Search Results (147)

Critical components in support structures for wind turbines, flange joints, are fundamental to ensure the structural integrity of mechanical assemblies under varying operational conditions. This paper investigates the structural performance of L-type flange joints, focusing on the influence of bolt grades and bolt pretension through a finite element analysis (FEA) study of its key performance indicators, including stress distribution, deformation, and force–displacement behaviors. This paper studies two high-strength bolt grades, Grade 10.9 and Grade 12.9, and two main steps—first, bolt pretension and, second, external loading (tower shell tensile load)—to investigate the influence on joint reliability and safety margins. The novelty of this study lies in its specific focus on static axial loading conditions, unlike the existing literature that emphasizes fatigue or dynamic loads. Results show that the specimen carrying a higher bolt grade (12.9) has 18% more ultimate load carrying capacity than the specimen with a lower bolt grade (10.9). Increased pretension increases the stability of the joint and reduces the micro-movements between A and B (on model specimen), but could result in material fatigue if over-pretensioned. Comparative analysis of the different bolt grades has provided practical guidance on material selection and bolt pretension in L-type flange joints for wind turbine support structures. The findings of this work offer insights into the proper design of robust flange connections for high-demand applications by highlighting a balance among material properties, bolt pretension, and operational conditions, while also proposing optimized pretension and material recommendations validated against classical analytical models. Full article

The increasing adoption of Renewable Energy Sources (RESs), due to international energy policies mainly related to the decarbonization of electricity production, raises several operating issues for power systems, which need “flexibility” in order to guarantee reliable and secure operation. RESs can be considered examples of Distributed Energy Resources (DERs), which are typically electric power generators connected to distribution networks, including photovoltaic and wind systems, fuel cells, micro-turbines, etc., as well as energy storage systems. In this case, improved operation of power systems can be achieved through coordinated control of groups of DERs by “aggregators”, who also offer a “flexibility service” to power systems that need to be appropriately remunerated according to market rules. The implementation of the aggregator function requires the development of tools to optimally operate, control, and dispatch the DERs to define their overall flexibility as a “market product” in the form of bids. The contribution of the present paper in this field is to propose a new optimization strategy for flexibility bidding to maximize the profit of the aggregator in flexibility markets. The proposed optimal scheduling procedure accounts for important practical and technical aspects related to the DERs’ operation and their flexibility estimation. A case study is also presented and discussed to demonstrate the validity of the method; the results clearly highlight the efficacy of the proposed approach, showing a profit increase of 10% in comparison with the base case without the use of the proposed methodology. It is evident that quantitatively more significant results can be obtained when larger aggregations (more participants) are considered. Full article

Ultra-high-power wind turbine generator bearings are susceptible to micro-spalling and electrical erosion in long-cycle operation, which seriously affects the operating efficiency and service life of the unit. For this reason, this paper adopts a kind of composite grease containing nano-hydroxy magnesium silicate powder and, through the wind turbine assembly machine test and raceway surface analysis, systematically investigates its impact on bearing temperature rise, bearing vibration, and wind turbine power under actual working conditions to meet the lubrication requirements of wind turbine generator bearings. The results of the study showed that the composite grease significantly reduced the operating temperature of the wind turbine bearings under full operating conditions. It is worth noting that the reduction in generator bearing temperature varied among the three turbines due to uncertain environmental factors. In addition, the grease effectively increased the output power of the turbine under medium wind speed loading conditions, further verifying its potential value and practical effect in the application of wind turbines. Full article

This study presents a micro-scale hybrid wind turbine that integrates a Savonius rotor with a Helical Darrieus rotor, aiming to enhance energy conversion efficiency and adaptability for decentralized renewable energy generation. The hybrid design leverages the high torque generation of the Savonius rotor and the aerodynamic efficiency of the Helical Darrieus rotor. Computational analyses using CFD simulations and experimental validation with a 3D-printed prototype in a closed wind tunnel were conducted at speeds ranging from 3 to 8 m/s. The results demonstrate that the hybrid turbine achieves a power coefficient of 0.26 at an optimal tip-speed ratio of 2.7, marking a 180% improvement over standalone Savonius rotors. The hybridization process mitigates the low-speed inefficiencies of the Savonius rotor. It compensates for the high-speed limitations of the Darrieus rotor, resulting in a turbine capable of operating efficiently over a wider range of wind speeds. This balanced integration maximizes energy harvesting and improves adaptability to varying wind conditions, achieving balanced and synergistic performance. Full article

In many countries located in Central–Eastern Europe, there is a need for heating in the autumn and winter seasons. In Poland, this has been met over the years, mainly through the development of centralized heating systems. The heat sources in such systems are based on fossil fuels like coal or gas. New regulations and climate concerns are forcing a transformation of existing systems towards green energy. The research presents two scenarios of such a change. The first focuses on maintaining centralized heat sources but increases the share of renewables in the heat supply. This can be realized by weather-independent, high-power sources such as biomass boilers and/or high-temperature heat pumps (HP) such as sewage heat pumps or ground source HP. The second scenario changes the location of the heat sources to more dispersed locations so that the unit power can be lower. In this case, renewable heat sources can be used at favorable locations in the system. Among the sources included in this scenario are solar panels, photovoltaic panels, micro wind turbines, and ground source heat pumps with local heat storage. These are characterized by low energy density. Their dispersion in the urban space can contribute to the desired energy generation, which would be impossible to achieve in the centralized scenario. Furthermore, the transmission losses are lower in this case, so lower heating medium temperatures are required. The existing district heating network can be used as a buffer or heat storage, contributing to stable system operation. The article presents a comparative analysis of these solutions. Full article

During braking, high-power wind turbine disc brake friction pairs experience thermo-mechanical interactions at the interface, which lead to both physical and chemical changes. The friction interface features asperities and embedded hard particles within the substrate. Wear debris from these asperities or dislodged hard particles accumulates at the interface, continuing to participate in the friction process—a phenomenon known as the “endogenous third body”. Throughout braking, the microscopic morphology and contact conditions of the interface evolve dynamically. The stress–strain distribution and vibration behaviour of the friction system, influenced by the endogenous third body, also vary with braking parameters. This study employs the W-M fractal theory to develop a finite element model of a rough friction interface containing hard-particle endogenous third bodies. The model is validated through experimental testing. Based on the performance test parameters of high-power wind turbine disc brakes, a simulation is conducted to analyse the contact friction process involving the endogenous third body at the rough interface between the brake disc and brake pad. The simulation reproduces the formation process of the endogenous third body and reveals its evolutionary stages, including “ploughing”, “gap-filling”, and “aggregation”. Additionally, the study examines changes in the internal stress–strain and vibration states of the friction system under varying braking speeds (5 m/s to 35 m/s) and braking loads (3 MPa to 6 MPa). The findings demonstrate how different braking parameters influence the friction system containing the endogenous third body. The results showed that when the braking speeds were 5 m/s, 15 m/s, 25 m/s, and 35 m/s, and the braking load was 6 MPa, the average amplitude of the brake pads was the smallest, at 0.017 mm, 0.021 mm, 0.025 mm, and 0.020 mm, respectively. This research provides valuable insights into the three-body contact friction mechanism at the micro-braking interface, the formation of composite material third bodies, and the role of wear-stage third bodies in affecting the friction interface. Full article

More distributed energy resources are being integrated into microgrid systems, making scheduling more complex and challenging. In order to achieve the utilization of renewable energy and peak load shifting on a microgrid system, an optimal scheduling model is established. Firstly, a microgrid operation model including a photovoltaic array, wind turbine, micro gas turbine, diesel generator, energy storage, and grid connection is constructed, considering the demand response and the uncertainty of wind and solar power. The modeling demand response is determined via a price–demand elasticity matrix, whereas the uncertainty of wind and solar power is established using Monte Carlo sampling and a K-means clustering algorithm. Secondly, a multi-objective function that includes operational and environmental treatment costs is constructed. To optimize the objective function, an Improved Dung Beetle Optimization algorithm (IDBO) is proposed. A tent mapping, non-dominated sorting, and reverse elite learning strategy is proposed to improve the Dung Beetle Optimization algorithm (DBO); therefore, the IDBO is developed. Finally, the proposed model and algorithm are validated through some simulation experiments. A benchmark function test proves that IDBO has a fast convergence speed and high accuracy. The microgrid system scheduled by IDBO has the lowest total cost, and its ability to achieve peak load shifting and improve the utilization of renewable energy is proved through tests involving different scenarios. The results show that compared with traditional optimal scheduling models and algorithms, this approach is more reliable and cost-effective. Full article

Wind turbine design is an iterative process. Many aspects are considered when designing a wind turbine, including aerodynamic and power performance, structural loads and behavior, and control techniques. In the preliminary design stages, the governing equations of each design aspect are used to calculate the different loads and performance outputs while optimizing between them. This is usually made using wind turbine simulation software. This work presents a data-based machine learning (ML) approach towards the design of a micro-scale wind turbine. Extensive simulations are made on a 45 cm diameter rotor while performing parametric analysis using the QBlade wind turbine simulation tool. Different design parameters and wind conditions were changed one at a time, and data were collected to be further analyzed and used to train the ML models. The measurable outputs of the models are the coefficient of power (C_P), loads normal and tangential to the blade at midspan (F_N and F_T), and the torque (T) on the rotor. Linear regression was found unsuitable for predicting C_P due to its high nonlinearity; however, it gave satisfactory results for the blade loads. Ensemble models were found to give the highest accuracy for predicting all the desired outputs. The model accuracy is measured in terms of the coefficient of determination (R²), where the model could predict C_p, F_N, F_T, and T with R² values of 0.999, 0.984, 0.984, and 0.986 respectively. Full article

As global energy demands rise, there is an increasing need to transition from fossil fuels, which contribute to environmental harm and have limited reserves, to more sustainable and renewable energy sources. This shift is vital for both protecting the environment and ensuring long-term energy security. Renewable energy, such as wind power, plays a significant role in mitigating climate change and reducing greenhouse gas emissions while also being environmentally harmonious. Wind energy, in particular, is gaining importance as a clean, renewable source of power, with wind turbines serving as key components of this transformation. The success of wind energy projects depends largely on proper site selection. Factors such as wind potential, the topographical structure, environmental sensitivity, and legal considerations must all be carefully analyzed to ensure maximum performance and minimal environmental impact. The site selection process is crucial in optimizing energy production while promoting sustainability. Effective micro-siting strategies, which focus on the specific placement of turbines within a site, are also essential for improving energy efficiency and minimizing environmental disruption. This study highlights the importance of careful site analysis to ensure the successful and sustainable implementation of wind energy projects. Full article

The rise of high-rise vertical farms in cities is helping to mitigate urban constraints on crop production, including land, transportation, and yield requirements. However, separate issues arise regarding energy consumption. The utilisation of wind energy resources in high-rise vertical farms is therefore on the agenda. In this study, we investigate the aerodynamic performance of an ellipsoidal tall building with large openings to determine, on the one hand, the threshold income wind that could impact human comfort, and on the other, the turbulence intensity at specific locations on the roof and façade where micro-wind turbines could operate. To this end, we calculate the wind pressure coefficient and turbulence intensity of two scale models tested within a wind tunnel facility and compare the results with a separate CFD simulation completed in the past. The results confirm that the wind turbines installed on the building façade at a height of at least z/h = 0.725 can operate properly when the inlet wind speed is greater than 7 m/s. Meanwhile, the wind regime on the roof is more stable, which could yield higher energy harvesting via wind turbines. Furthermore, we observe that the overall aerodynamic performance of the models tested best under wind flowing at angles of 45° and 60° with respect to their centreline, whereas the turbulence at the wind envelope compares to that of the free wind flow at roof height. Full article

With the implementation of policies to promote renewable energy generation on the supply side, a micro-energy grid, which is composed of different electricity generation categories such as wind power plants (WPPs), photovoltaic power generators (PVs), and energy storage devices, can enable the local consumption of renewable energy. Energy storage devices, which can overcome the challenges of an instantaneous balance of electricity on the supply and demand sides, play an especially key role in making full use of generated renewable energy. Considering both minimizing the operation costs and maximizing the renewable energy usage ratio is important in the micro-energy grid environment. This study built a multi-objective optimization model and used the NSGA-III algorithm to obtain a Pareto solution set. According to a case study and a comparative analysis, NSGA-III was better than NSGA-II at solving the problem, and the results showed that a higher renewable generation ratio means there is less electricity generated by traditional electricity generators like gas turbines, and there is less electricity sold into the electricity market to obtain more benefits; therefore, the cost of the system will increase. Energy storage devices can significantly improve the efficiency of renewable energy usage in micro-energy grids. Full article

This paper investigates the potential of Micro Gas Turbines (MGTs) in the global shift towards low-carbon energy systems, particularly focusing on their integration within microgrids and distributed energy generation systems. MGTs, recognized for their fuel flexibility and efficiency, have yet to achieve the commercialization success of rival technologies such as Internal Combustion Engines (ICEs), wind turbines, and solar power (PV) installations. Through a comprehensive review of recent techno-economic assessment (TEA) studies, we highlight the challenges and opportunities for MGTs, emphasizing the critical role of TEA in driving market penetration and technological advancement. Comparative analysis with ICE and RES technologies reveals significant gaps in TEA activities for MGTs, which have hindered their broader adoption. This paper also explores the learning and experience effects associated with TEA, demonstrating how increased research activities have propelled the success of ICE and RES technologies. The analysis reveals a broad range of learning and experience effects, with learning rates (α) varying from 0.1 to 0.25 and experience rates (β) from 0.05 to 0.15, highlighting the significant role these effects play in reducing the levelized cost of energy (LCOE) and improving the net present value (NPV) of MGT systems. Hybrid systems integrating MGTs with renewable energy sources (RESs) and ICE technologies demonstrate the most substantial cost reductions and efficiency improvements, with systems like the hybrid renewable energy CCHP with ICE achieving a learning rate of α = 0.25 and significant LCOE reductions from USD 0.02/kWh to USD 0.017/kWh. These findings emphasize the need for targeted TEA studies and strategic investments to unlock the full potential of MGTs in a decarbonized energy landscape. By leveraging learning and experience effects, stakeholders can predict cost trajectories more accurately and make informed investment decisions, positioning MGTs as a competitive and sustainable energy solution in the global energy transition. Full article

The reproduced planetary boundary layer (PBL) wind is commonly applied in downscaled simulations using commercial CFD codes with Reynolds-averaged Navier–Stokes (RANS) turbulence modeling. When using the turbulent inlets calculated by numerical weather prediction models (NWP), adjustments of the turbulence eddy viscosity closures and wall function formulations are concerned with maintaining the fully developed wind profiles specified at the inlet of CFD domains. The impact of these related configurations is worth discussing in engineering applications, especially when commercial codes restrict the internal modifications. This study evaluates the numerical performances of open-source OpenFOAM 2.3.0 and commercial Fluent 17.2 codes as supplementary scientific comparisons. This contribution focuses on the modified turbulence closures to incorporate turbulent profiles produced from mesoscale PBL parameterizations and the modified wall treatments relating to the roughness length. The near-ground flow features are evaluated by selecting the flat terrains and the classical Askervein benchmark case. The improvement in near-ground wind flow under the downscaled framework shows satisfactory performance in the open-source CFD platform. This contributes to engineers realizing the micro-siting of wind turbines and quantifying terrain-induced speed-up phenomena under the scope of wind-resistant design. Full article

The hard particles in the copper-based powder metallurgic material of a brake pad for a wind turbine brake falls off and presses into the surface of the brake disc to form abrasive particles under high-speed and heavy-load working conditions. The presence of abrasive particles will produce abrasive wear with micro-scratch and micro-scribe on the copper-based material of the brake pad. The critical scratch depth effect in the abrasive wear process is proposed based on the critical depth effect of the metal removal process at the micro-scale. The abrasive wear is divided into two types: scratch wear and scratch wear, which is proposed according to the comparison of the actual scratch depth and the critical scratch depth. The range of braking speeds and friction coefficients in abrasive wear is determined by the recommended parameters of the disc brake. The ABAQUS2020 software is used to simulate and analyze the micro-scale abrasive wear of a brake pad. The brake strain/stress curves of the brake pad under different brake speeds and friction coefficients are compared and analyzed for two abrasive wear types based on the range of braking parameters, and the key factors affecting abrasive wear are proposed. Full article

In view of the increasing environmental challenges and the growing demand for sustainable energy solutions, the optimization of microgrid systems with regard to economic efficiency and environmental compatibility is becoming ever more important. This paper presents the Microgrid Performance and Investment Rating (MPIR) index, a novel assessment framework developed to link economic and environmental objectives within microgrid configurations. The MPIR index evaluates microgrid configurations based on five critical dimensions: financial viability, sustainability, regional renewable integration readiness, energy demand, and community engagement, facilitating comprehensive and balanced decision making. The current cases focus on the area of Greece; however, the model can have a wider application. Developed using a two-target optimization model, this index integrates various energy sources—including photovoltaics, micro-wind turbines, and different types of batteries—with advanced energy management strategies to assess and improve microgrid performance. This paper presents case studies in which the MPIR index is applied to different microgrid scenarios. It demonstrates its effectiveness in identifying optimal configurations that reduce the carbon footprint while maximizing economic returns. The MPIR index provides a quantifiable, scalable tool for stakeholders, not only advancing the field of microgrid optimization, but also aligning with global sustainability goals and promoting the transition to a more resilient and sustainable energy future. Full article