WEPS inadequately simulated the hourly wind speeds at six of the 13 stations, with a low index of agreement (d < 0.5). The complex regional topography may be one of the reasons for this lack of agreement, because the WEPS's performance of interpolation relies on spatial distances and surface complexity. Therefore, we validated the model using another wind-speed database to eliminate the impact of spatial interpolation. The performance of the WEPS was improved after removing the impact of spatial interpolation, producing d values > 0.5 at nine of the 13 stations. Our results suggest that the WEPS can accurately simulate hourly wind speeds and assess wind erosion in the absence of interpolation, whereas the model may be uncertain when invoking spatial interpolation. Some evidence also suggests that the model may have a tendency to underestimate observed hourly wind speeds. Pragmatically, this suggests that model users should consider the possibility that WEPS may underestimate wind erosion risk in the iPNW and plan implementation of conservation practices accordingly. [ABSTRACT FROM AUTHOR]

Wind farms are a clean and efficient source of renewable energy. However, they cause negative impacts on raptors. Here, we present a review of the existing scientific literature on the effects of wind farms on raptors' ecology with a particular interest in the potential solutions. After collecting 216 studies, we found a consensus in the literature that raptors exhibit avoidance behaviors, and that the abundance of raptors decreases after wind farm installation, although it might recover over time. The position of wind farms on mountaintop ridges poses a particular danger to large soaring raptors, as they rely on orographic uplift to gain altitude. Adult mortality significantly affects population dynamics, particularly in endangered species, but young inexperienced individuals show a higher collision risk. The combination of different methods including field monitoring, GPS telemetry and systematic search for carcasses is an adequate approach to further investigate the problem and solutions. Shutdowns on demand, the installation of deterrents, turbine micro‐sitting and the repowering of wind farms have been suggested as potential solutions, although results are contradictory and case‐specific. Furthermore, it is essential to report the potential occurrence of conflicts of interest in scientific papers, as they can influence the interpretation of the results. Finally, from a future perspective, it is crucial to assess the effectiveness of solutions to mitigate the negative effects of wind farms to promote raptor conservation. This becomes increasingly relevant in the context of renewable energy development and increasing energy demand worldwide. [ABSTRACT FROM AUTHOR]

ABSTRACT The contribution explores the significance of employing dry‐air technology as an efficient method for controlling and mitigating corrosion inside offshore wind turbine nacelles and towers. The article describes a dry‐air approach that curtails the necessity for costly corrosion protection measures and it explains its ability to diminish and regulate relative humidity. Additionally, it is outlined how the utilization of a dry‐air strategy results in the creation of an internal overpressure within the wind turbine structure. This overpressure effectively serves as a barrier against the ingress of moisture‐laden, salt‐infused air. Comparative site‐sensor data are presented and discussed for two dehumidification techniques. Finally, practical solutions are presented. [ABSTRACT FROM AUTHOR]

Wind power generation has become an indispensable part of the power supply side of the power grid. Due to the intermittent and uncertain characteristics of wind energy, short-term wind power prediction plays an important role in the stable operation of power system. By constructing the digital twin model, real-time and high-precision prediction of wind energy is realized. First, the genetic algorithmsupport vector machine (GA-SVM) algorithm is used to build the model. Multidimensional sensors and meteorological stations of the virtual wind power generation system collected the meteorological data of the environment and updated the meteorological history database at the same time. Second, based on the collected meteorological data, the preliminary prediction results are obtained, and by searching in the historical database, the predicted value and the actual output value of wind turbines or wind farms under similar conditions are obtained. Finally, the prediction results of the GA-SVM are modified to obtain the predicted value of the digital twin model. The prediction method can greatly improve the accuracy of the short-term forecast of wind energy. [ABSTRACT FROM AUTHOR]

Accurate wind speed modeling is beneficial for the design of wind energy conversion systems. Models of wind speed are used to assess the adequacy and dependability of a power supply. However, precise wind speed modeling is challenging due to the sporadic availability of wind speed. In this note, we propose a wind speed model with an autoregressive (AR) structure. A hybrid model is developed under linear and nonlinear parts based on a quasi‐linear autoregressive exogenous neural network (Q‐ARX‐NN). The model's structure is composed of a regression vector and its coefficients. The coefficients are divided into linear and nonlinear coefficients. A set of linear coefficients is identified under the algorithm of least square error (LSE), and a set of nonlinear coefficients is modeled by using a neural network to refine the residual error of the nonlinear part. Some artificial neural network (ANN) models can be set as nonlinear part sub‐models to sharpen the model's accuracy. The proposed model is tested for wind speed modeling to estimate wind energy production. Various nonlinear parts of the sub‐model are tested, such as neural networks, radial basis function networks, and ANN networks. Moreover, we evaluate the effects of the order of the model by varying hidden and output nodes, which can be summarized as the number of coefficients of the regression vector. Using specific wind turbine performance data, prediction models estimate production power. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy such as offshore wind power to electrolyze seawater for hydrogen production offers a sustainable development pathway to address energy and climate change issues. In this study, by incorporating nitrogen-doped carbon quantum dots (N-CDs) into precursors, we successfully synthesized a nitrogen-doped carbon (NC)-layer-coated Co(OH)F/CoP2 catalyst NC@Co(OH)F/CoP2/NF loaded on nickel foam (NF). The introduction of N-CDs induced significant morphology change of the catalyst, facilitating the exposure of numerous active sites, ensuring the presence of catalytically active species CoP2 in nanoparticle form and avoiding agglomeration, which was advantageous to enhancing the overall hydrogen evolution reaction (HER) activity of the catalyst. The formation of Co–N bonds accelerated electron transfer, regulated the electronic structure, and optimized the catalyst's adsorption capacity for H* intermediates, which resulted in remarkably improved HER performance. In addition, Co(OH)F can also serve as a structural support, preventing the catalyst from collapsing during the HER catalytic process. NC@Co(OH)F/CoP2/NF exhibited excellent HER activity in alkaline freshwater and alkaline seawater, respectively requiring overpotentials of only 107 and 128 mV to achieve a current density of 100 mA cm−2. More importantly, it also demonstrated excellent HER activity at high current densities, with overpotentials of 189 and 237 mV at a current density of 1000 mA cm−2 in alkaline freshwater and alkaline seawater, respectively. This work provides new insights into the design and construction of highly efficient HER catalysts for applications in alkaline freshwater and seawater. [ABSTRACT FROM AUTHOR]

The rapid development of offshore wind farms (OWFs) calls for economical and reliable power transmission technology. This review paper focuses on the diode‐rectifier‐unit based high voltage direct current (DRU‐HVDC) transmission systems. The main technical features of DRU‐HVDC are highlighted and the comparisons with MMC‐HVDC and LCC‐HVDC are conducted. Considering the uncontrollability of DRU and the necessity of offshore wind turbines (WTs) to establish offshore network, the existing decentralized and centralized control strategies are reviewed in detail. For the fully‐grid‐forming converter, the operation principle of the P–V and Q–f power control is explained from the OWF‐DRU level and the WT level, respectively. For the partial‐grid‐forming converter, why the voltage control loop can be eliminated is analysed. Focusing on the start‐up issue caused by the unidirectional‐power‐flow characteristic of DRU, several start‐up solutions are reviewed, including medium voltage alternative current (MVAC) umbilical cable, auxiliary MMC, energy storage for WTs, auxiliary low voltage DC cable. Then considering different fault locations, the fault characteristic and protection of the DRU‐HVDC system is presented, including the offshore AC faults, DRU faults, HVDC faults and onshore AC faults. Finally, the future research topics worth exploring for DRU‐HVDC system are identified. [ABSTRACT FROM AUTHOR]

Wind farm can obtain the maximize profit by optimizing micro‐locations and cables. The factors that affect profit include the power output of wind turbines, cost and et al., where power output is affected by wake effect, cable cost is related to the length and type of collector cable. The profit is calculated on the premise that the costs and power loss of collector cable are determined. Obviously, there is a hierarchical relationship between the above problems. Therefore, a bi‐level optimization model with constraints is constructed in this paper, where the upper‐level objective function is the maximum profit, and the lower‐level objective functions are consists of minimum the cable cost and the power loss of collector cable; Moreover, an improved algorithm (IDEDA), based on differential evolution and Dijkstra, is used to optimize above model; Finally, simulation experiments are carried out for IDEDA and four algorithms for two different wind conditions, and the results show that IDEDA performs better compared to the other four algorithms in terms of profit and cable cost. [ABSTRACT FROM AUTHOR]

Wind power in China is experiencing accelerating growth to meet the need for structural reform of the energy supply, however its impact on the ecological environment urgently needs to be taken into account. In this study, the impact of a wind farm in Gonghe County, Qinghai Province, China, on local land surface temperature (LST) was explored by removing the temporal background using year-by-year LST averaging and filtering the spatial background using pixel-by-pixel LST averaging based on Moderate Resolution Imaging Spectroradiometer (MODIS) and the European Centre for Medium-Range Weather Forecast's ERA5 data. The main findings are as follows: (1) From a long-term series perspective, the LST on the wind farm and the adjacent areas shows an increasing trend, reaching 0.060K/19a in spring; (2) the wind farm exerts a warming effect on the local LST, with a maximum of 7.04 K and a minimum of 1.63 K, and there is a significant spatial matching with the wind farm boundaries, which is more obvious in spring and winter, and less pronounced in summer and autumn; (3) the construction of wind farms also has a potential upward impact on the LST in the adjacent areas, especially in autumn and winter, and the warming effect gradually decreases with increasing distance; (4) the warming effect is most remarkable when the predominant wind directions of the upwind and downwind are close to consistent and the differences in wind volumes are significant. Research findings on the effect of wind farms on local LST are vitally important for strengthening the establishment of wind farms, site selection of wind farms, and the scientific and reasonable utilization of wind energy resources. Key policy highlights: Impacts of wind farms on local land surface temperature. Using the MODIS and ERA5 data whose temporal and spatial backgrounds have been removed. [ABSTRACT FROM AUTHOR]

Icing is a popular research area in wind energy, and the icing problem of the supercooled droplet–ice crystal mixed-phase condition is one of the new challenges. A numerical method for analyzing the icing characteristics of wind turbine airfoil under mixed-phase conditions is presented. The control equations for the dynamics of supercooled droplets and ice crystals are formulated using the Lagrangian method. Equations for the conservation of mass and energy during the icing process involving supercooled droplets and ice crystals are constructed. The impact of erosion phenomena on the mixed-phase icing process is examined, and methodologies for solving the control equations are introduced. The numerical method is utilized for modeling mixed-phase icing under a range of conditions. The results of these simulations are then compared with data obtained from icing wind tunnel tests to assess the validity of the method. The influence of various mixed-phase conditions on ice shapes is studied. It is found that higher icing temperatures correspond to a larger icing range and amount. The increase in supercooled droplet content, ice crystal content, and ice crystal diameter all contribute to enhanced ice accretion. However, the effects of ice crystal content and diameter are relatively minor. [ABSTRACT FROM AUTHOR]

The diode-rectifier unit (DRU)-based high-voltage direct current (HVDC) transmission system offers an economical solution for offshore wind power transmission. However, this approach requires offshore wind farms to establish a strong grid voltage. To meet this requirement while fulfilling the dynamic characteristics of the DRU, this paper proposes an advanced grid-forming (GFM) control strategy for offshore wind turbines connected to DRU-HVDC. The strategy incorporates a P-U controller and a Q- ω controller based on reactive power synchronization. Furthermore, a novel virtual power-based pre-synchronization method and an adaptive virtual impedance technique are integrated into the proposed GFM control to improve system performance during wind turbine (WT) integration and low-voltage ride-through (LVRT) scenarios. The virtual power-based pre-synchronization method reduces voltage spikes during the integration of new wind turbines, while the adaptive virtual impedance technique effectively suppresses fault currents during low-voltage faults, enabling faster recovery. Simulation results validate the effectiveness of the proposed GFM control strategy, demonstrating improved start-up and LVRT performance through the pre-synchronization and adaptive virtual impedance methods. [ABSTRACT FROM AUTHOR]

The generation of sustainable energy through wind and hydrokinetic turbines, which convert the kinetic energy from fluid flows into mechanical energy, presents an attractive solution for diversifying the country energy matrix in response to climate change. Consequently, numerous studies have investigated the aerodynamic and hydrodynamic behaviors of various wind and hydrokinetic turbines using numerical simulations to understand their interaction with the surrounding fluid flows and enhance their performance. However, to validate these studies and aiming at improving the turbine design, experimental studies on a laboratory scale employing wind tunnels and hydraulic channels are essential. This work addresses the development and implementation of a reliable control system for experimentally evaluating the power coefficient (Cp) versus the tip speed ratio (TSR) curve of wind and hydrokinetic turbines. The control system, based on a DC motor acting as a generator and aligned with a commercial torque sensor, enables a precise control over the experimental setup. By obtaining and comparing the experimental performance curves of Cp versus TSR for both wind and hydrokinetic turbines with numerical results, the effectiveness and accuracy of the developed control system are demonstrated. A satisfactory fit between numerical and experimental results was achieved, underscoring the utility and reliability of the control system for assessing the turbine performance. [ABSTRACT FROM AUTHOR]

The "dual carbon" goal has made it a mainstream trend for new energy stations (NESs) and energy storage stations (ESSs) to jointly participate in market regulation. This paper proposes a multiple time scale distributed optimization method for NESs and ESSs based on the alternate direction multiplier method (ADMM). By first considering the uncertainty of new energy output and the volatility of electricity market prices, a multi time scale revenue model is constructed for day-ahead, intraday, and real-time markets. Then, the objective function is built by maximizing the comprehensive market revenues and is simplified using the synergistic effect of NESs and ESSs. Next, the simplified objective function is solved by the ADMM, and the revenues are maximized while each energy meets the relevant constraints. Lastly, the 33-node network topology is used to illustrate the feasibility of the proposed method. The simulation results show that after optimization, the output of NESs and ESSs can coordinate work in day-ahead, intraday, and real-time markets, while the abandonment power of wind and light is significantly improved. [ABSTRACT FROM AUTHOR]

This paper proposes a correction technique for bad data and high-precision analysis based on micro-phasor measurement unit (μPMU) data for a stable and reliable smart substation. First, a high-precision wide-area monitoring system (WAMS) with 35 μPMUs installed at Korea's Yeonggwang substation, which is connected to renewable energy sources (RESs), is introduced. Time-synchronized μPMU data are collected through the phasor data concentrator (PDC). A pre-processing program is implemented and utilized to integrate the raw data of each μPMU into a single comma-separated values (CSV) snapshot file based on the Timetag. After presenting the technique for identification and correction of event, duplicate, and spike bad data of μPMU, causal relationships are confirmed through the voltage and current fluctuations for a total of five states, such as T/L fault, tap-up, tap-down, generation, and generation shutdown. Additionally, the difference in active power between the T/L and the secondary side of the M.Tr is compared, and the fault ride through (FRT) regulations, when the fault in wind power generation (WP), etc., occurred, is analyzed. Finally, a statistical analysis, such as boxplot and kernel density, based on the instantaneous voltage fluctuation rate (IVFR) is conducted. As a result of the simulation evaluation, the proposed correction technique and precise analysis can accurately identify various phenomena in substations and reliably estimate causal relationships. [ABSTRACT FROM AUTHOR]

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of ( D   (1 + D) / (1 − D) . where D is the regulator transistor's on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to evaluate the accuracy of different forecasting models for monthly wind farm electricity production. This study compares the effectiveness of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), and Support Vector Regression (SVR). This study utilizes data from two wind farms located in Poland—'Gizałki' and 'Łęki Dukielskie'—to exclude the possibility of biased results due to specific characteristics of a single farm and to allow for a more comprehensive comparison of the effectiveness of both time series analysis methods. Model parameterization was optimized through a grid search based on the Mean Absolute Percentage Error (MAPE). The performance of the best models was evaluated using Mean Bias Error (MBE), MAPE, Mean Absolute Error (MAE), and R2Score. For the Gizałki farm, the ARIMA model outperformed SARIMA and SVR, while for the Łęki Dukielskie farm, SARIMA proved to be the most accurate, highlighting the importance of optimizing seasonal parameters. The SVR method demonstrated the lowest effectiveness for both datasets. The results indicate that the ARIMA and SARIMA models are effective for forecasting wind farm energy production. However, their performance is influenced by the specificity of the data and seasonal patterns. The study provides an in-depth analysis of the results and offers suggestions for future research, such as extending the data to include multidimensional time series. Our findings have practical implications for enhancing the accuracy of wind farm energy forecasts, which can significantly improve operational efficiency and planning. [ABSTRACT FROM AUTHOR]

The large-scale integration of wind power significantly alters the voltage dynamic characteristics of power systems. Wind turbines have a weak ability to withstand grid disturbances and have difficulty in providing effective reactive power support during transient periods. The sensitivity of wind turbines to the grid voltage significantly increases the probability of large-scale, cascading off-grid events. This paper proposes a coordinated control strategy to enhance the transient reactive power support capability of doubly fed wind farms. The additional stator current demagnetization control reduces the risk of a crowbar protection action after a fault and ensures that the unit power is controllable. Based on the voltage–reactive power coupling relationship, each unit can produce reactive power according to the voltage–reactive power sensitivity matrix during the transient period. After the reactive power output of the unit reaches the limit, transient active and reactive combined control is further adopted to reduce the active power output of the unit to a certain extent and improve the reactive power support capability. Finally, two cases are built in the PSCAD to verify the effectiveness of the proposed control strategy. The results show that the proposed control strategy can enable the wind farm to output more reactive power to the grid during the transient period, effectively supporting the system voltage during the transient process and avoiding further deterioration of the fault. [ABSTRACT FROM AUTHOR]

In recent years, hybrid towers have become increasingly established, especially for tall wind turbines. The concrete part of these towers, commonly constructed using segmental construction methods, consists of several circular ring segments stacked on top of each other. To reduce the amount of fabrication and erection effort, the joints between the segments are typically designed as dry ground joints. This paper deals with experimental investigations to determine the torsional load‐bearing capacity of such dry ground concrete joints subjected to combined loading of prestressing, bending, and torsion. Based on the experience of previous investigations, a test set‐up consisting of three reinforced concrete segments with circular ring cross‐sections was developed. The herein newly developed evaluation concept enabled precise identification of the failure point for each test run utilizing the measured tangential displacements of the joint. The test results clarify the weaknesses of the current design model regarding the insufficient interaction with the bending moment and show very good accordance with the new calculation model, the so‐called fiber model. [ABSTRACT FROM AUTHOR]

The combined deployment of a PV and SW system in a residential building with an electric vehicle The interest in independent and sustainable energy supply is steadily increasing in times of continuously rising electricity prices and growing environmental awareness. While photovoltaic (PV) systems have almost become commonplace on roof surfaces and balcony railings, small wind (SW) turbines are still relatively rare. This is despite the fact that wind power accounts for over 50 % of the renewable energy generated in Germany and is subject to significantly lower fluctuations throughout the year compared to solar radiation. The aim of the calculations presented in this article therefore was to exemplarily examine whether the combined use of photovoltaic and small wind turbine systems on residential buildings represents both an energetically and an economically viable course of action. It was also necessary to analyse the importance of using and charging an electric vehicle in the context of the system combination. The resulting economic efficiency of the combined systems was determined by comparing software‐based yield forecasts for a specific location with the load profile of an average 3‐person household. [ABSTRACT FROM AUTHOR]

The past decade has seen rapid development of offshore wind energy around the world. Furthermore, to improve the efficiency of power generation, wind turbine development has been trending towards increasingly large and tall turbines. These developments call for innovations in the form of wind turbine towers to address the challenges faced by existing tower forms (e.g., steel tubular towers and prestressed concrete towers) in structural adequacy, construction efficiency and/or maintenance. This paper presents a new form of hybrid wind turbine towers which possesses many important advantages over the existing tower forms and are particularly suitable for large offshore wind turbines. The new hybrid towers, termed herein hybrid FRP-concrete-steel prestressed double-skin wind turbine towers or PDSWTs, are prefabricated in segments and then assembled on site. The PDSWT segments are a variation of hybrid FRP-concrete-steel double-skin tubular members (DSTMs), and they consist of an outer confining tube made of fibre-reinforced polymer (FRP), a thin steel inner tube with welded shear studs, prestressed concrete between the two tubes, and flanges welded at the ends of the steel tube. The onsite assembly of the tower involves mainly connecting the steel flanges of two adjacent segments using high-strength bolts, and installing prestressed tendons through the whole tower. In this paper, the rationale behind the development of PDSWTs is first explained, followed by a discussion of the design considerations and future research needs to facilitate the practical applications of the new tower form. [ABSTRACT FROM AUTHOR]

The pervasive issue of global warming has propelled the continued empirical efforts by policymakers and research pundits geared towards finding sustainable solutions to salvaging the ecosystem. Consequently, this study evaluates the heterogenous impacts of technological innovation, sustainable energy, and financial development on environmental sustainability captured by CO2 emissions, methane emissions, and nitrous oxide emissions in the BRICS countries from 1995 to 2020. The study employs second-generation estimators comprising quantile regression (QR), augmented mean (AMG), common correlation effect group mean (CCEMG), and cross-sectional ARDL (CS-ARDL). The main findings show that among the indicators of technological innovation, high technology exports, ICT goods exports, and ICT services exports drive sustainable environment in the long run whereas environmental-related technology promotes both in the short run and long run. The moderating impacts of sustainable energy are evident through wind energy, solar energy, and hydrogen technology. Conversely, financial development measured by broad money and domestic credits to private sector hinders environmental sustainability. More so, the covariates entailing economic growth, population growth, poverty, and trade openness escalate the stock of pollutants. The empirical regularity of the main estimators is supported by outcomes of QR across the low, middle, and upper quantiles. On the policy front, the study recommends promoting initiatives that drive technology and renewable energy to enhance the sustainability of the BRICS' environment. [ABSTRACT FROM AUTHOR]

Why do some European countries succeed in developing offshore wind power? This study compares the Spanish and Danish cases from the 1970s to 2021. By completing the literature on both policy failure and success with concepts from psychology, the study stresses the relevance of public funding instability, federal architecture, intertwined political interests and policy discourse as dimensions that impact the rise of offshore wind power. Drawing on this framework, the Danish success suggests that strong leadership based on a shared objective can create efficient institutions able to avoid veto players and secure financial investments over time. This process can boost the rise of a self-confident discourse that will reinforce the virtuous circle. [ABSTRACT FROM AUTHOR]

To effectively manage turbine blade weight and blade deflection under severe weather conditions, longer and stiffer blades are required, fiber glass producers have devoted significant efforts to developing and commercializing high‐modulus (HM) glass fiber products of the first generation. The current focuses aim at the commercialization of the second generation and the development of the third‐generation products. This article briefly reviews four key areas: (a) the benefit of longer blades on wind energy generation, (b) characteristics of HM glass fibers of various generations, (c) fundamental science and understanding behind HM glass fiber development, and (d) finally statistically based composition (C)–property (P) and structure (S)–property (P) modeling approaches in new glass design. [ABSTRACT FROM AUTHOR]

[Display omitted] • Swelling-assisted pyrolysis was proposed for the recovery of glass fibers from WTBs. • Resin decomposition ratio reached 76.8 % at 350 °C in swelling-assisted pyrolysis. • The swelling treatment physically disrupted the cross-linked structure of the WTBs. • The oxidation duration was reduced owing to the less content of pyrolysis char. • Tensile strength of fibers from swollen-WTB was higher than that from original-WTB. The recycling of end-of-life wind turbine blades has become a global environmental challenge driven by the rapid growth of wind power. Pyrolysis is a promising method for recovering glass fibers from these discarded blades, but traditional pyrolysis is often operated at high temperatures, which degrades the mechanical properties of recovered fibers. To address this issue, a swelling-assisted pyrolysis method was proposed to recover high-quality glass fibers from end-of-life wind turbine blades at low temperatures. The results confirmed that the decomposition of the resin matrix within the blade was significantly promoted at low temperatures in the swelling-assisted pyrolysis process, achieving a resin decomposition ratio of 76.8 % at 350 °C. This improvement was attributed to enhanced heat transfer and co-pyrolysis with acetic acid. Swelling could physically disrupt the cross-linked structure of the blade, creating a more porous and layered structure, thereby enhancing heat transfer during the pyrolysis process. Simultaneously, the co-pyrolysis with acetic acid could generate hydrogen radicals, which promoted the cracking of macromolecular oligomers into lighter products or gaseous alkanes. Consequently, the formation of pyrolysis char within the solid pyrolysis product was reduced, shortening the oxidation duration to 30 min. In comparison to traditional pyrolysis, the swelling-assisted pyrolysis process effectively suppressed the diffusion of surface defects over the recovered fibers, leading to promising improvements in their flexibility, elasticity, and mechanical properties, with tensile strength notably increased by 27.5 %. These findings provided valuable insights into recovering high-quality glass fibers from end-of-life wind turbine blades. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the Engineering students' knowledge on Renewable Energy (RE) resources. An online survey through proving Google form was conducted by using descriptive methodology. The participants for the survey were the engineering undergraduate students from Military Institute of Science and Technology (MIST), Dhaka, Bangladesh. A set of e-questionnaire with 19 items including 4 demographic and 15 knowledge measuring items was developed to collect data from the MIST undergraduate students. A total of 153 students responded to the survey. The demographic results indicated that male students of first and third study year with 20 to 30 years of age range from mechanical or industrial and production-engineering fields of study are the maximum respondents to the survey of this study. The main findings of the study highlighted that engineering students at MIST possess a higher level of understanding about various aspects of renewable energy, including solar energy, geothermal energy, wind energy, biogas energy, laws and policies of renewable energy (RE), establishment of RE, sources of information for RE, and the application of renewable energy in Bangladesh. Since the mean score for the questions was 3.72, reflecting a knowledge level between neutrality and agreement, the majority of the students responded positively to all the questions, indicating their strong grasp of these topics. The results also revealed that female students had a good understanding of renewable energy compared to male students, with an average score of 3.83 for females and 3.69 for males. Additionally, the study found that 3rd-year students displayed the highest level of understanding, while 1st-year students exhibited the lowest level of comprehension regarding renewable energy resources. [ABSTRACT FROM AUTHOR]

[Objective] Soil erosion caused by compound forces is obvious in Mollisol region, studying the annual alternating superposition of natural driving factors for soil composite erosion in different typical intervals in Northeast Mollisol Region has practical significance for soil erosion control in the region. [Methods] We analyzed and compared the spatiotemporal distribution of natural driving factors of water, wind, freeze-thaw, and snowmelt in 11 typical regions of the region, and clarified the alterative and superposition characteristics of each factor. [Results] In terms of time, the driving factors of hydraulic power, wind power, freeze-thaw and snowmelt in northeast Mollisol region occurred in superposition and alternation within the year. In spring, the driving factors of wind power, freeze-thaw and snowmelt were the most complex. In Summer, the driving factors of hydraulic power, wind power and freeze-thaw were the main driving factors. In autumn, the combined effects of hydraulic power, wind power and freezing and thawing were limited, while in winter, the effects of wind power and freezing were obvious. In terms of space, the hydraulic driving effect gradually decreased from southeast to northwest. Wind effect gradually decreased from southwest to northeast. The freeze-thaw effect gradually decreased from southwest to northeast. Snowmelt gradually decreased from northwest to southeast. According to the different characteristics of erosion driving factors, the whole region was divided into hydraulic, water-wind-freeze- thaw, water-wind-snow melt, water-freeze-thaw-snow melt erosion zones, and targeted soil erosion control could be carried out in different regions. [Conclusion] Each camp showed obvious temporal and spatial differences in their erosion performance. The characteristics of the composite erosion driving factors in a year were obtained based on the alternating superposition of natural driving factors within a year, providing reference for targeted soil erosion control and in-depth research on the composite erosion prevention and control in different regions. [ABSTRACT FROM AUTHOR]

Pumped storage power stations have flexible functions such as peak shaving, frequency regulation, phase modulation, and emergency backup, which can suppress the fluctuation of new energy output, promote new energy consumption, and improve the safe and stable operation level of the power grid. However, under the current two part tariff system, the rotating reserve value of pumped storage power stations in the power grid has not been fully reflected. This article takes the complementarity of wind power, photovoltaic, and pumped storage power stations as the background, constructs a day-ahead scheduling model for pumped storage power stations considering the requirement of rotating reserve. The goal is to maximize the operational revenue of the pumped storage power station and minimize the peak valley difference in the output of other power plants in the power grid. By using the weight method, the multi-objective problem is transformed into a single objective optimization problem to solve. Furthermore, the impacts of the current two part tariff and peak valley electricity price on the scheduling strategy and the operational profit of pumped storage power stations are analyzed and compared. The calculation results show that considering the requirement of rotational reserve can significantly improve the operating profit of pumped storage power stations, and the scheduling objectives have a significant impact on the operation mode of the power station. The model and method in this paper can be used to make the day ahead scheduling of pumped storage power stations. [ABSTRACT FROM AUTHOR]