Exploitation Of Wind Energy Research Articles

A piezoelectric oscillator for low-speed wind energy collection

ABSTRACT The exploration of low-speed wind harvesters is key to harnessing wind energy and enabling self-powered Internet of Things (IoT) sensor networks. In this paper, a piezoelectric oscillator (APO) for low-speed wind energy collection (B-WEC) is proposed and applied to low-speed wind energy harvesting. The magnetic model and power generation characteristics of the harvester are formulated, the magnetic torque is simulated, and the performance under different parameter combinations is tested experimentally. The results show that the APO rotation reduces the magnetic resistive torque by 26.00%. The highest peak-to-peak voltage is 92.35 V for an APO magnet diameter is 8 mm and the angle of the stopper (γ) is 60°, which is 1258.09% higher than fixed (γ is non-existent). Moreover, it has a maximum power of 0.56 mW at 4 m/s, and the optimally matched resistance is 200 kΩ. The harvester can light up about 150 LEDs. The B-WEC designed in this paper can effectively reduce the driving wind speed of piezoelectric wind energy harvesters and can be used as a power source for self-powered networked sensor networks. This study provides a new solution idea for the exploitation of wind energy.

Wake effect impact on the levelized cost of energy in large floating offshore wind farms: A case of study in the northwest of the Iberian Peninsula

With the growing world energy needs, offshore wind farms tend to increase in terms of installed capacity, rated power, and the number of wind turbines. This trajectory leads to higher electricity production losses due to the wake effect between the wind turbines, resulting in an elevated Levelized Cost of Energy. Therefore, it is crucial to estimate this cost for various wind farm designs, involving the application of different distances between the wind turbines, aiming to identify the most cost-effective solutions. In this study these estimates were carried out within a legally designated 1800 km2 area earmarked for offshore wind energy exploitation by the Spanish government, situated at the northwest corner of the Iberian Peninsula, considering 15 MW wind turbines. This region is one of the most promising areas of the Iberian Peninsula and Europe since its wind resource potential for the upcoming years has been classified as outstanding. The wind data employed in this analysis emanates from a dynamical downscaling process performed using the Weather Research and Forecasting model, derived from a multi-model ensemble of the 6th phase of the Coupled Model Intercomparison Project. The data encompasses the timeframe spanning 2025 to 2049, under the Shared Socioeconomic Pathways 2–4.5, adjusted to coincide with the projected operational lifetime of wind farms. The results show that, without any kind of restrictions in terms of installed power and number of wind turbines, the most economically advantageous Levelized Cost of Energy is achieved at intermediate distances between the wind turbines. Conversely, when specifying a predetermined number of wind turbines, optimal results are attained with the application of the highest distance between turbines.

Development of wind turbines for urban environment using innovative design thinking methodology

This work focuses mainly on wind energy usage as a renewable source for energy generation in urban environments, where the variability of air current flow is a challenge. One of the main objectives to be achieved in this study is to develop small vertical wind turbines. Design thinking methodology was used to innovative ideas development using the application of concepts from rapid prototyping (additive manufacturing). As a target object to idealize an innovative product, was the providing of a mobile equipment recharging system, using the air current generated by the urban public transport vehicles. As a result, a modular system of small power generation was produced, tested, and validated. The mini-turbine with the best performance in power generation in wind flows lower than 4 m/s was the VAWT, which achieved the smallest difference, 18 % greater. Therefore, it was demonstrated that the installation of small wind turbines in an urbanized area requires a minimum of wind measurements at the exact location to validate the innovative design.

Consideration of various configurations of SG6043-based rotor applied in small capacity horizontal axis wind turbine

The SG6043 airfoil model is well known for its high aerodynamic efficiency and it is suitable for designing small wind turbine blades. This paper determined the optimal blade configurations using only the SG6043 airfoil model with ten different lengths from 1 m to 10 m. Then, it proposed the most suitable model for a rated wind speed of 5 m/s in Vietnam. The chord and twist values of each blade’s part were optimized by using the Betz optimization method (BOM) in the Qblade open software. Several important characteristic quantities such as lift coefficient (Cl), drag coefficient (Cd), power factor (Cp) and power (P) of the different blade configurations are determined by using a combination of both XFLR5 code and Qblade software. After that, parameters related to operation such as pitch angle and rotation speed of the rotor were also investigated to find the operating conditions for the best efficiency of wind energy exploitation. The obtained results show that the Cp of the blades has a maximum value of about 0.476 and the P has a value of up to 95.319 kW in operating conditions with a wind speed range between 1 m/s and 10 m/s. In addition, the ratios of power to blade surface area (P/S) and the ratios of power to blade volume (P/V) at the wind speed of 5 m/s were also investigated. The results show that rotors with blades ranging from 3 m to 5 m will give much higher P/S and P/V values than other blade configurations under these operating conditions. This emphasizes that these blade configurations will bring more economic benefit because they will consume less material and reduce production time while still ensuring the required capacity value. Finally, the 5 m blade rotor with a capacity of 2.750 kW at a rated wind speed of 5 m/s was proposed as the rotor suitable for individual household use. This design can help millions of Vietnamese households be proactive in their power source, thereby contributing to the significant reduction of CO2 emissions from coal-fired power plants.

The Impact of High-Rise Building Shapes on Wind Flow Characteristics and Energy Potential

In recent years, wind energy has become a potential source of low carbon energy. The shape of a building is a significant factor in aerodynamics, providing an opportunity for wind power control and wind energy proliferation. This research project aims to study the design of high-rise buildings and investigate how wind affects energy absorption by developing an aerodynamic optimization procedure (AOP) and using Computational Fluid Dynamics (CFD) in COMSOL Multiphysics. This study aimed to optimize the building shape for wind energy exploitation. Optimizing the building shape in the early stages of design enables the control of wind-induced loads and responses and reduces the energy demand in high-rise buildings, where resource consumption is higher than that in low-height buildings. This study used a three-dimensional CFD simulation of wind loading on tall buildings to optimize the building shape. This research will provide valuable insights for architects, engineers, and building developers to design and optimize high-rise buildings for wind energy exploitation, reduce the carbon footprint, and improve the energy efficiency of buildings.

Acoustic measurements of wind farm noise inside homes and comparison with the ISO 9613 standard

To achieve the energy transition objectives, many wind farms are installed to produce electricity by exploiting wind energy. The production of electricity through wind farms is widespread in the world. One of the problems complained about by people who live near wind farms is the noise emitted by the rotation of the blades. This work reports acoustic measurements inside homes near wind farms. The acoustic measurements were performed for different wind speeds and directions. Furthermore, to verify the effectiveness of the simulation method of the propagation of the noise generated by wind farms, the measured values of the sound levels were compared with those obtained from the numerical simulations using the provisions of the ISO 9613 standard, and the wind turbines are considered point-like sound sources. The comparison between the measurements carried out in the field with the theoretical simulations has highlighted that the calculated levels are lower than the measured ones, this means that in the acoustic impact forecasting procedures, the noise emitted by the wind farms is underestimated and is one of the reasons why the Wind farms in operation are a source of complaints from the populations living nearby.

Drivers for optimum sizing of wind turbines for offshore wind farms

Abstract. Large-scale exploitation of offshore wind energy is deemed essential to provide its expected share to electricity needs of the future. To achieve the same, turbine and farm-level optimizations play a significant role. Over the past few years, the growth in the size of turbines has massively contributed to the reduction in costs. However, growing turbine sizes come with challenges in rotor design, turbine installation, supply chain, etc. It is, therefore, important to understand how to size wind turbines when minimizing the levelized cost of electricity (LCoE) of an offshore wind farm. Hence, this study looks at how the rated power and rotor diameter of a turbine affect various turbine and farm-level metrics and uses this information in order to identify the key design drivers and how their impact changes with setup. A multi-disciplinary design optimization and analysis (MDAO) framework is used to perform the analysis. The framework uses low-fidelity models that capture the core dependencies of the outputs on the design variables while also including the trade-offs between various disciplines of the offshore wind farm. The framework is used, not to estimate the LCoE or the optimum turbine size accurately, but to provide insights into various design drivers and trends. A baseline case, for a typical setup in the North Sea, is defined where LCoE is minimized for a given farm power and area constraint with the International Energy Agency 15 MW reference turbine as a starting point. It is found that the global optimum design, for this baseline case, is a turbine with a rated power of 16 MW and a rotor diameter of 236 m. This is already close to the state-of-the-art designs observed in the industry and close enough to the starting design to justify the applied scaling. A sensitivity study is also performed that identifies the design drivers and quantifies the impact of model uncertainties, technology/cost developments, varying farm design conditions, and different farm constraints on the optimum turbine design. To give an example, certain scenarios, like a change in the wind regime or the removal of farm power constraint, result in a significant shift in the scale of the optimum design and/or the specific power of the optimum design. Redesigning the turbine for these scenarios is found to result in an LCoE benefit of the order of 1 %–2 % over the already optimized baseline. The work presented shows how a simplified approach can be applied to a complex turbine sizing problem, which can also be extended to metrics beyond LCoE. It also gives insights into designers, project developers, and policy makers as to how their decision may impact the optimum turbine scale.

Reduced desalination carbon footprint on islands with weak electricity grids. The case of Gran Canaria

The aim of this paper is to present options to make low-carbon footprint large-scale desalination a reality on arid islands with weak electrical grids. Through these options, the goal is to reconfigure on-grid wind energy/desalination systems for large- and medium-scale water production. In this context, it is proposed to use lithium-ion batteries for stationary energy storage together with management strategies aimed at avoiding the wind energy/desalination systems having to consume energy from the conventional grid they are connected to. The control strategy is based on ensuring that the power provided by the wind farm and batteries remains in synchrony with the power demand of the desalination plant throughout the system's useful life. The interannual variation of wind energy is considered when sizing the renewable energy system and processes for its estimation are proposed. The case study is centred on the Canary Archipelago, a region that is especially vulnerable to the impacts of climate change, but which enjoys exceptional characteristics for the exploitation of wind energy. The results obtained show the optimal wind farm and energy storage system capacities of the analysed configurations. The approach presented allows a low-carbon operational footprint. If the control strategy were to be put into practice today, the current grid restrictions and a life cycle assessment of the system carried out in a societal context that continues to be fossil fuel dependent indicate a potential reduction of 77.4% of the footprint. However, the remaining 22.6% could be eliminated in the future when the manufacturing processes of wind turbines, batteries and desalination plants receive the benefits of carbon-neutral societies.

Neural network-assisted integration of renewable sources in microgrids: A case study

This study examines the incorporation of renewable energy sources into microgrids using neural network-assisted optimization methods. The objective is to tackle the difficulties related to the fluctuation and uncertainty of renewable energy production. An examination of the collected data over various time periods indicates encouraging patterns in the production of renewable energy. The solar energy use shows a steady rise from 120 kWh to 140 kWh, representing a 16.67% increase. Similarly, wind energy usage also demonstrates an upward trend, increasing from 80 kWh to 95 kWh, marking an 18.75% expansion. The biomass energy production has seen a substantial increase from 50 kWh to 65 kWh, representing a significant 30% rise. The examination of microgrid load consumption demonstrates the increasing energy needs in residential, commercial, and industrial sectors. The household load consumption has increased from 150 kWh to 165 kWh, representing a 10% spike. Additionally, the commercial load and industrial load have also seen a surge of 15%. The predictions made by the neural network demonstrate a high level of accuracy, closely matching the actual output of renewable energy. The accuracy rates for solar, wind, and biomass projections are 98.4%, 95.5%, and 97.3% correspondingly. The assessment of improved energy distribution emphasizes the effective usage of renewable sources, guaranteeing grid stability and optimal resource utilization. The results highlight the capacity of neural network-assisted methods to precisely predict renewable energy outputs and efficiently incorporate them into microgrids, hence promoting sustainable and resilient energy solutions. This report provides valuable insights on improving microgrid operations, decreasing reliance on traditional energy sources, and accelerating the shift towards sustainable energy systems.

Machine Learning-Driven Wind Energy Forecasting for Sustainable Development

The growing need for energy, in addition to the depletion of fossil fuel supply, has underlined the importance of renewable energy for long-term growth. Renewable energy stands out among these, but its broad usage is hampered by the inherent uncertainty of wind power generation. This study uses machine learning to predict wind energy yield. Several regression models were used, including decision tree regression, linear regression, and random forest regression. The results emphasize the random forest regression, which has a high R-squared score, suggesting strong predictive ability. The paper also contains wind power output projections, which provide insights for optimal wind energy planning and usage. Overall, this attempt gives vital insights to improving the effective use of renewable energy, advancing the cause of sustainable development.

A semi-analytical method for the static stability analysis of air cushion supported floating platforms

Air cushion-supported floating platforms (ACSFPs) have a simple structure and low construction cost, yet they possess excellent stability and hydrodynamic performance, making them suitable for deep-sea wind or wave energy exploitation. However, efficient methods for evaluating the stability of ACSFPs are lacking. In this paper, a semi-analytical stability analysis method was developed for ACSFPs, which analytically calculates the displacement of ACSFPs and air cushion volume. It numerically solves the nonlinear equations that consist of the conservation of ACSFP displacement and the ideal gas equations for air cushions to obtain the stability lever. The semi-analytical method not only allows for the quick evaluation of the initial stability of ACSFPs but also efficiently assesses larger angles, including extreme conditions such as air leakage from cushions and submergence of the wetted surface. The effectiveness of the semi-analytical method was demonstrated by using it to calculate the stability of a circular ACSFP, and its results were verified using the CAD method.

Study of indicators on regulation for offshore wind energy exploitation in Brazil

ABSTRACT Generating electrical power through offshore wind farms presents an opportunity for Brazil to diversify its energy matrix, embracing renewable sources and addressing challenges such as climate change and energy security. Despite three decades passing since the installation of the world's first offshore wind farm, Brazil has yet to take effective steps towards implementing wind turbines in its territorial waters and exclusive economic zone, revealing a significant gap in harnessing its maritime wind potential. This study assessed the adequacy of the country's legal and regulatory framework for the expanding offshore wind sector, considering environmental, technological, tariff-related, and organizational dimensions. The results pointed out challenges impacting the sector: the lack of competence of the Energy Research Company (EPE) to obtain prior environmental licenses, the absence of competence of the National Energy Policy Council (CNPE) in defining areas for bidding, and the inadequacy of the CNPE's composition in adequately representing the affected sectors, limiting the diversity of perspectives considered. These discoveries provide essential guidance for the Legislative and Executive branches, assisting in the formulation of policies that promote sustainable growth of offshore wind energy in Brazil, contributing to a cleaner and more resilient energy future in the face of climate change.

Nigerian wind energy status

This review paper evaluates the current status of the Nigeria wind energy sector to identify the available Wind Energy Potential, Installed Wind Energy Capacity and Renewable Energy Policies in a bid to provide accurate information to aid the exploration and exploitation of wind energy across Nigeria. Consequently, the huge expanse between the wind energy Potential across Cities in Nigeria, the poor numbers of installed wind capacity and Nigeria’s Renewable Energy policies show low interest in Wind Energy in comparison to other RE sources. All this calls for further investment in the Nigerian wind energy sector

A simple continuum approach to predict the drained pull-out response of piles for offshore wind turbines

The article presents a continuum approach to predict the response of pile foundations for jacket-supported offshore wind turbines. Tensile loading conditions are examined, which may be critical for piles used in combination with this structure type, generally adopted to exploit wind energy in intermediate water depths. The approach is developed to guarantee a simple implementation with a limited number of input data easily attainable from cone penetration tests and laboratory tests, and to ensure computational cost-effectiveness. Data from technical-scale tests on open-ended steel piles driven in dense sand and subjected to drained pull-out are used to assess the performance of the approach. The results are shown to be accurate, approximating rather closely the experimental load–displacement curves. The accuracy of the approach is also compared to that obtained with a recently proposed design method, to investigate the predictive capacity of the approach and its potential to support preliminary design activities.

Fatigue strength of tubular welded connections in offshore floating platforms

AbstractThe work reported in the present paper is part of a European research program aimed at developing a hybrid tension‐leg floating platform, suitable for combined offshore wind and wave energy exploitation. Eight (8) fatigue tests on welded tubular joint specimens are performed, which represent the full penetration brace‐to‐cylindrical column welded connections of the project prototype structure. The large‐diameter columns are reinforced internally with a grid of longitudinal and transverse stiffeners fillet welded to the shell. The specimens are approximately 1/6‐scale physical models made of S355 grade steel, and subjected to cyclic loading under constant load amplitude histories. The brace‐to‐cylinder welds are semiautomatic, and high‐frequency mechanical impact treatment is applied in four specimens. The experiments are supported by post‐fracture metallographic examination and finite element analyses. The results indicate two locations for fatigue crack initiation: brace‐to‐cylinder crown and cylinder‐to‐stiffener connection.

Efficiency and Feasibility Analysis of Wind Turbines in Tandem in a Vortex Tube

Polar scientific research is of great importance for the human. The exploitable wind energy of the polar region accounts for more than 20% in the worldwide sense. However, the harsh polar storms, extreme wind speed (up to 100 m/s), ice crystals and sand in the wind all hinder the exploitation of wind resources. Therefore, in order to protect the power generation infrastructure and to maximize the power generation window, this paper proposes an innovative concept of power generation first. This concept, placing multi wind turbines in tandem in a vortex tube, is based on the Venturi principle which allows the wind in a funnel-shaped air inlet to accelerate. Meanwhile, the large-scale vortices and associated turbulent kinetic energy in the tube are diminished through the inlet honeycomb grid, thus driving the multi-turbines in tandem to generate more power. Second, to verify the efficiency of this concept, the CFD simulation technology is employed to investigate the wake characteristics in two distinct flow fields, namely the open space and the vortex tube space. The simulation results are then compared with prototype site tests. The comparison confirms the superior performance of this vortex tube scheme accommodating multi-turbines and the use of a honeycomb at the inlet.

Potential of prospective plans in MENA countries for green hydrogen generation driven by solar and wind power sources

This study is focused on exploring the potential of green hydrogen production in distinctive geographical locations in the Middle East and North Africa (MENA) by leveraging solar and wind energies. Those locations include Egypt, Morocco, and the Gulf region, as prospective hydrogen hubs. The current mathematical model has been developed using Matlab/Simulink and validated with the respective literature. Using realistic meteorological data of those cities, the hourly hydrogen yield, energetic and exergetic efficiencies have been predicted. A levelized cost of hydrogen and carbon dioxide mitigation has been examined. Besides, a holistic map of hydrogen cost depending on a widespread spectrum of solar radiation and wind speed has been developed. The results demonstrate that hydrogen production rates using solar energy are staggering compared to those using wind energy, specifically for the economic zone of Ain Sokhna in Egypt. The results reveal that Hurghada has a significant hydrogen cost of 4.4 $/kg, notably by exploiting wind energy. Using solar energy, Aswan and Salalah have a distinguished hydrogen cost of 5 $/kg, while NEOM, Hurghada, Al Maktoum, and Duqm have a hydrogen cost of 5.1 $/kg. Based on environmental perspectives, exploiting solar energy can alleviate 47.6 tons/year in Aswan, while harnessing wind resources in Hurghada mitigates 77.9 tons of annual carbon dioxide emissions.

Short-Term Wind Power Prediction Based on CEEMDAN-SE and Bidirectional LSTM Neural Network with Markov Chain

Accurate wind power data prediction is crucial to increase wind energy usage since wind power data are characterized by uncertainty and randomness, which present significant obstacles to the scheduling of power grids. This paper proposes a hybrid model for wind power prediction based on complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN), sample entropy (SE), bidirectional long short-term memory network (BiLSTM), and Markov chain (MC). First, CEEMDAN is used to decompose the wind power series into a series of subsequences at various frequencies, and then SE is employed to reconstruct the wind power series subsequences to reduce the model’s complexity. Second, the long short-term memory (LSTM) network is optimized, the BiLSTM neural network prediction method is used to predict each reconstruction component, and the results of the different component predictions are superimposed to acquire the total prediction results. Finally, MC is used to correct the model’s total prediction results to increase the accuracy of the predictions. Experimental validation with measured data from wind farms in a region of Xinjiang, and computational results demonstrate that the proposed model can better fit wind power data than other prediction models and has greater prediction accuracy and generalizability for enhancing wind power prediction performance.

Optimal Design and Performance Analysis of a Hybrid System Combining a Semi-Submersible Wind Platform and Point Absorbers

Integrating point absorber wave energy converters (PAWECs) and an offshore floating wind platform provide a cost-effective way of joint wind and wave energy exploitation. However, the coupled dynamics of the complicated hybrid system and its influence on power performance are not well understood. Here, a frequency-domain-coupled hydrodynamics, considering the constraints and the power output through the relative motion between the PAWECs and the semi-submersible platform, is introduced to optimize the size, power take-off damping, and layout of the PAWECs. Results show that the annual wave power generation of a PAWEC can be improved by 30% using a 90° conical or a hemispherical bottom instead of a flat bottom. Additionally, while letting the PAWECs protrude out the sides of the triangular frame of the platform by a distance of 1.5 times the PAWEC radius, the total power generation can be improved by up to 18.2% without increasing the motion response of the platform. The PAWECs can reduce the resonant heave motion of the platform due to the power take-off damping force. This study provides a reference for the synergistic use of wave and wind energy.

Techno-economic assessment of offshore wind energy potential at selected sites in the Gulf of Guinea

Offshore wind power has been found to stand out among the most dynamic renewable energy technologies. With its long coastal line, Nigeria has an overwhelming advantage in developing marine energy resources to relieve the power crisis effectively. This work analyzed and characterized observation data of sea-surface wind speed and direction at 30-minute intervals between 1979 and 2015 at five synoptic offshore stations in the Gulf of Guinea. The seasonal variations in hourly surface wind speed and directions as well as the Weibull distribution of wind speed and wind power at 100 m hub height were examined. The wind shears, capacity factors, and accumulated energy outputs for seven offshore wind turbine types were determined for the selected locations. In addition, the economic analysis of the selected offshore turbines using levelized cost of energy was carried out, while sensitivity analysis of the total levelized cost of energy to key input parameters was further determined. The results revealed large spatial and temporal variations in wind speed and wind power in the Gulf of Guinea. The most viable offshore site for wind energy exploitation was Agbami (the deepest offshore site), while Bonny (the shallow coastal site) had the least. The findings established very good fits (having mean bias (between −0.08 ms−1 and −2.44 ms−1), percentage bias (between −0.47% and −13.98%), correlation coefficients (between 0.97 and 0.98), Chi-square (between 0.2 and 1.2), and root mean square error (between 1.2 ms−1 and 3.1 ms−1)) between Weibull distribution and the actual wind data. The wind turbines with the highest and the lowest wind power densities, capacity factors, and power outputs across the seasons and sites were V236-15.0 MW and Siemens SWT113, respectively. The levelized cost of energy was considered for the deep waters due to the moderately high-capacity factors. The highest values ranged between 101.48 and 137.12 USD/MWh at Sea Eagle with V236-15 MW and V117-4.2 MW, respectively, while the lowest ranged from 52.29 to 69.66 USD/MWh at Agbami with V236-15 MW and Siemens (SWT113), respectively. The exploitation of Nigeria’s offshore wind resources could also be dedicated to producing renewable hydrogen and can serve to meet the country’s ambitious targets set for carbon neutrality by 2060.