Development Of Wind Power Plants Research Articles

Design and Thermal Analysis of a 250 MVA HTS Transformer for Substation of Offshore Wind Farms

In Offshore Substations (OSs), using High Temperature Superconducting (HTS) transformers instead of conventional power transformers to reduce operational and construction limitations such as weight, capacity, marine pollution, and future planning can be considered as desirable. HTS transformers can reduce operating system costs in wind power plant development programs. However, OSs have specific operating conditions in fault mode that should be considered in the design HTS transformers.In this paper, a 250 MVA 33/220 KV HTS transformer is designed, and electromagnetic analysis is done in normal conditions to calculate AC loss and thence to design the cooling system. The second step, thermo-flow analysis is done by Finite Element Method (FEM) to calculate the temperature distribution of the windings. Increasing turbulence of inlet flow and creating a porous coating on the tapes are used in this transformer to increase the heat-transfer rate. lastly, the specifications of the HTS transformer are compared with the conventional transformer to give useful information to OS designers to investigate using novel construction ideas such as floating OS by HTS transformer.

Techno-economic Analysis of New Wind Power Plant Development in Southern Sulawesi Electrical Power System

Global warming due to carbon emissions has resulted in climate change, which negatively impacts the lives of living things. On the other hand, electricity demand is increasing every year due to the increasing human population, economic growth and equipment electrification. At the moment, most of the electricity generation in Indonesia uses fossil energy power plants which produce carbon emissions. PT. PLN (Persero) is a State-Owned Enterprise tasked with managing the electricity system in Indonesia. PT. PLN (Persero) through the General Plan for Electricity Supply (RUPTL) for 2021-2030 is targeting the construction of New and Renewable Energy Power Plants. One of possible plan is the Wind Power Plant (WPP) construction in the Southern Sulawesi electrical power system. The use of WPP is expected to reduce carbon emissions. However, the integration of WPP causes other problems in the existing system such as dropped voltage, increased equipment loading, increased short circuit current and decreased stability. So, it is necessary to conduct a study on the effects of integrating WPP into the existing system. Using DIgSILENT Power Factory software, Load Flow, Short Circuit and Transient Stability simulations were carried out. Then an economic analysis was carried out including calculating net present value (NPV), internal rate of return (IRR), profitability index (PI), payback period (PBP) and levelized cost of energy (LCOE. The use of WPP at a certain capacity will not disrupt the stability of the system's power because it is still supported by the fast response generators in the system during variable WPP output. Also voltage drop, equipment loading and short circuit current will not exceed the design value of the system. From financial aspect, with certain assumptions, WPP development can be proven to be economically feasible.

Site suitability assessment for the development of wind power plant in Wolaita area, Southern Ethiopia: an AHP-GIS model

The primary driver of economic growth is energy, predominantly derived from fossil fuels, the demand for which has experienced a significant increase since the advent of the Industrial Revolution. The emissions of hazardous gases resulting from the utilization of these fuels have been well acknowledged, therefore exerting a notable impact on the environment. In the context of Ethiopia, it is observed that despite the presence of ample renewable resources, the accessibility to power continues to be constrained. In order to effectively tackle this issue, it is imperative to redirect attention towards the utilization of renewable sources, such as wind energy, as a means of enhancing the existing power grid infrastructure. The present study used geospatial tools to evaluate the appropriateness of the Wolayita region for the establishment of a wind power facility. The process of site selection is guided by multiple factors, and a multi-criteria approach is facilitated through the utilization of Geographic Information System (GIS). The evaluation of seven characteristics was conducted utilizing the Analytical Hierarchy Process (AHP) methodology, which involved pairwise comparisons and weighted scoring. The process of suitability mapping involves the classification of locations into four distinct categories, which range from the most suitable to the least suitable. The findings demonstrate that the area of 0.628% (28.00 km2) is deemed the most suitable, while 54.61% (2433.96 km2) is considered somewhat acceptable. Additionally, 0.85% (37.85 km2) is identified as the least suitable, leaving a remaining 43.91% (1060.00 km2) that is deemed unsuitable. The central, northwestern, and southern regions are identified as optimal geographic areas. The results of this study facilitate the process of investing in renewable energy, thereby assisting Ethiopian authorities and organizations in promoting sustainable development. This report serves as a crucial reference point for the wind energy industry.

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

Development of a mobile wind power plant for power supply of the troops

The scientific article was published as part of the implementation of the scientific project of grant funding for 2022-2024 IRN № АР148039/0222 «Scientific and technical substantiation of the parameters and development of a wind power plant for the electric power supply of the objects of the Armed Forces, other troops and military formations of the Republic of Kazakhstan» (the study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan). The article presents the results of the development of a mobile wind power plant for the energy supply of troops. In the Armed Forces of Kazakhstan, there is a need to create and implement technical devices that convert wind energy into electrical energy and have no analogues. As a result of the research, a mobile wind power plant was developed, the main element of which is a pair of identical vertically arranged curved blades. The developed design can be used in any regions of Kazakhstan. The wind plant is not tied to the weather characteristics of the area, it is able to operate in low light and low winds. It can be used to ensure a guaranteed minimum power supply to military facilities in areas of centralized power supply experiencing a shortage of energy, to prevent damage from emergency and restrictive shutdowns. In addition, to provide electricity to both technological military consumers: communication equipment, radar installations, electric drives of combat systems, lighting installations, and technical military consumers: hospitals, military camps, training centers and training grounds, military facilities support units and units located in shelter, tent cities, etc.

Evaluation of wind measurement methods for determination of realistic wind shear: A case study in Aksaray, Turkey

Wind energy has become a large and important market in Turkey. Wind resource assessment and hub height extrapolation are the most analyses during wind power plant development. Wind shear is a critical parameter for wind speed analyses in wind energy power plant projects. The study covered measurement analyses of LIDAR (Light Detection and Ranging) and wind measurement mast system data that were compared as common in literature. Then wind shear formation and analysis factors were realistically evaluated with the multi-criteria method first in the literature using wind speed, wind direction, WSC, roughness, turbulence intensity (TI) and correlation factor. Under 100 m measurements were extrapolated to 101 m and upper 101 m. The predicted 245 pieces of the data set by using power law and log law and the measured data set were correlated with an anemometer and the LIDAR measurements to figure out an efficient prediction method. 20 pieces of wind shear coefficients (WSCs) were calculated using mast-mast, LIDAR-LIDAR, mast-LIDAR and LIDAR-mast wind speed measurement. Then, these WSCs were applied and tested for various measured wind speeds and the instantaneous wind speed was predicted with WSC values. Simultaneously, the log law method was repeated for different roughness values and the ideal roughness value was calculated for the site specifications. These predictions provided specific information about the height of wind shear and TI height supported by LIDAR and anemometers. In comparing data estimated by the power-law and log-law methods with measurements, good and acceptable results were obtained with more than a 0.999 correlation coefficient.

Prediksi Kecepatan Angin Jangka Menengah dengan Artificial Neural Network untuk Estimasi Daya Listrik Tenaga Angin (Studi Kasus: Kota Sabang)

Indonesia, as a country at the equator, has a very large renewable energy potential that can be used as a source of electrical energy. Electricity consumption in Indonesia, especially in Aceh, continues to increase annually because of population growth and increasing economic needs. Recently, the construction of power plants has been considered to be environmentally friendly and economical. One of the efforts that can be made is the development of wind-power plants. The availability of certain wind speeds was expected. Therefore, accurate prediction data must be used as the basis for building wind power plants. To increase the accuracy of wind speed prediction by looking at the error rate in predicting the amount of wind speed generated using an Artificial Neural Network with feed-forward and feed-backward functions from the back propagation algorithm (BPNN). The results of the application using the Neural Network algorithm with a back propagation Neural Network (BPNN) to predict wind speed show that the Neural Network algorithm can predict wind speed with an error of 0.0036. In July 2021, the estimated energy demand is 81.5 KWH.

Суждение о формировании экономического и технологического развития ветроэнергетики

Russia’s energy security is a critical infrastructure for economic and national integrity. The study examines the possibilities for creating alternative generating energy capacities using renewable energy sources – wind farms. The attention of the world community in climate conservation on a planetary scale is noted, which is expressed in multilateral agreements and other legal acts that make up the international institutional framework for the development of renewable energy. It is indicated that the presence of high technologies and exceptional competencies of the world’s leading companies create conditions for the production of unique wind turbines and the development of a software and hardware system for managing wind farms. On the basis of technologies developed in world practice for the construction of wind turbines and wind farms. A proposal was made on the need to develop high-tech industries to create wind power plants of various capacities for the climatic conditions of Russia, which will increase the economic and technological potential of the country’s regions. It has been determined that the energy efficiency largely depends on the availability of innovative technologies, research and development, highly qualified specialists, and financial resources of companies. The largest modern manufacturers of wind turbines in economic regions, the trends of their further expansion are presented. The purpose of the study is to assess the state and dynamics of the prospective development of wind power plants in the global energy sector.

Хищные птицы и ветроэнергетика в Казахстане: какие перспективы для орлов?

Хищные птицы и ветроэнергетика в Казахстане: какие перспективы для орлов?

Wind Power Plant Site Selection using Integrated Machine Learning and Multiple-Criteria Decision Making Technique

The growing demand for clean and sustainable energy sources has driven countries around the world to explore renewable energy options, including wind power. This research focuses on the use of machine learning techniques to optimize the site selection process for wind power plants in the Philippines. The study aims to address the challenge of identifying suitable locations for wind power plant development, which requires the assessment of various environmental and socio-economic factors. The research utilizes various datasets, including wind speed and direction, topography, land use, population density, and infrastructure availability. Additionally factors on The datasets was acquired to the Maps that contains road network, urban areas, protection areas, slope, wind speed, water courses, natural disasters and transmissions lines. These datasets are processed and analysed using SVM machine learning algorithms to identify the most suitable sites for wind power plant development. The study results indicate that machine learning techniques can provide a more accurate and efficient approach to wind power plant site selection compared to traditional methods. The model can identify areas with high potential for wind energy generation, taking into account various factors that influence the feasibility and profitability of wind power plant development. The research findings are expected to provide valuable insights for policymakers, investors, and other stakeholders involved in the renewable energy sector in the Philippines. The use of machine learning techniques can facilitate the identification of optimal locations for wind power plants, leading to more efficient and effective renewable energy development in the country.

A novel probabilistic modeling framework for wind speed with highlight of extremes under data discrepancy and uncertainty

Wind power is serving as a rapidly growing renewable energy resource for global sustainable development, and thus an important task for optimal utilization of this resource is to accurately describe and estimate the uncertain wind speed. In this regard, this paper proposes a novel probabilistic modeling framework for an accurate description of wind speed with the highlight of extremes, where two sources of discrepancy inside wind speed data are taken into account. One is the discrepancy between the non-tail part and the tail (extremes) of wind speed data, which can separate the whole dataset into homogeneous subsets. Then, a dual-model estimation model relying on the existing probability distributions and machine learning algorithm is proposed to facilitate an accurate description of a feasible region with extremely high wind speed values. Another source of the discrepancy lies in the collected data in various lengths of time series, and thus the estimated model should be continuously changed to adapt to the ever-growing time series. As a case study, this proposed framework is verified in a real-world wind speed dataset, where three scenarios with different time lengths are designed for deep investigation. It is found that: (1) Extremes of wind speed can be well separated in the proposed probabilistic modeling with a theoretical derivation of the boundary. (2) The distribution equation-based method can easily provide a more precise description of the extremes than the support vector regression (SVR)-based model, reaching a smaller Bayesian risk and maximal value of the loss. (3) Probabilistic modeling depends on the length of the time series of data collection. (4) Additional experiments under some degree of uncertainty are set to verify the robustness of the proposed method. The novelties lie in the theoretical boundary identification and automatic description of high wind speed distribution, which can potentially provide data-driven evidence for the development of wind power plants.

Adaptive neural dynamic surface control for uniform energy exploitation of floating wind turbine

To avoid the harmful effects of global warming on the earth planet and its atmosphere, the expansion of wind energy consumption based on new control techniques leads to improved energy capacity. The development of wind power plants on the sea is more efficient owing to the stronger wind flows in comparison with the onshore structure. Furthermore, stable installation of the offshore wind energy base meets the energy management requirements of today's consumers. As a result, dependency on fossil fuels as the main source of global warming decreases. The feedback control system and on-line sensor signals provide the stability and increased efficiency of the floating wind turbine. The aggressive environment and large size structure of the turbine lead to entering uncertainty in the turbine model and exogenous noises that should not be effectively compensated by conventional control methods. Therefore, a radial based functional neural network (RBFNN) controller is proposed to estimate and compensate the effect of uncertainty on feedback control of the wind turbine. For comparison purposes, a linear quadratic regulator (LQR) state feedback is also developed for optimal control of the floating wind turbines. The neural network adaptively determines the upper bound of uncertainty/noise. Therefore, conservative high-gain control actions to achieve robustness of the classical feedback controllers against structural deviations of the turbine body are decreased. In our newly proposed adaptive control algorithm, using a basic raised cosine function guides to restore the computational efficiency of RBFNN. With the Lyapunov-based stability analysis, the final limits of the closed-loop system and the convergence caused by the terminal sliding mode (TSM) tracking error are determined. Detailed software simulations of both the LQR and the designed RBFNN control systems indicate the superiority of the neural network-based approach.

Green marketing as a tool for promoting wind energy technologies

Currently, one of the urgent problems is environmental sustainability, the absence of which can lead to a deterioration in the living conditions of future generations of people. To ensure environmental sustainability, it is necessary not only to improve production technologies, but also the use of green (environmental) marketing. The purpose of this marketing is to focus the market on products produced using environmentally friendly technologies. One of the promising green technologies is wind energy, which does not pollute the air, does not affect the climate and is mobile. The article considers the need for active use of marketing of green technologies in the field of wind energy and analyzes the development of alternative technological solutions in this area. The object of the study is wind energy as an energy industry that provides resistant ecosystem homeostasis and environmental sustainability; the subject of the study is green marketing within the framework of the concept of sustainable development. The advantages of using green marketing by wind energy enterprises are the focus on developing the brand image and reputation of the manufacturer; the implementation of corporate social responsibility in the field of energy conservation; increasing competitive advantages in the market; increasing the profitability of production and operation. The classification of wind power plants (wind turbines) according to the orientation of the wind-receiving rotor is given. The operation of horizontal axis and vertical axis wind power plants is compared. Alternative technical solutions in wind turbine constructions using modern knowledge in the field of composite materials and mathematical modeling methods are presented. It is shown that increasing energy efficiency is a key factor in ensuring the profitability of the use of wind turbines. The main trends in the development of wind power plants, both highpower wind farms and small local wind turbines have been identified. Marketing management, which can be implemented through the cooperation of technology startups and the state on the principles of mutually beneficial partnerships, is the instrument for successful product launch into the green energy market in modern conditions.  

Effect of Wind Turbine Blade Material Type on Generated Electric Power

Electric power as an energy system has a very important role in the economic development of a country. Therefore, now many researches are conducting developments in energy generation research and one of them is the development of wind power plants or wind turbines. The purpose of this study was to determine the effect of the type of blade material used in wind turbines on the varying electrical power produced. The blade material used in this material is pine wood, fiberglass/epoxy composite and fiberglass/coconut fiber/epoxy. The tests carried out in this study were to measure the rotation of the rotor, measure the current, voltage and power for variations in wind speed. The wind speed used is 3 m/s 4 m/s 5 m/s 6 m/s. blade with fiberglass/epoxy/coconut fiber composite material gets high rotational results compared to other materials, at a wind speed of 6 m/s it can produce a rotation of 1241,156 rpm and the electrical power generated is 3,545 W.

Wind speed spatial estimation using geostatistical kriging

Accurate wind speed prediction plays an important role in the planning and development of wind power plant. Wind speed prediction can reduce the impact of wind power grid connection and improve the control of wind power systems. In this study, wind speed is considered as a geographical variable. We firstly used exploratory methods to examine the spatio-temporal dependence on wind field. The variogram was taken into account in analysing the spatial structure in the rectangular grid. Then the exponential model was adopted to fit the anisotropic feature of variogram. The de-trended data have been computed by using a geostatistical kriging estimator. The results were compared with the leave-one-out cross-validation (LOOCV) method. The accuracy of the proposed method was verified to obtain the best estimated results.

Evaluation of wind power potential for selecting suitable wind turbine

India is a developing nation and heavily spends on the development of wind power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of Ennore site using wind data collected over a period of two years by three parameter Weibull distribution. The Weibull parameters are estimated using maximum likelihood, least square method and moment method and the accuracy is determined using R2 and root mean square error values. The site specific capacity factor is calculated by the mathematical model developed by three parameter Weibull distribution at different hub heights above the ground level. At last, the wind energy economic analysis is carried out using capacity factor at 30 m, 40 m and 50 m height for different wind turbine models. The analysis showed that the site has potential to install utility wind turbines to generate energy at the lowest cost per kilowatt-hour at height of 50 m. This research provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine.

Offshore wind power assessment on the western coast of Thailand

This paper presents an offshore wind resource assessment and offshore wind power feasibility analysis on the western coast of Thailand using coupled mesoscale atmospheric and microscale Computational Fluid Dynamics wind flow modeling, along with a climatic database. Offshore wind maps at elevations of 80 m, 90 m and 120 m above mean sea level (amsl) are presented and validated with measured wind datasets gathered from nine met masts installed along the coast of the Andaman Sea and the Strait of Malacca on the western part of Thailand. Results show that, at an elevation of 120 m amsl, the northern region near Myanmar is characterized by wind speeds in the range of 5.5 to 6.0 m/s, while the area around Phuket Island has wind speeds in the range of 4.6 to 5.3 m/s. In line with the Thai energy policies for wind power plant development, the annual energy production, the capacity factors, the levelized cost of energy (LCOE), the CO2eq emission avoidance, and the required Feed-in-Tariff (FiT) are analyzed for wind power plants integrating 3.3 MW, 8.0 MW and 9.5 MW offshore wind turbine generators. Results show that offshore wind power plants with 3.3 MW wind turbine generators could produce over 13 GWh of electricity per year under the Very Small Power Producer (VSPP) scenario for 10 MW wind power plants. For its part, 50 MW wind power plants under the Small Power Producer (SPP) scenario could produce 68 GWh/yr, and nearly 123 GWh/yr for SPP wind power plants with 90 MW of installed capacities. With capacity factors in the order of 16%, the lowest LCOE is 0.188 USD/kWh and the CO2eq emission avoidances reach 774 tonnes CO2eq per year. Finally, the required FiT to sustain the development of VSPP offshore wind power plants in the vicinity of Phuket Island is in the range of 0.314 to 0.688 USD/kWh.

Comparison of 1-D seismic site response analysis tools for layered liquefiable deposits at an offshore windfarm site

Various offshore wind farms have been proposed in the Taiwan strait with a long-term target of installing 4.2 gigawatts by 2030. The proposed projects will be in areas with various known faults and areal seismic sources which should be accounted for in design. A reliable prediction of site response for soil deposits is crucial for seismic loading evaluation of existing energy structures and for design of new structures including offshore wind farms in seismically active regions. This paper presents generic results of 1-D site response analyses based on work performed for an offshore wind power plant development site in the Taiwan strait. The deposits in the project area generally consist of layered deposits with liquefiable layers. The site response analyses were initially performed using two different open-source tools, DEEPSOIL and Cyclic 1D. Both equivalent linear and non-linear approaches were adopted for the analyses and additional evaluations were subsequently performed using PLAXIS 2D for comparison with the results from the open source tools. The results from the different tools were systematically compared and provided useful insight on peak ground (seabed) acceleration, acceleration time histories and shear strains at specific depths and design response spectra. The paper includes a discussion of the sensitivity of the outputs to various input parameters for each of the tools utilized in the analyses and the suitability and limitations of each approach for assessing liquefaction potential are also discussed.

Investigation of accurate location planning for wind farm establishment: a case study

Purpose Wind as a major source of renewable energy has received tremendous attentions due to its unique features to reduce carbon emission and also to keep the environment safe. Nevertheless, to use wind energy properly, the environmental circumstances and geographical location related to wind intensity should be considered as a priority. Different factors may affect the selection of a suitable location for developments of wind power plants; thus, these factors should be considered concurrently to identify the optimum location of wind plants. Design/methodology/approach In this study, first, basic data envelopment analysis (DEA) was used, then dual DEA was used and, finally, Anderson Petersen (AP) model of dual DEA was selected to prioritize cities or decision-making units (DMUs). Numerical Taxonomy (NT) method was also used to assess the validity of AP dual model in DEA. The prescribed approach was applied for five cities in East Azerbaijan province of Iran. Findings The results indicate that wind power as a renewable energy can be harnessed in few cities, and the ranking by DEA illustrated that the city of Tabriz is the first priority. Practical implications Low environmental degradation effects in comparison to other methods and the ability to utilization at a widespread level include the benefits of using wind energy in the generation of electricity. In this regard, the study of relevant potentials and finding suitable locations for the deployment of wind energy utilization equipment are essential. Using DEA method helps us to choose optimal locations according to different criteria. Social implications Wind energy is justifiable in reducing social costs in comparison with fossil fuel plants, which includes negative effects, and its electricity can be used as a sustainable energy in the country's economic, social and cultural development. Originality/value For identifying the most proper location for development of wind power plants in Iran, DEA is applied for the first time to prioritize the suitable locations for installations of wind turbines among five different cities in the East Azerbaijan region. A number of crucial factors including land price, distance to power, rate of natural hazards, wind speed and topography are considered for location optimization of wind turbines for the first time. Also, to validate the results of DEA method, NT method is used to assess the validity of AP dual model in DEA.

COMPARISON OF HINT WIND TINES OF AIRFOIL TYPE NACA 4412, NACA 23012, and NACA 16-212 USING QBLADE SOFTWARE

Wind energy as one of the new renewable energies that has considerable potential in Indonesia is known by the rapid development of wind power plants in Indonesia. The windmill blade which is one of the main components of the windmill has a role as the conversion of wind potential energy into motion energy to eventually become electrical energy that is influenced by the shape of the windmill blade of the windmill. NACA (National Aeronautical Committee Advisory) in charge of aeronautics has standards regarding varying airfoil shapes. A comparison of variations of 4-digit type airfoils (NACA 4412), 5 digits (NACA 23012) and series 16 (NACA 16-212) to determine the value of Cl / Cd from the variation of NACA airfoil types. The results of simulations carried out using Qblade software showed that the value of Cl / Cd to the highest alpha of the three types of airfoils was NACA 4412 with a value of 134, alpha 6 and the Cp value for the highest TSR was 0.44 at TSR 5.5. Furthermore, the NACA 4412 airfoil blades can be developed by making lighter material variations so that the windmill blades are easier to spin so that the resulting power becomes more maximal.