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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]

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]

The accurate prediction of the flow field characteristics of complex mountains is of great practical significance for the development and construction of wind farms, but it is not yet fully understood. The main purpose of this study is to propose a method for the study of flow field characteristics under complex mountain conditions, which can optimize the boundary conditions required for numerical simulation through the wind acceleration ratio and, at the same time, couple the numerical simulation and wind measurement data to reflect the real mountain flow field distribution. The results show that the proposed method has good applicability in complex mountain wind farms, can reproduce the real flow field distribution, and has a certain practical value. Wind speed distribution and turbulence intensity are greatly affected by boundary conditions such as wind speed and wind direction and are also affected by the shielding effect brought by terrain changes. The contrast between 120° and 150° wind direction is more obvious. When the incoming wind moves to the top of a mountain or the ridgeline, it will form a low-speed wake area behind it, resulting in reduced wind speed, increased turbulence intensity, and an unstable flow field. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is not merely a technical option; it is a fundamental element in making and shaping policies for achieving sustainable development in the energy sector. This achieves a degree of integration among economic, environmental, and social urban policies in the secondary Najaf region. The use of renewable energy for wind farms, contributes to providing energy for human activities and various processes, by harnessing kinetic energy from wind movement to generate electrical power through the operation of wind turbines, wind energy undergoes a transformation from mechanical energy to electrical energy, meeting the energy demands of urban centers and rural areas. Therefore, this study aims to introduce a renewable energy source from wind energy, as a solution to the current and anticipated electricity deficit in the study area. In addition to contributing to urban development, agriculture, environmental conservation and related fields. This research adopts for multi-criteria decision-making (MCDM) methodology within the geographic information system (GIS) to identify the most suitable spatial location. As a result, the study has identified appropriate and efficient sites for wind farms, through establishing planning and design criteria and standards for wind farm development. The proposed design includes a well-planned wind farm covering 40.3 Km2, equipped with 99 turbines, capable of producing 198 Mw of electrical energy to alleviate shortages and meet future energy demands. [ABSTRACT FROM AUTHOR]

Currently, qualified generating stations powered by renewable ener gy sources (hereinafter referred to as RES) are becoming increasingly popular in the electric power industry. Wind farms and solar generating panels have become mostly common in the modern world. Russia is a vast country that offers many potential locations for RES facilities. The аrctic zones attract special attention. However, having chosen a potential location for the construction of such an object, it is necessary to analyse the effectiveness and feasibility of the investment project. The purpose of this study is to consider the current state of the Murmansk region’s energy system for further determination of the probability of new energy projects developing there. In this regard, the wind energy potential of the region has been assessed, and the forecast of electricity consumption for the period from 2024 to 2029 has been performed. The authors have analysed justifications and possibilities for the construction of wind power plants on the territory of the Kola Peninsula as an alternative to stations powered by hydrocarbon fuels. It has been found that the existing opportunities in the Russian region are favourable for the realisation of new wind farm on its territory. A comparative analysis of the Murmansk region and neighboring territories has shown that this area is suitable for implementing such investment projects.

The wind power industry is increasing worldwide every year. Thus, obtaining timely and detailed information on wind farms’ number and spatial distribution is critical for quantitatively estimating wind energy utilization and for planning the construction of new wind farms. Therefore, this study proposes a method for quickly identifying wind farms in a large-scale area. Given that wind farms mainly comprise individual objects such as wind turbines and substations, we labeled sample images of wind turbines and substations on a global scale. Then, these sample images are used to train a target recognition model and an object classification model and detect the specific locations of wind turbines and substations in the study area. Additionally, we deeply analyzed the location features of the wind turbines and further improved the recognition accuracy based on these known features using geographic constraints. Based on the location information of wind turbines and substations, a clustering model organizes them effectively into complete wind farms. A comprehensive evaluation of the clustering model verifies its scientific validity and reliability. Specifically, this framework was systematically tested throughout Vietnam with remarkable results, using high-resolution historical images provided by Google Earth. Indeed, our framework achieved 90.45% recall and 95.73% accuracy for wind turbines and 81.37% recall and 78.96% accuracy for substations. Finally, we successfully obtained the spatial location and distribution of 15 completed wind farms, demonstrating that the proposed scheme can quickly and accurately identify wind power plants in a large-scale area, which supports wind power management and energy utilization planning.

Scotland's staple global exports will soon include renewable offshore energy, so-called green energy. Already, Scotland produces more electricity than it currently needs. The future story is about connectivity and the transformation of the National Grid which directs electricity supplies into homes and businesses. Scotland's offshore renewables ambition has been significant in putting the nation in the green energy spotlight and attracting the attention of international investment groups. The concept of a Just Transition – creating tens of thousands of new local jobs and employment – requires a workforce to develop the skills to become productive members of this new sector. A Just Transition will require a great deal of fresh thinking, but too many Scots are unprepared for the change, and too few are set to truly benefit. Who will be the beneficiaries of this revolution? Only time will tell. [ABSTRACT FROM AUTHOR]

The small-signal stability of high voltage direct current (HVDC)-connected wind farms (WFs) is a challenging issue in modern power systems. The relative stability, i.e., the stability margin, of such a typical multiple-input multiple-output (MIMO) system is quite difficult to be quantified. This paper evaluates the relative stability of HVDC-connected WFs using a new stability index based on the ν-gap metric. We first develop a MIMO model represented by a transfer function matrix of the HVDC-connected WFs. Then, a new stability index, i.e., the robust stability margin, based on the ν-gap metric is proposed to quantify the relative stability of such a MIMO system. Finally, we propose a method to compute the stable region of control parameters based on the corresponding stability criterion of ν-gap metric. Case studies are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, the potential impact of wind farm locations on the sustainable development of cities in Poland was evaluated, considering the availability of wind-generated electricity. We analyzed 37 cities in Poland with populations over 100,000. Research indicates that wind farms located 30–80 km from large cities perform best in terms of generating capacity, while greater distances increase transmission costs and energy losses. In Poland, wind farms are primarily situated in the northwestern regions, posing challenges for energy transmission to the southern cities, which are the main centers of energy consumption. The findings show that wind farms with the highest generating capacity are generally about 50 km from major cities. Key factors influencing wind farm locations include technical criteria, economic feasibility, environmental impact, public opinion, and the availability of transmission networks. Sustainable development of wind farms requires strategic cooperation between urban and rural municipalities, joint spatial planning, coordinated land acquisition, and the exchange of know-how. [ABSTRACT FROM AUTHOR]

The present research aims to select optimal areas for the installation of wind farms in the north-eastern part of Cuba. The research is based on the free software QGIS, Hierarchical Process Analysis, databases of the information of the alternatives and criteria and Geographic Information Systems (GIS), which makes it possible to know the places where these farms will be installed. In addition, experts were consulted to obtain the weights or level of importance of the selected criteria, such as distance to ports, distances to common roads, distances to population centers, to electrical grids and finally the wind speed. As a result, a mathematical conceptual model was obtained for the selection of optimal zones for the installation of wind farms in the eastern north of Cuba, by means of the MCDM and GIS methods, where it was determined that, within the evaluated alternatives of wind farms, Gibara III is the optimal one. These models will allow the development of wind projects in the eastern region of Holguin, and to be able to manage human, financial and material resources. [ABSTRACT FROM AUTHOR]

A theoretical model is proposed to analyze the soil settlement-induced negative skin friction and bending moment on a batter rock-socketed pile (BRSP). A series of model tests were conducted to verify the accuracy of the proposed theoretical model. Parametric studies are conducted to investigate the effects of the inclined angle and diameter of BRSP, and the consolidation settlement of surrounding soil on the bending moment and skin friction on the BRSP. Under the settlement of surrounding soil, the axial forces and the bending moments of BRSP nonlinearly distribute in the clay layer and reach their maximum magnitudes at the rock-soil surface and rapidly attenuated to zero in the rock layer. The deflections of BRSPs decrease linearly along the pile embedded in the clay layer and decrease to zero at the rock-soil interface. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Patagonian region of Argentina has great wind potential. In this geographical area of complex terrain, the local wind is influenced by the proximity of the Andes Mountain chain, and it is very intense and turbulent. The wind profiles, turbulence intensity, and average wind speeds at the site do not meet the recommended values in the standards. This issue could have a significant impact on the design loads for structures installed in the region. The objective of this work was to compare the behavior under extreme wind load on different types of towers for multi-MW wind turbines in situ. For this, a hybrid tower, a concrete tower, and a steel tower of equal dimensions were compared. Additionally, we analyzed the influence of the cross-sectional shape of concrete on hybrid towers. The flow pattern around the structures was studied using a solid wall model. As for the towers, we implemented a stress–strain elastic analysis. We calculated the stress fields, displacement fields, and aerodynamic behavior for each tower. We conclude that hybrid towers present the most optimal behavior. Among the different cross-sectional shapes analyzed for this type of tower, we found that all of them show advantages and disadvantages, with the circular section being the one that has the highest average performance from the resistance and aerodynamic standpoint. [ABSTRACT FROM AUTHOR]

With the expansion of green energy, more and more data show that wind turbines can pose a significant threat to some endangered bird species. The birds of prey are more frequently exposed to collision risk with the wind turbine blades due to their unique flight path patterns. This paper shows how data from a stereovision system can be used for an efficient classification of detected objects. A method for distinguishing endangered birds from common birds and other flying objects has been developed and tested. The research focused on the selection of a suitable feature extraction methodology. Both motion and visual features are extracted from the Bioseco BPS system and retested using a correlation-based and a wrapper-type approach with genetic algorithms (GAs). With optimal features and fine-tuned classifiers, birds can be distinguished from aeroplanes with a 98.6% recall and 97% accuracy, whereas endangered birds are delimited from common ones with 93.5% recall and 77.2% accuracy. [ABSTRACT FROM AUTHOR]

Wind farms play a crucial role in renewable energy generation, but their reliability is often compromised by complex environmental and equipment conditions. This study proposes a field of view enhanced convolutional neural network (CNN) model for fault diagnosis and prevention in wind farms. The model is developed by collecting and processing wind farm fault data and compared with support vector machine (SVM) and k-nearest neighbor (KNN) models. The results showed that the proposed CNN model outperformed the other models in terms of convergence speed (17 iterations to reach the minimum loss), fault diagnosis accuracy (99.3% and 99.2% for inner and outer circle faults, respectively), and stable power output improvement. The model's application to maintenance scheduling and economic benefit analysis in a real wind farm case demonstrated its high consistency and accuracy in fault prediction and maintenance optimization. The proposed approach has the potential to enhance wind farm reliability, efficiency, and economy by enabling accurate fault diagnosis, early warning, and preventive maintenance. [ABSTRACT FROM AUTHOR]

Planning for the expansion of generation and transmission infrastructure, with a focus on integrating wind farms is presented in this study according to the goals of economic efficiency, operational performance, security, and reliability of the transmission system operator. The approach incorporates a bi-level optimization framework, with the upper level outlining the formulation of power system expansion planning to reduce construction and operational costs while adhering to the investment budget limits. In the lower-level model, which economic reliable-secure functioning is formulated for the transmission network. The objective function of the problem aims to minimize operational costs, energy losses, and anticipated energy not supplied, and the voltage security index. The constraints of this problem include AC optimal power flow model, security, and reliability limits. Scheme extracts a convex-linear model for the formulation using the conventional linearization technique. Pareto optimization driven by the aggregation of weighted functions results in a single-objective framework for the lower-level problem, and the Karush-Kuhn-Tucker technique presents a single-level model for the scheme. The approach utilizes stochastic optimization has been adopted to model load, wind farms, and network equipment availability uncertainties. Finally, the study cases yielded numerical findings that showcase the efficacy of the proposed scheme in achieving the desired economic, operational, security, and reliability status within the transmission network. This is particularly true in situations where there is appropriate generation and transmission expansion.

Nowadays, the production of renewable energy is increasing rapidly due to its enormous potential and environmental advantages. Still, the addition of renewable energy to the grid has resulted in some volatility in the electrical system. In this work, the national grid of Ethiopia is used as an example to examine the impact of significant wind power integration on grid stability. In particular, issues with voltage stability in both steady-state and emergency scenarios are taken into account for the network. The dynamic modeling of the wind farm is taken into consideration for contingency-based analysis, and the whole nation's power network, including the largest wind farm in the nation, Adama-II, is modeled for base-case analysis using MATLAB's built-in PSAT software. The result indicates that the bus voltages are within an acceptable standard voltage range for the base-case system. Nevertheless, the wind farm will be disconnected from the network in compliance with the global manufacturer's guideline in the case of a three-phase fault at the network point of common coupling (PCC), where the voltage at PCC is equivalent to 0.045 per unit voltage. The results also demonstrate that the voltage profile throughout the whole nation power network is lower when there is a problem at PCC. As a result, as Ethiopia is building several huge wind farms, it is advised that fault detection and control methods be thoroughly designed before connecting the major wind farms to the grid.

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The multi-objective economic load dispatch problem (ELDP) with non-smooth cost functions and ramprate limits presents a challenging optimization task in power systems. This paper proposes the use of a modified cheetah optimizer (MCO) that incorporates opposition-based learning (OBL) and a dynamic adaptive weighting factor to efficiently solve this problem. The simulations are conducted on standard test systems using MATLAB programming. A comparative study is performed, evaluating the performance of the MCO against basic CO and other similar heuristics. The results demonstrate the effectiveness of the MCO in achieving optimal solutions for the multi-objective ELDP with non-smooth cost functions and ramp-rate limits. The proposed approach offers a promising solution for addressing the complex optimization requirements in power system operation and planning. The optimal cost is determined using multi-criterion optimization (MCO) in 3-bus system as $6,838.6434/h, $7,738.789/h, and $8,252.033/h for 700 MW, 800 MW and 850 MW demand levels respectively. The optimal cost is evaluated as $17,988.96/h for the 13-bus test system considering a total demand of 1800 MW. The optimal cost is evaluated as 121960.30 $/hr, for the 40-bus test system considering a total demand of 10500 MW. These outcomes demonstrate the efficacy of MCO in resolving the ELDP with generator and valve controls. [ABSTRACT FROM AUTHOR]

As an important migratory bird habitat along the East Asian-Australasian route, the coastal wetlands along the Yellow Sea have experienced significant human losses and threats due to the impact of wind farms. In this study, the radar data was adopted to examine and analyse the spatial and temporal changes of the human-made characteristic areas that caused the change of the migration route of birds in the Yellow Sea from 2015 to 2022. The results show that the areas of impact zones in the study area on water of the Yellow Sea, during the last 8 years, increased 14 times, from 35.7 km2 to 506.3 km2. The areas of impact zones in the study area on land, during the last 8 years, increased almost two times, from 303.4 km2 to 544.2 km2, which also has a serious impact on the number of migratory birds. Therefore, China should carefully evaluate the impact and potential threat of domestic wind farms under operation and construction on birds and other wildlife, and provide scientific solutions for the site selection of new wind farms. [ABSTRACT FROM AUTHOR]

Wind energy has emerged as a pivotal practice in the contemporary energy landscape, generated through gridconnected power sources aligning with the vernacular principles of systemic approaches. This study explores the surge in initiation rates, offering insights into various factors impacting sustainable electricity production. Intriguingly, this research delves into the intricacies of managing the variability and uncertainty inherent in energy demand, catalysing the integration of grid-based solutions that enhance sustainability. It probes the dynamic nature of power supply paradigms, revealing a journey of continuous enhancement by applying cutting-edge resource methodologies. Amidst the backdrop of global shifts in electricity dynamics, this study uncovers the profound implications of energy depletion and wasteful consumption practices, spotlighting a burgeoning movement towards optimising grid electricity resources on a macro scale. The intricacies and nuances of power supply challenges are comprehensively dissected, offering valuable insights. Furthermore, the study explores the pivotal role played by information technology innovators in consolidating the predictability of wind energy, augmenting its viability. It also aligns with forward-looking reviews, underscoring the actionable strategies taken. The culmination of these efforts not only enhances predictability but also unlocks a spectrum of reflective and adaptive resources in wind energy utilisation. [ABSTRACT FROM AUTHOR]

The project highlights the wind energy and the process followed in the wind farms in order to generate the energy by using wind power and wind capacity as well. Moreover, it has been observed that wind energy is also considered one of the most effective electrical energy sources. The application of wind energy can be beneficial for different aspects of the business sectors of different countries across the globe and this is possible because of its cost-effectiveness. Furthermore, this study encompasses the strategies employed within wind farms to preserve and efficiently harness wind power for the generation of electrical energy. Notably, the project delineates the utilization of a diverse array of instruments, each instrumental in the conversion of wind power into valuable wind energy. Beyond the realm of technology, wind farms grapple with a spectrum of formidable challenges, stemming from the inherently capricious nature of wind. In addition, various issues concerning power quality and the stability of the power system have also been identified within these wind farms. To ameliorate these multifaceted challenges, the project introduces a range of meticulous control measures for implementation. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paradigm shift towards sustainable energy sources has propelled research into enhancing the efficiency and reliability of power systems. This study introduces an advanced methodology for optimal power flow (OPF) by integrating the skill optimization algorithm (SOA) with considerations for open-access trading of wind farms and the integration of electric vehicle (EV) fleets. In order to improve exploration features of SOA, opposition-based learning (OBL) is used for diversifying the population. The proposed ISOA-based OPF model addresses the optimization of power flow in a multi-objective framework, aiming to minimize generation cost and minimize transmission loss while accommodating the open access trading between wind farms and EV fleet demands. The incorporation of open-access trading enables the effective utilization of surplus wind energy among interconnected power systems, fostering grid resilience and sustainable benefits. Simulation results on standard IEEE 30-bus and 57-bus test systems validate the efficacy of the proposed approach, showcasing improved system performance, reduced cost and power losses, and enhanced utilization of renewable resources in modern power grids. In the IEEE 30-bus, fuel costs are $803.13/hr standard and $935.2408/hr with extra trading. In the IEEE 57-bus, costs are $37589.34/hr standard and $37628.8/hr with additional trading. These results align with benchmarks, showcasing the method's efficacy in intricate problem-solving. [ABSTRACT FROM AUTHOR]

The present research aims to select optimal areas for the installation of wind farms in the north-eastern part of Cuba. The research is based on the free software QGIS, Hierarchical Process Analysis, databases of the information of the alternatives and criteria and Geographic Information Systems (GIS), which makes it possible to know the places where these farms will be installed. In addition, experts were consulted to obtain the weights or level of importance of the selected criteria, such as distance to ports, distances to common roads, distances to population centers, to electrical grids and finally the wind speed. As a result, a mathematical conceptual model was obtained for the selection of optimal zones for the installation of wind farms in the eastern north of Cuba, by means of the MCDM and GIS methods, where it was determined that, within the evaluated alternatives of wind farms, Gibara III is the optimal one. These models will allow the development of wind projects in the eastern region of Holguin, and to be able to manage human, financial and material resources.

Admittance identification is an effective tool to solve the issue of black-box admittance modeling in wind farms. However, due to the large operating range of wind farms, it is difficult to accurately identify the admittance model of wind farms under all operating conditions, which limits the research on wideband oscillation caused by the interaction between wind farms and the power grid. This paper analyses the characteristics of the frequency-coupling admittance for wind farms. It is found that the power-sharing ratio of wind turbine generators (WTGs) affects the admittance characteristic of the wind farm, which leads to a huge number of operating points for the wind farm. The all-operating-point (AOP) admittance model of wind farms considering frequency-coupling characteristics is hard to directly identify. Aiming for this problem, this paper proposes to first identify the AOP-admittance model for WTGs. Then, based on the operating points of each WTG and the network structure, the AOP-admittance model of the wind farm is obtained via the admittance aggregation and model reduction method. This proposed method solves the problem of black-box admittance modeling and addresses the problem of dimension disaster in admittance modeling for wind farms. The identified model of the wind farm can be used to accurately assess the stability of the wind power integration system under various operating conditions. Finally, the effectiveness of the proposed method is verified through the admittance measurement and stability analysis of the wind farm.

Abstract Digital twin technology, aligned with Industry 4.0 standard, has witnessed widespread adoption in various industries, notably in manufacturing. Meanwhile, the concept of digital twin itself is yet to be clearly defined in wind farm sector. Our primary contribution lies in investigating the potential for transferring knowledge of industrial digital twins for the wind farm industry. Through a comprehensive literature study, we explored the digital twin concept within the context of wind farm applications. Also, we conducted a comparative analysis of digital twin frameworks employed in wind farm and manufacturing sectors. We aim to identify commonalities and differences between these frameworks and to determine how they could be adapted to the unique requirements of the offshore wind sector. A case study is presented, wherein the Industry 4.0 standard framework, Asset Administration Shell (AAS), is conceptually applied to the wind farm sector. Additionally, we briefly explored the AASX Package Explorer and concluded that implementing the AAS could be a promising option for enhancing digital twin functionality in offshore wind farms, and for achieving interoperability in line with Industry 4.0 standard.

With the rising demand for electricity and limited fossil fuel reserves, wind energy conversion systems are nowadays considered a pivotal and indispensable resource within the realm of alternative power generation. Flexible AC Transmission Systems (FACTS) devices can be utilized to improve the voltage profile and stability in the presence of large wind farms. This study presents a comprehensive techno-economic assessment for different FACTS devices used with wind farms. In the technical assessment, the improved voltage (IV) index is presented to quantify the contribution of the Static Synchronous Compensator (STATCOM) and Unified Power Flow Controller (UPFC) devices with the focus on the improvement of the voltage levels during different types of faults. In the economic assessment, a cost comparison between the chosen FACTS devices is presented, where a cost related (CR) index is proposed which considers the investment cost in the FACTS device and the minimum revenue that could be obtained as a result of FACTS installation to keep the wind farm connected as a result of the voltage improvement during faults. In addition, guidelines to calculate the threshold for annual additional energy from the wind farm and its revenue needed to compensate for the FACTS device total cost are presented. To consider the environmental impact, the role of the FACTS devices on reducing CO2 emissions, and the associated carbon credit certificates, is considered. Finally, to combine both assessments, a new weighted techno-economic (TEI) index is presented which combines the IV and the CR indices obtained from the technical and economic assessments, respectively. This index will assist system operators in selecting the optimal device, where a breakeven point serving as the criterion for selecting the best device based on the proposed approach. The results show that the TEI index for the proposed system indicates that the STATCOM is considered a preferable solution when the focus is towards the economic weight. On the other hand, the UPFC becomes a preferable solution when the technical aspect is more important to the system operator. In this study, a technical weight of 0.8364 (economic weight of 0.1636) is the turning point between the two devices. Below this weight, the STATCOM is more suitable for installation and above this weight, the UPFC is a preferred option.

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.

Digital twin technology, aligned with Industry 4.0 standard, has witnessed widespread adoption in various industries, notably in manufacturing. Meanwhile, the concept of digital twin itself is yet to be clearly defined in wind farm sector. Our primary contribution lies in investigating the potential for transferring knowledge of industrial digital twins for the wind farm industry. Through a comprehensive literature study, we explored the digital twin concept within the context of wind farm applications. Also, we conducted a comparative analysis of digital twin frameworks employed in wind farm and manufacturing sectors. We aim to identify commonalities and differences between these frameworks and to determine how they could be adapted to the unique requirements of the offshore wind sector. A case study is presented, wherein the Industry 4.0 standard framework, Asset Administration Shell (AAS), is conceptually applied to the wind farm sector. Additionally, we briefly explored the AASX Package Explorer and concluded that implementing the AAS could be a promising option for enhancing digital twin functionality in offshore wind farms, and for achieving interoperability in line with Industry 4.0 standard. [ABSTRACT FROM AUTHOR]

Power systems, in recent years, have been experiencing a dynamic rise in the amount of power obtained from distributed renewable energy sources leading to the concept of microgrids to address the distributed power grid integration issues. Microgrids, a promising means of facilitating the green transformation of power systems, allow the union operation of distributed energy resources (DER) such as combined heat and power (CHP), renewables like photovoltaic (PV), wind and fuel cells (FC), energy storage systems, diesel generators, and controllable loads, either individually or in combination. The protection of DERs within microgrids can be considered as one of the main challenges associated with such phenomenon. Short and Long power transmission lines, in case of a fault, both have particular impacts on system parameters and may result into subsequent events threatening the microgrid and renewable generation units. On the other hand, The high penetration of microgrids not only can change the power flow within the power network, but it can also affect the fault current levels and may lead to their islanding in case of a fault. Before investing in microgrids, especially those in far places, this paper develops a tool to be used in investigating the influence of the interconnecting transmission line length as well as the type/severity of fault on the microgrid performance. The toolbox was developed using MATLAB/Simulink Toolbox. The developed tool was then validated on a case study microgrid and results show that the length of the interconnecting transmission line and the fault severity directly impact the microgrid performance (i.e. voltage and power deviations). In that case, interconnection or islanded mode is contingent upon the decision of the utility operator which also depends on the sensitivity of the equipment used in the microgrid. [ABSTRACT FROM AUTHOR]

The current strong global consensus on reducing carbon emissions is a motivation to develop more efficient means of harnessing sustainable sources of energy. Accordingly, research efforts toward the development of more efficient wind turbine designs are desirable. With this motivation, we present a set of numerical studies on flows past vertical axis wind turbines (VAWTs). We perform large eddy simulations (LES) of flows past several VAWT configurations. A uniform inflow is set for our simulations. The influence of turbine blades on the flow field is modeled using the actuator line method (ALM). Our focus is on a twin rotor configuration, wherein the rotors are placed close enough, so that the separation between the centers of the two rotors is less than the diameter of the two individual turbines (the overlapping configuration). We demonstrate that such a configuration indeed results in (a) the enhanced power coefficient (ratio of power extracted by the turbine configuration to the power available in the freestream) and (b) better power density (power extracted by a turbine configuration per unit ground area occupied by the VAWT) compared to a single rotor VAWT configuration. Based on our findings, we conclude that the overlapping twin rotor arrangement can prove to be the preferred configuration for large-scale VAWT-based wind farms. [ABSTRACT FROM AUTHOR]

This study explores the impact of wind facilities on land values based on wind farm construction and land transaction datasets in China from 2005 to 2017. We implement a two-way fixed effects model to estimate the causal effects of the siting of wind farms on land prices. Our results show that the siting of wind farms significantly impacts land transaction prices. On average, land parcels located within 10 km of a wind farm enjoy a 4.78% price premium. However, land parcels located within 1 to 3 km of a wind farm experience depreciation, while lands located within 3 to 6 km of a wind turbine experience an increase on average. We further find that offshore wind farms are viewed more favorably by nearby residents compared to inland wind farms. [ABSTRACT FROM AUTHOR]

This work aims to analyze the performance of environmental education promoted by wind farms in Rio Grande do Norte's municipalities, starting from the perspective of the impacts on the natural, socioeconomic, and cultural environment. For that, a systematic review of dissertations and theses that dealt with this topic was carried out using the case study or comparative analysis technique. In the results, it was verified uniformity of the authors that, in general, the wind farms do not effectively maintain programs of environmental education, mainly, after the installation of the parks, as determined by the legal system for environmental licensing, with the accomplishment of significant negative impacts on the social, economic and cultural contexts of traditional populations. [ABSTRACT FROM AUTHOR]

This article explores the growing opposition to wind and solar energy projects, both domestically and globally. Concerns raised by opposition groups include the impact on local communities, such as noise, vibration, and changes to landscapes. Indigenous groups and rural communities in the Global South have also clashed with wind project developers, accusing them of land theft and bribery. The article highlights the arrest of climate activist Greta Thunberg for protesting a wind farm on indigenous land in Norway. It raises questions about the feasibility of a high renewables strategy and the need for an honest debate about energy options. The article also discusses the challenges of meeting climate targets and the significant land area required for wind and solar installations. It concludes by mentioning the growing movement to prohibit solar energy systems on farmland in the Midwest, with several townships and counties adopting restrictive ordinances. The article emphasizes the importance of taking the concerns raised by opposition groups seriously and adopting a principled approach to address the opposition to renewable energy. [Extracted from the article]

Wind energy producing facilities are often located based on the presence of wind resources, resulting in their construction in remote places that are far from high voltage power transmission lines and large consumption centers. Wind farms that use squirrel cage induction generators (SCIG) directly linked to the power grid constitute a substantial proportion of wind energy conversion systems worldwide. However, in situations when wind farms are linked via medium voltage (MV) distribution lines because of controlled electricity output, a prevalent problem occurs called Wind Farm to Weak Grid Connection. This scenario is characterized by power production that is similar to the capacity of the grid for transportation, leading to inadequate control of voltage at the point where the grid is connected (PCC). This work presents a new compensation method that utilizes the Unified Power Quality Compensator (UPQC) with a unique internal control system based on fuzzy logic controllers. The aim is to tackle the difficulties related to connecting Wind Farms to weak grids. The UPQC, which is a Custom Power System (CUPS) device, presents a possible alternative for improving power quality in such situations. The suggested compensation technique entails the use of the UPQC series converter to regulate voltage at the WF terminals, while using the shunt converter to filter power provided by the WF and reduce voltage swings at the grid side. The internal control approach prioritizes the regulation of active and reactive power in converters and the transfer of power between them via the UPQC DC-Link. The suggested technique differs from traditional tactics by using both reactive power and DC-bus energy storage to optimize compensating capabilities. Additionally, it involves active power sharing amongst UPQC converters. The efficacy of the fuzzy logic improved UPQC compensating technique in enhancing both Power Quality and Wind Farm stability is proven via meticulous simulations. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Anales de Geografía de la Universidad Complutense is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Worldwide energy demand is constantly increasing. This fact, in combination with the ever growing need to reduce the energy production footprint on the environment, has led to the adoption of cleaner and more sustainable forms of energy production. Renewable Energy Sources (RES) are constantly developing in an effort to increase their conversion efficiency and improve their life cycle. However, not all types of RES are accepted by the general public. Wind Turbines (WTs) are considered by many researchers as the least acceptable type of RES. This is mostly because of how their installation alters the surrounding landscape, produces noise and puts birds in danger when they happen to fly over the installation area. This paper aims to apply a methodology which, by using Rational Basis Function Neural Networks (RBFNN), is capable of investigating the criteria used for the installation locations of WTs in a transparent way. The results from the Neural Network (NN) will be combined with protected areas and the Land Fragmentation Index (LFI), in order to determine possible new installation locations with increased social acceptance and, at the same time, increased energy production. A case study of the proposed methodology has been implemented for the entire Greek territory, which is considered one of the most suitable areas for the installation of wind farms due to its particular geomorphology. [ABSTRACT FROM AUTHOR]

The Patagonian region of Argentina has great wind potential. In this geographical area of complex terrain, the local wind is influenced by the proximity of the Andes Mountain chain, and it is very intense and turbulent. The wind profiles, turbulence intensity, and average wind speeds at the site do not meet the recommended values in the standards. This issue could have a significant impact on the design loads for structures installed in the region. The objective of this work was to compare the behavior under extreme wind load on different types of towers for multi-MW wind turbines in situ. For this, a hybrid tower, a concrete tower, and a steel tower of equal dimensions were compared. Additionally, we analyzed the influence of the cross-sectional shape of concrete on hybrid towers. The flow pattern around the structures was studied using a solid wall model. As for the towers, we implemented a stress–strain elastic analysis. We calculated the stress fields, displacement fields, and aerodynamic behavior for each tower. We conclude that hybrid towers present the most optimal behavior. Among the different cross-sectional shapes analyzed for this type of tower, we found that all of them show advantages and disadvantages, with the circular section being the one that has the highest average performance from the resistance and aerodynamic standpoint.

In this study, the potential impact of wind farm locations on the sustainable development of cities in Poland was evaluated, considering the availability of wind-generated electricity. We analyzed 37 cities in Poland with populations over 100,000. Research indicates that wind farms located 30–80 km from large cities perform best in terms of generating capacity, while greater distances increase transmission costs and energy losses. In Poland, wind farms are primarily situated in the northwestern regions, posing challenges for energy transmission to the southern cities, which are the main centers of energy consumption. The findings show that wind farms with the highest generating capacity are generally about 50 km from major cities. Key factors influencing wind farm locations include technical criteria, economic feasibility, environmental impact, public opinion, and the availability of transmission networks. Sustainable development of wind farms requires strategic cooperation between urban and rural municipalities, joint spatial planning, coordinated land acquisition, and the exchange of know-how.