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The objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO2 emission intensity factor (kg CO2/kWh) of the national electricity system. [ABSTRACT FROM AUTHOR]

We consider a sequential decision making process such as energy trading or electrical production scheduling whose outcome depends on the future realization of a random factor, such as a meteorological variable. Assuming that the decision maker has access to a dynamically updated probabilistic forecast (predictive distribution) of the random factor, we propose several stochastic models for the evolution of the probabilistic forecast of a given quantity, and show how these models may be calibrated from ensemble forecasts, commonly provided by weather centers. We then show how these stochastic models can be used to determine optimal decision making strategies to maximize a specific gain functional. Applications to wind energy trading are given. [ABSTRACT FROM AUTHOR]

Solar irrigation systems should become more practical and efficient as technology advances. Automation and AI-based technologies can optimize solar energy use for irrigation while reducing environmental impacts and costs. These innovations have the potential to make agriculture more environmentally friendly and sustainable. Solar irrigation system implementation can be hampered by a lack of technical expertise in installation, operation, and maintenance. It must be technically and economically feasible to be practical and continuous. Due to weather and solar irradiation, photovoltaic power generation is difficult for high-efficiency irrigation systems. As a result, more precise photovoltaic output calculations could improve solar power systems. Customers should benefit from increased power plant versatility and high-quality electricity. As a result, an artificial intelligence-powered automated irrigation power-generation system may improve the existing efficiency. To predict high-efficiency irrigation system power outputs, this study proposed a spatial and temporal attention block-based long-short-term memory (LSTM) model. Using MSE, RMSE, and MAE, the results have been compared to pre-existing ML and a simple LSTM network. Moreover, it has been found that our model outperformed cutting-edge methods. MAPE was improved by 6–7% by increasing Look Back (LB) and Look Forward (LF). Future goals include adapting the technology for wind power production and improving the proposed model to harness customer behavior to improve forecasting accuracy. [ABSTRACT FROM AUTHOR]

This study aims to conduct resource assessments at five offshore locations (L1–L5) in the Gulf of South Suez for possible development of wind farms. For this purpose, the hourly mean wind speed and direction data at 100 m above mean sea level (AMSL) and other meteorological data at near water surface from ERA5 (fifth-generation reanalysis for the global climate weather) is used. Statistical analyses, wind power, energy estimation, plant capacity factor, etc., have been performed using Windographer software. The cost of energy and greenhouse gas emissions are conducted based on international installation cost per kW and emissions factor per kWh from the literature. The data covers 43 years, between 1979 and 2021. The results show that at L1 to L5 locations, the long-term mean wind speed (WS) and wind power density (WPD) values are 8.678 m/s and 533 W/m2, 4.371 m/s and 78 W/m2, 8.917 m/s and 587 W/m2, 7.856 m/s and 406 W/m2, 8.072 m/s and 453 W/m2, and 7.876 m/s and 406 W/m2 at 100 m ASL, respectively. Based on the site-specific parameters (WS, WPD, WPC, MWVI, MWSI, AWVI, AWSI, minimum zero power, maximum rated power, PCF, COE, and maximum wind duration), values of 8.917 m/s, 587 W/m2, 1.125, 34.92, 0.358, 101.9, 6.26%, 5.76%, 54.04%, 0.007 USD/kWh, and 91%; L2 are identified as the most relevant area for wind farm development among the studied locations. At L2 site, the wind turbine WT2 can deliver annually 21.266 GWh of energy at respective plant capacity factors of 48.55%. [ABSTRACT FROM AUTHOR]

A major barrier to wind sources when participating in an electricity market is inaccurate forecasting of wind power. The wind power uncertainty affects the plant's scheduled generation power, bidding price, and profitability. The profits of wind farms may be increased by determining the suitability of power output and bidding strategy in the electricity market, which is one of the challenges for wind plant producers because it is difficult to predict wind power accurately. To solve this problem, wind farm owners need to have plans to reserve power or link with other wind plants to be able to fully meet the contracted power. This paper proposed models linking wind farms or wind farms and other energy sources such as thermal power and energy storage systems. The simulation results on the IEEE 30-bus system show that the profits of a wind plant are increased when there is a backup power agreement from the thermal power plant or energy storage systems. It also demonstrates that the profitability of a wind power plant can be enhanced up to 132% by implementing a backup power agreement with a thermal power plant or energy storage systems. Furthermore, the wind output power increases significantly, reaching 95 MW in the integration models compared to the original model of 55 MW, thereby generating substantial social welfare. [ABSTRACT FROM AUTHOR]

Aspects of superstring theory on deformed BTZ black holes, formed near k NS5 branes by p fundamental strings, and single-trace T T ¯ holography, are presented. The excitation energy of a singly wound long string plus its contribution to the energy of the black hole, 1/p fraction of the black-hole energy, is the same as that in T T ¯ deformed CFT2 with c = 6k. This supports the claim that the black hole can be thought of as a state in a symmetric product of p CFT2's of central charge 6k, where the black-hole energy is split equally among all p factors. A comment on superstring theory on deformed global AdS3 is also presented. [ABSTRACT FROM AUTHOR]

In this article, the aim is to develop a model for efficient energy management using hybrid energy to power a drilling rig. This involves utilizing wind turbines and emergency generators, as well as charging battery storage systems with recycled energy from the depot through regenerative braking. The goal is to decrease the fuel consumption of diesel generators, while also reducing energy costs and environmental impact. The model takes into account the combined energy demand for diesel generators and battery charging as input. The results indicate that the proposed model can reduce operating costs and greenhouse gas emissions by over 25% compared to using only diesel generators. Analysis of 365 days in the last year reveals that three-quarters of operating costs could be saved due to random loading on the drilling rig. The investment payback period is estimated to be 1 year and 4 months. The proposed micro-drilling rig network with the optimal battery system and energy recovery has a lower life cycle cost of $1,500,000 with a $114,000 investment, compared to $5,400,000 for the baseline method. A reservation cost of $4,000,000 can be achieved within three-quarters of the specified period. For system performance analysis, a complete Model Power Supply of Drilling Rig is established on MATLAB/Simulink environment. Overall, this study demonstrates that the rig's generator load demand is reduced, leading to decreased environmental pollutants and operating costs. [ABSTRACT FROM AUTHOR]

The large-scale wind power grid connection will change the power distribution between the original system tide and synchronous machine, and the interaction between wind turbine and synchronous machine affects the system's damping oscillation characteristics. Traditional synchronous generators' extra damping control provides an important means for DFIG to improve system damping characteristics. Different types of PSS have different suppression effects on low-frequency oscillations. In this paper, four types of IEEE PSS models are built in DIGSILENT/PowerFactory to study the suppression effects of DFIG additional different types of PSS on low-frequency oscillations of power systems, and the suppression effect of four types of PSS on system low-frequency oscillation after connecting to the DFIG reactive power control loop is compared and analyzed from two perspectives: eigenvalue and time-domain simulation. The MRAC control principle is used to improve PSS4B, and the total least squares-estimation of signal parameters via rotational invariance technique identification method is used to obtain the system transfer function, and the controller parameters are calculated in real time using the adaptive law based on the gradient approach. Finally, the MRAC–PSS4B is connected to the DFIG rotor-side controller's reactive power control loop, and the improvement effect of the designed MRAC–PSS4B controller on the power system's low-frequency oscillation characteristics under different contact line transmission power is confirmed. [ABSTRACT FROM AUTHOR]

This paper presents the design and development of a modular multiport DC-DC converter for hybrid charging station. The system is supplied by renewable energy sources (RES) like solar photovoltaic system (SPV), wind energy system (WE) and fuel cell (FC). The proposed converter has several benefits like current sharing capability, providing lower current ripple and lower voltage ripple, lower current stress on the switches, lower current rating of switches and using a small-sized inductor. Due to the unavailability of continuous flow of power from the RES throughout the day, an effective energy management system using the adaptive neuro-fuzzy inference system (ANFIS) is implemented in the proposed system. ANFIS controller is implemented to identify and enable the available power from the renewable energy sources to feed the base load as well as charge the batteries in the hybrid charging station. The ANFIS controller continuously monitors the power availability for the charging station, thereby feeding minimum power to the base load. The proposed system is simulated and tested using the MATLAB/SIMULINK software, and a prototype of the same has been developed in the laboratory. From the simulation and experimental results, it is observed that the proposed converter suits best for integrating hybrid sources and used for charging the EVs. Improved life expectancy of the battery is obtained using the proposed converter. The proposed converter produces an efficiency of 97% and is superior to the other existing converters. [ABSTRACT FROM AUTHOR]

Demand-side flexible load resources, such as Electric Vehicles (EVs) and Air Conditioners (ACs), offer significant potential for enhancing flexibility in the power system, thereby promoting the full integration of renewable energy. To this end, this paper proposes an optimal allocation method for demand-side flexible resources to enhance renewable energy consumption. Firstly, the adjustable flexibility of these resources is modeled based on the generalized energy storage model. Secondly, we generate random scenarios for wind, solar, and load, considering variable correlations based on non-parametric probability predictions of random variables combined with Copula function sampling. Next, we establish the optimal allocation model for demand-side flexible resources, considering the simulated operation of these random scenarios. Finally, we optimize the demand-side resource transformation plan year by year based on the growth trend forecast results of renewable energy installed capacity in Jiangsu Province from 2025 to 2031. [ABSTRACT FROM AUTHOR]

Decarbonising the energy system requires high shares of variable renewable generation and sector coupling like power to heat. In addition to heat supply, heat pumps can be used in future energy systems to provide flexibility to the electricity system by using the thermal storage potential of the building stock and buffer tanks to shift electricity demand to hours of high renewable electricity production. Bridging the gap between two methodological approaches, we coupled a detailed building technology operation model and the open-source energy system model Balmorel to evaluate the flexibility potential that decentral heat pumps can provide to the electricity system. Austria in the year 2030 serves as an example of a 100% renewable-based electricity system (at an annual national balance). Results show that system benefits from heat pump flexibility are relatively limited in extent and concentrated on short-term flexibility. Flexible heat pumps reduce system cost, CO2 emissions, and photovoltaics and wind curtailment in all scenarios. The amount of electricity shifted in the assessed standard flexibility scenario is 194 GWhel and accounts for about 20% of the available flexible heat pump electricity demand. A comparison of different modelling approaches and a deterministic sensitivity analysis of key input parameters complement the modelling. The most important input parameters impacting heat pump flexibility are the flexible capacity (determined by installed capacity and share of control), shifting time limitations, and cost assumptions for the flexibility provided. Heat pump flexibility contributes more to increasing low residual loads (up to 22% in the assessed scenarios) than decreasing residual load peaks. Wind power integration benefits more from heat pump flexibility than photovoltaics because of the temporal correlation between heat demand and wind generation. [ABSTRACT FROM AUTHOR]

The building sector is significantly contributing to climate change, pollution, and energy crises, thus requiring a rapid shift to more sustainable construction practices. Here, we review the emerging practices of integrating renewable energies in the construction sector, with a focus on energy types, policies, innovations, and perspectives. The energy sources include solar, wind, geothermal, and biomass fuels. Case studies in Seattle, USA, and Manama, Bahrain, are presented. Perspectives comprise self-sufficiency, microgrids, carbon neutrality, intelligent buildings, cost reduction, energy storage, policy support, and market recognition. Incorporating wind energy into buildings can fulfill about 15% of a building's energy requirements, while solar energy integration can elevate the renewable contribution to 83%. Financial incentives, such as a 30% subsidy for the adoption of renewable technologies, augment the appeal of these innovations. [ABSTRACT FROM AUTHOR]

The paper proposes a nonlinear controller called dual super-twisting sliding mode command (DSTSMC) for controlling and regulating the rotor side converter (RSC) of multi-rotor wind power systems that use doubly-fed induction generators. It was proposed that this controller be developed as an alternative to the direct power control (DPC), which makes use of a pulse width modulation (PWM) strategy to regulate the RSC's functioning. Overcoming the power/current quality issue with the proposed technique (DPC-DSTSMC-PWM) is characterized by great robustness and excellent performance. The designed strategy was contrasted with the standard method of control and other methods already in use. So, the unique proposed control strategy's robustness, performance, efficiency, and efficacy in enhancing system characteristics were tested and validated in Matlab/Simulink. In both tests, the proposed method resulted in significant improvements, reducing active power ripples by 83.33%, 57.14%, and 48.57% in the proposed tests. When compared with the traditional regulation method, the reduction rates of reactive power ripples are 64.06%, 52.47%, and 68.7% in the tests. However, in contrast to the conventional method, the proposed tests showed a decrease of between 72.46%, 50%, and 76.22% in the value of total harmonic distortion (THD) of the provided currents. These ratios show how effective the proposed plan is in ameliorating and enhancing aspects of the energy system. [ABSTRACT FROM AUTHOR]

This study presents a data-driven assisted real-time optimization model which is an innovative approach to address the challenges posed by integrating Submerged Arc Furnace (SAF) systems with renewable energy sources, specifically photovoltaic (PV) and wind power, with modern intelligent energy terminals. Specifically, the proposed method is divided into two stages. The first stage is related to data-driven prediction for addressing local time-varying renewable energy and electricity market prices with predicted information, and the second stage uses an optimization model for real-time SAF dispatch. Connections between intelligent energy terminals, demand-side devices, and load management systems are established to enhance local renewable resource utilization. Additionally, mathematical formulations of the operating resistance in SAF are explored, and deep neuron networks are employed and modified for dynamic uncertainty prediction. The proposed approach is validated through a case study involving an intelligent energy terminal with a 12.5 MVA SAF system and 12 MW capacity renewable generators in an electricity market with fluctuating prices. The findings of this research underscore the efficacy of the proposed optimization model in reducing operational costs and enhancing the utilization of localized renewable energy generation. By integrating four distinct dissatisfaction coefficients into the optimization framework, we demonstrate the model's adaptability and efficiency. The application of the optimization strategy delineated herein results in the SAF system's profitability oscillating between $111 and $416 across various time intervals, contingent upon the coefficient settings. Remarkably, an aggregate daily loss recovery amounting to $1,906.84 can be realized during the optimization period. Such outcomes not only signify considerable economic advantages but also contribute to grid stability and the diminution of renewable energy curtailment, thereby underscoring the dual benefits of economic efficiency and sustainability in energy management practices. [ABSTRACT FROM AUTHOR]

East Inner Mongolia region is rich in renewable energy and is an important power station. The aim of this study was to further enhance the development and utilization of wind power and photovoltaic in the East Inner Mongolia region, and help build a new type of power system in the region. Based on the research targets in Chifeng, Tongliao, Xing'an and Hulunbuir in the East Inner Mongolia region, Study of load characteristics, wind power and photovoltaic output characteristics and optimal ratios throughout the year, and study the scale and mode of operation of energy storage in the banner county seats. Research shows that wind power, photovoltaic monthly output during the year as a whole shows the law of "winter big summer small, spring big winter small", applies. Taking into account the operating costs and the average standard deviation of slow regions, the optimal ratio of wind and photovoltaic power in Chifeng should be 4.7:1, in Tongliao 4.8:1 and in Hulunbuir and Xing'an 4.4:1; Compared with the adjustment of the before energy storage method, the combined power formed by the power storage of grid is relatively gentle, with a low peak valley difference, and the overall performance of the grid side storage is better than that of the supply side storage. Therefore, research on the ratio of wind and photovoltaic power and the energy storage analysis of these regions can effectively promote the development of power and accelerate the realization of strategic goals such as "dual carbon", as well as providing a reference for the future planning of the East Inner Mongolia region power network. [ABSTRACT FROM AUTHOR]

In this study, a frequency regulation is proposed that adjusts the release of rotational kinetic energy to ensure that a wind turbine remains near the maximum power point in the event of persistent under-frequency. The proposed scheme calculates wind turbine power by multiplying the frequency deviation with the variable control gain and then adding the resulting value to the torque controller power. Considering the operational characteristics of the wind turbine, separate control gains are applied in both the over-frequency section (OFS) and the under-frequency section (UFS). When the rotor speed approaches the maximum power point (MPP), the UFS control gain decreases, causing the wind turbine to gradually transition to maximum power point tracking (MPPT). This overcomes the limitations of conventional frequency regulation, enhancing both the power output of the wind turbine and the average grid frequency. To validate the proposed scheme, an IEEE 14 bus system, including a wind power plant and a photovoltaic plant, was simulated using the EMTP-RV simulator. The simulation results demonstrate that the proposed scheme effectively performs frequency regulation in the power grid regardless of the wind penetration. [ABSTRACT FROM AUTHOR]

In the practical environment, it is very common for the simultaneous occurrence of base excitation and crosswind. Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating. For this purpose, the effects of the wind speed and random excitation level are investigated with the stochastic averaging method (SAM) based on the energy envelope. The results of the analytical prediction are verified with the Monte-Carlo method (MCM). The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester (BEH) realize the performance enhancement for a weak base excitation. However, as the strength of the wind increases to a particular level, the influence of the random base excitation on the dynamic responses is weakened, and the system exhibits a periodic galloping response. A comparison between a BEH and a linear energy harvester (LEH) indicates that the BEH demonstrates inferior performance for high-speed wind. Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation. The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds. However, as the speed of the incoming wind is up to a particular level, the disadvantage of the BEH becomes clear and evident. [ABSTRACT FROM AUTHOR]

Expanding the South American renewable energy matrix to ensure more sustainable socio-economic development, mitigate the climate change effects, and meet the targets set in the Paris Agreement is crucial. Hence, this study sought to estimate South America's wind speed and wind power density alterations projected by eight global climate models (GCMs) from the Coupled Model Intercomparison Project—Phase 6 (CMIP6). To this end, we applied statistical downscaling and bias correction to the GCMs outputs through the Quantile Delta Mapping method and assessed the projected changes in wind power in future climate under the Shared Socioeconomic Pathways (SSPs) SSP2-4.5 and SSP5-8.5 emission scenarios. ERA5 reanalysis data from 1995 to 2014 validated the models' historical simulations. The CMIP6 multi-model ensemble indicated an approximate 25–50% increase in wind power density in sectors such as Northeast and South Brazil and growing wind power in regions such as Argentine Patagonia, northern Venezuela, and portions of Uruguay, Bolivia, and Paraguay. Estimates of the wind power growth for the twenty-first century in those regions reiterated their potential performance in the historical period. For the SSP5-8.5 emission scenario, the ensemble projections indicated even more favorable wind power conditions in the sectors mentioned. However, individual projections of wind intensity anomalies obtained by each ensemble member showed a large spread among the GCMs, evidencing the uncertainties associated with the prospects of change in wind power on the continent. Furthermore, this study has presented a first analysis of CMIP6 projections for South American wind power generation, providing relevant information to the energy sector decision-makers. [ABSTRACT FROM AUTHOR]

Renewable energy plays an important role in the power mix of India being sustainable and environmental source of energy. In this study, modified fuzzy Q-learning (MFQL)-based solar radiation forecasting has been proposed to forecast 30-min-ahead solar irradiance. Application of MFQL is novel in this field, as it uses reinforcement learning and model-free environment. Raw data have been collected for four Indian cities in the state of Rajasthan, i.e. Jodhpur, Ajmer, Jaipur and Kota via the data portal of National Institute of Wind Energy and Wind Resource (NIWE). Empirical mode decomposition (EMD) has been used as the data pre-processing technique, and relevant features are extracted from Pearson's correlation coefficient. The results obtained from the MFQL forecaster are promising with forecasting accuracy of 92.38% for winter, 93.73% for summer, 91.54% for monsoon and 92.05% for autumn season for the city of Ajmer, and similar results have been obtained for other cities as well. MFQL lends itself as an effective tool for forecasting of seasonal solar irradiance. Proposed prediction model can be effectively utilized for solar irradiance forecasting and for optimal generation of power from incident solar radiation. [ABSTRACT FROM AUTHOR]

As of now, there are multiple types of renewable energy sources available in nature which are hydro, wind, tidal, and solar. Among all of that the solar energy source is used in many applications because of its features are low maitainence cost, less human power for handling, a clean source, more availability in nature, and reduced carbon emissions. However, the disadvantages of solar networks are continuously depending on the weather conditions, high complexity of the solar energy storage, and lots of installation place is required. So, in this work, the Proton Exchange Membrane Fuel Stack (PEMFS) is utilized for supplying the power to the local consumers. The merits of this fuel stack are high power density, ability to work at very less temperature values, efficient heat maintenance, and water management. Also, this fuel stack gives a quick startup response. The only demerit of PEMFS is excessive current production, plus very less output voltage. To optimize the current supply of the fuel stack, a Wide Input Operation Single Switch Boost Converter (WIOSSBC) circuit is placed across the fuel stack output to improve the load voltage profile. The advantages of the WIOSSBC are less current ripples, uniform voltage supply, plus good voltage conversion ratio. Another issue of the fuel stack is nonlinear power production. To linearize the issue of fuel stack, the Grey Wolf Algorithm Dependent Fuzzy Logic Methodology (GWADFLM) is introduced in this article for maintaining the operating point of the fuel cell near to Maximum Power Point (MPP) place. The entire system is investigated by utilizing the MATLAB software. [ABSTRACT FROM AUTHOR]

The development opportunities and high-performance capacity of offshore wind energy project depends on the selection of the suitable offshore wind power station (OWPS) location. The present study aims to introduce a decision-making model for assessing the locations for OWPS from multiple criteria and uncertainty perspectives. In this regard, the concept of interval-valued intuitionistic fuzzy set (IVIFS) is utilized to express uncertain information. To quantify the degree of difference between IVIFSs, an improved distance measure is proposed and further utilized for deriving the objective weights of criteria. Numerical examples are discussed to illustrate the usefulness of introduced IVIF-distance measure. The RANking COMparison (RANCOM) based on interval-valued intuitionistic fuzzy information is presented to determine the subjective weights of criteria. With the combination of objective and subjective weights of criteria, an integrated weighting tool is presented to find the numeric weights of criteria under IVIFS environment. Further, a hybrid interval-valued intuitionistic fuzzy Weighted integrated Sum Product (WISP) approach is developed to prioritize the OWPS locations from multiple criteria and uncertainty perspectives. This approach combines the benefits of two normalization tools and four utility measures, which approves the effect of beneficial and non-beneficial criteria by means of weighted sum and weighted product measures. Further, the developed approach is applied to the OWPS location selection problem of Gujarat, India. Sensitivity and comparative analyses are presented to confirm the robustness and stability of the present WISP approach. This study provides an innovative decision analysis framework, which makes a significant contribution to the OWPS locations assessment problem under uncertain environment. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Modelling the wind potential energy for metallurgical sector in Albania" published in Scientific Reports. The correction addresses errors in the affiliations of the authors and the legends of several figures and tables. The corrected version of the article is now available. The article is licensed under a Creative Commons Attribution 4.0 International License. [Extracted from the article]

The development opportunities and high-performance capacity of offshore wind energy project depends on the selection of the suitable offshore wind power station (OWPS) location. The present study aims to introduce a decision-making model for assessing the locations for OWPS from multiple criteria and uncertainty perspectives. In this regard, the concept of interval-valued intuitionistic fuzzy set (IVIFS) is utilized to express uncertain information. To quantify the degree of difference between IVIFSs, an improved distance measure is proposed and further utilized for deriving the objective weights of criteria. Numerical examples are discussed to illustrate the usefulness of introduced IVIF-distance measure. The RANking COMparison (RANCOM) based on interval-valued intuitionistic fuzzy information is presented to determine the subjective weights of criteria. With the combination of objective and subjective weights of criteria, an integrated weighting tool is presented to find the numeric weights of criteria under IVIFS environment. Further, a hybrid interval-valued intuitionistic fuzzy Weighted integrated Sum Product (WISP) approach is developed to prioritize the OWPS locations from multiple criteria and uncertainty perspectives. This approach combines the benefits of two normalization tools and four utility measures, which approves the effect of beneficial and non-beneficial criteria by means of weighted sum and weighted product measures. Further, the developed approach is applied to the OWPS location selection problem of Gujarat, India. Sensitivity and comparative analyses are presented to confirm the robustness and stability of the present WISP approach. This study provides an innovative decision analysis framework, which makes a significant contribution to the OWPS locations assessment problem under uncertain environment. [ABSTRACT FROM AUTHOR]

The metallurgical industry, in the context of the global energy crisis and the new European green deal, needs urgent investments on energy and resource efficiency. The metallurgical sector, which includes the production of different metals is an energy-intensive industry that requires large amounts of energy for various processes such as smelting, refining, and casting. One of the largest consumptions of energy in Albania comes from the metallurgical sector during the production of iron, steel, chromium and aluminum which corresponds respectively to three private companies called "Kurum International Ltd", "AlbChorme Ltd" and "Everest Ltd". During the last three years, these companies have temporary interrupted the production process due to the higher electricity price that come from imports. Based on it, our research work presents the energy efficiency analysis in the Albanian metallurgical sector by focusing on the implementation of wind energy in the above mentioned private metallurgical companies, because adding new generation capacity from Renewable Energy Sources in a context of industrial energy communities, will contribute to improve the security of supply for this industry. The Wind Balkan Atlas, New European Wind Atlas, and Wind Atlas Analysis and Application Program (WAsP) has been used to select the appropriate areas and to develop the wind potential distribution maps, as well as to select the most suitable type of wind turbine based on capacity factors. Two areas were selected close to the metallurgical sectors in the regions of "Vajkal" in Bulqizë and "Selitë e Malit" in Tirana. It has been installed the power of 9 MW for each wind farm, with a capacity factor of 40% and 36.6% respectively, and with a total annual energy production of about 60 GWh/year, these wind farms will cover about 26% of the total annual consumption of companies. Clean Energy Management Software (RETScreen Expert) was used for the detailed economic analysis and environmental impact of proposed wind farms. The economic sensitivity analysis of the proposed wind farms showed that even for the highest installation cost value of 1350 €/kW, for discount rates 5, 7, and 11%, the LCoE values are within the statistically established range for wind farms in Europe. [ABSTRACT FROM AUTHOR]

This paper presents an investigation into the effect of area ratio parameter of diffusers on its energy output through power coefficient Cp. This parameter has effect both on diffusers' energy yield, besides diffuser's size for architectural integration prospects. A systematic increase in diffusers area ratio is adopted following standardized diffuser profile presented by NACA 1244 aerofoil. A series of area ratios were investigated (i.e., 1.25, 1.5, 1.75, 2, 2.5, 3 and 3.5). Area ratio of 1.5 (i.e., outlet/inlet, 0.75 m/0.50 m) exhibited the highest power coefficient Cp of 4.2, in addition to achieving highest resulting velocity of 25.8 m/s under incident velocity of 16m/s. Considerable wind separation inside inner walls of diffusers occurred from area ratio 1.75 onwards, which impacted resulting velocities. Simulations performed with ANSYS CFD Academic to standalone diffusers. A series of incident velocities employed from 1 to 16 m/s that resulted in velocity increase by 120–156% respectively. [ABSTRACT FROM AUTHOR]

As of now, there are multiple types of renewable energy sources available in nature which are hydro, wind, tidal, and solar. Among all of that the solar energy source is used in many applications because of its features are low maitainence cost, less human power for handling, a clean source, more availability in nature, and reduced carbon emissions. However, the disadvantages of solar networks are continuously depending on the weather conditions, high complexity of the solar energy storage, and lots of installation place is required. So, in this work, the Proton Exchange Membrane Fuel Stack (PEMFS) is utilized for supplying the power to the local consumers. The merits of this fuel stack are high power density, ability to work at very less temperature values, efficient heat maintenance, and water management. Also, this fuel stack gives a quick startup response. The only demerit of PEMFS is excessive current production, plus very less output voltage. To optimize the current supply of the fuel stack, a Wide Input Operation Single Switch Boost Converter (WIOSSBC) circuit is placed across the fuel stack output to improve the load voltage profile. The advantages of the WIOSSBC are less current ripples, uniform voltage supply, plus good voltage conversion ratio. Another issue of the fuel stack is nonlinear power production. To linearize the issue of fuel stack, the Grey Wolf Algorithm Dependent Fuzzy Logic Methodology (GWADFLM) is introduced in this article for maintaining the operating point of the fuel cell near to Maximum Power Point (MPP) place. The entire system is investigated by utilizing the MATLAB software. [ABSTRACT FROM AUTHOR]

This work emphasizes the development and examination of a Hybrid Luo Converter integrated with a unified Maximum Power Point Tracking (MPPT) for both grid and independent hybrid systems. The primary objectives of this hybrid system are to efficiently harness power from intermittent and variable renewable sources while elevating low-voltage energy inputs to utility-grade levels. Unlike previous studies employing specific MPPT algorithms for solar and wind sources, this work aims to simplify the control system by utilizing a unified MPPT controller. This research also introduces a novel approach involving dual-lift hybrid Luo converters to create hybrid systems, operating exclusively or concurrently based on the availability of renewable resources. To maximize power generation from all renewable sources, a unified MPPT algorithm is developed. The hybrid system, incorporates 500 W wind and 560 W PV systems, the innovative Luo converter, and the unified MPPT controller. A comprehensive comparative analysis is presented, comparing the hybrid system's performance with that of traditional control algorithms, such as the Perturb & Observe, and Radial Basis Function Network controllers. The successful prototype of the converter validates the practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

The use of wind energy, the area of wind farms, and the length of wind turbine blades continuously increase with the increase in energy demand. This study aims to simulate large wind farms in the atmospheric boundary layer with different double-rotor (DR) wind turbine arrangements using large eddy simulation. The effect of four DR wind turbine arrangements on the efficiency of a large wind farm was investigated in this study. All simulations were performed using the OpenFOAM solver. The performance of different turbine arrangements was investigated based on the mean velocity, the extent of the wake region, mean kinetic energy, and turbine power. Results showed that the arrangement of DR turbines with transverse spacing produces higher power than other layouts. Moreover, DR layouts produce the same power as single-rotor layouts with a short blade length. This scenario is important from an economic point of view. [ABSTRACT FROM AUTHOR]

Part of power transformers failures are result of great electromagnetic forces acting on its windings due the circulation of high currents, as in case of short circuits. To contribute for a more reliable mechanical design, this paper presents a finite element analysis (FEA) for a complete calculation and evaluation of electromagnetic forces on transformers windings. Three arrangements of concentric windings are analyzed considering three-phase and three-dimensional models, dealing with issues as the influence of magnetic core window and lateral phases presence, ensuring more accurate results. The adopted modeling allows to determinate the total axial and radial forces on all the phases and its distribution over the height of windings and around the core leg. It was possible to identify points of greater and lesser forces and the behavior of forces on different constructive arrangements, allowing its choice improvement during the design stage. The results present good agreement to the analytical method, allowing the application of the developed FEA for transformer design optimization, contributing for a time and costs reduction and avoiding future mistakes in its construction and failures during its operation. [ABSTRACT FROM AUTHOR]

The basic concernment of this work is to enhance the frequency regulation of power system integrated with renewable energy (wind and solar energy along with pumped hydro-energy storage). The integration of renewable energy system with grid may lead to power quality issues. The design of secondary controller to improve frequency regulation is immensely obligatory. The design of effective controller is highly relied on controller structure. In this work, the optimally designed fuzzy PID (ODFPID) is established for frequency regulation of power system. The membership function (MF) and rule base structures of fuzzy logic controller (FLC) is designed by using computational technique which is relevant to the corresponding system rather than trial-and-error method. The proposed controller MF is asymmetrical, and this structure of fuzzy is immensely relevant for a particular system. To decide optimal structure of FLC and gain parameters of controller, a computational technique with ability to solve problem with high numbers of variables is tuned. For this purpose, the capability to solve such problems of crow search algorithm (CSA) is enhanced by introducing craziness factor entitled as craziness-based CSA (CCSA). The supremacy of proposed CCSA technique is concluded by a comparison analysis with CSA technique to regulate frequency and tie-line power of a power system with FPID controller. The performance of CCSA ODFPID controller is tested in different environment (with wind, solar and PHES). The dominance of proposed approach is observed by conceding undershoot, overshoot, settling time and functional values of frequency and tie-line power deviation. The overall improvement due to the usage of CCSA technique over CSA technique for different case studies is 77.5226%. The propose ODFPID controller is having overall improvement of 86.0292% in comparison with FPID controller. The proposed ODFPID controller is concluded as a better approach for frequency regulation of power system. [ABSTRACT FROM AUTHOR]

The wind power generation is highly dependent on current weather conditions. In the course of the energy transition, the generation levels from volatile wind energy are constantly increasing. Accordingly, the prediction of regional wind power generation is a particularly important and challenging task due to the highly distributed installations. This paper presents a study on the role of regional wind power infeed estimation and proposes a multi-aggregated wind power characteristics model based on three scaled Gumbel distribution functions. Multi-levels of wind turbines and their allocation are investigated for the regional aggregated wind power. Relative peak power performance and full load hours are compared for the proposed model and the real measurement obtained from a local distribution system operator. Furthermore, artificial intelligence technologies using neural networks, such as Long Short-Term Memory (LSTM), stacked LSTM and CNN–LSTM, are investigated by using different historical measurement as input data. The results show that the suggested stacked LSTM performs stably and reliably in regional power prediction. [ABSTRACT FROM AUTHOR]

The starting time of a large-rated variable speed pumped storage unit (PSU) operating in pumping mode is crucial in the power balancing scenario in a modern power system as it defines the transition period from generation to pumping modes and vice versa, which determines the stability of the power system. Typically, doubly fed induction machines (DFIM) are preferred in large-rated variable speed PSUs (> 100 MW) as they ensure variable speed operation through partial-rated power converters. The start of DFIM in pumping mode is challenging, and it is ensured through rotor side power converters. DFIM is typically started by short-circuiting the stator windings and supplying power to the rotor windings via power converters. The conventional starting method leads to more starting time and power consumption due to the saturation of the iron core in the earlier speed range because of the higher magnetizing inductance seen from the rotor side. This paper proposed an improved starting method in which the machine's magnetization current is supplied via stator windings and acceleration current is supplied via rotor windings. The proposed method is based on the field-oriented vector control method, and it significantly reduces the starting time and power consumption compared to the conventional starting method. The proposed method is validated through a 306 MVA DFIM-fed variable speed PSU, and results show that the improved starting method reduces the starting time and power consumption by 27.5 and 37.2%, respectively, as compared to the conventional starting method. This reduced starting time is preferred by the grid authorities as it improves the stability of the power system. Furthermore, experimental results are validated in the laboratory with a scaled-down unit of 7.5 kW DFIM. [ABSTRACT FROM AUTHOR]

This article dealt the application of three-phase all-pass filter integrated with phase-locked loop (3Ø-APF-PLL) control approach in islanded electrical supply system for enhanced power quality (PQ). It also covers the effectiveness of proposed control under various operating conditions such as intermittent wind speed, variable solar irradiance, and unbalanced nonlinear load. An islanded electrical supply system includes wind energy generation, solar photovoltaic (SPV), and battery energy storage (BES). The proposed control technique provides a coordinated and balanced operation under a dynamical load. A 3Ø-APL-PLL-based control approach is proposed to extract the maximum value of fundamental component of load current and phase angle. The proposed control approach is utilized to operate voltage source converter (VSC) that performs multi-functions, such as reducing source current harmonics, power compensation (real & reactive), balancing of loads, and improving the overall power quality of the islanded SPV-wind-BES electrical supply system. The SPV system is developed using an incremental conductance (IC)-based maximum power point tracking (MPPT) technique to extract maximum power during the intermittent conditions of solar irradiance. A bidirectional controller (BDC) is designed to operate the charging/discharging modes of a BES. Generally, an islanded electrical supply system suffers from poor voltage & frequency regulation due to the intermittency of power generation sources, which can be solved by utilizing a BES with BDC control to manage the power leveling between the power generation sources and the unbalanced load. A 3Ø-APF-PLL control approach is compared to existing controllers like a least mean square (LMS) (Singh et al. in IET Power Electron 13:2767–2774, 2020) and second-order generalized integrator-based frequency locked loop (SOGI-FLL) (Golestan et al. in IEEE Trans Power Electron 34:213–224, 2018). Numerous parameters, such as the evaluation of the maximum value of the fundamental component, stability, steady-state error, and harmonic compensation capabilities, are taken into account when comparing 3Ø-APF-PLL to the control approaches described above. The dynamic parameters of the islanded electrical supply system are justified under the IEEE-519 standard. [ABSTRACT FROM AUTHOR]

The need for reserve provision in power systems is growing progressively due to the increase in wind power penetration level. This paper aimed to present a model from the ISO point of view for using demand-side resources as flexible resources that are aggregated as a demand-side provider (DSP). The DSP consists of demand response aggregator as grid backup and energy storage systems plus plug-in electric vehicles (PEVs) parking lot aggregators as fast reserve. In this regard, a two-stage stochastic programming model has been presented for energy and reserve determination in the unit commitment problem in the form of mixed integer linear programming (MILP). In this study, the incentive-based model of the capacity market program has been employed to achieve a certain level of demand-side response. Meanwhile, the Weibull probability distribution function and truncated Gaussian distribution have been applied to generate wind speed scenarios and model the uncertainties of PEVs' behavior, respectively. The results obtained in this study demonstrate that the simultaneous scheduling of energy sources and demand-side aggregators for energy supply as well as reserve has led to the reduction of wind energy uncertainty and improved system operational conditions. Also, increase in the number of PEVs present in the parking lot, in addition to reducing the operation costs, leads to increased grid reserve level as well as considerable reduction of wind power spillage. [ABSTRACT FROM AUTHOR]

Wind energy generation is continuously expanding in the global energy scenario of sustainable resources to replace fossil energy and alleviate the negative impacts on the environment. With the global attention focused on centralized generation, less attention has been paid to improving small wind turbines. As a result, small wind turbines have marginal contribution to the global energy scenarios, because of their poor performance and high cost. This review is aimed to gather methodologies and experiences in big machines and avail them for small machines. The review presents an evaluation of global expansion of wind energy followed by investigations on the blade element momentum (BEM), lifting line-based methods and other vorticity-based models, wind turbine noise, optimization of airfoils, blades and rotors, and commercial numerical codes with a special focus on small wind turbines. The main findings of the review show the necessity of more research and development efforts to improve the performance of small wind turbines and acceptability by the users, integration of the BEM with lifting line methods and other available software, more numerical and experimental real-scale studies on noise generation and its impact on the neighboring living beings, development of new optimized airfoils and blades for low Reynolds number operation and urban wind profile, and creation of computational codes for the design, micrositing, and simulation of small wind turbines. It is hoped that this review can be of help to researchers, development engineers, young scientists, and general readers interested in the topic. [ABSTRACT FROM AUTHOR]

The paper summarizes the issues related to relationships between the PC index and magnetic disturbances: threshold level of the PC index required for the disturbances beginning, delay time in response of magnetic substorms and storms to the PC index growth, relation of PC index to magnetospheric field-aligned currents in course of substorm, different types of magnetic substorms (isolated, expanded, delayed, sawtooth) and magnetic storms (classic, pulsed and composite) and their relation to different regularities in the PC index alterations, linear dependence of the substorm and storm intensities on value of the preceding of PC index, special features of magnetic activity in the winter and summer polar caps, variations of PC index and magnetic disturbances in course of the 23/24 solar activity cycles. New aspects that have arisen due to the PC index application are concerned with the threshold-dependent mode of the substorm development and regular repeateness of sawtooth substorms occurring under conditions of steady powerful EKL field. The experimental results examined in the paper are indicative that the PC index serves as an indicator of the solar wind energy which comes in the magnetosphere and then realizes in the form of magnetosphere disturbances. This paper follows the review of Troshichev (Front Astron Space Sci 9:1069470, 2022), where the relationships between the solar wind electric field EKL and PC index have been examined. [ABSTRACT FROM AUTHOR]

Wind energy is gaining importance owing to its renewable and environmentally friendly characteristics. However, the variability and stochastic nature of wind speed makes accurate forecasting difficult. Hence, this study introduces a novel approach (VMD-SCINet) for wind speed forecasting (WSF) by integrating the strengths of variational mode decomposition (VMD) and sample convolution and interaction network (SCINet) architecture for the prediction of wind speed. This study utilizes VMD as a denoising technique for wind speed data and incorporates SCINet to capture global patterns and long-range dependencies for the WSF. The wind speed data acquired from two distinct sites: Leicester, and Portland is used for the evaluation. To evaluate the WSF capability of the proposed hybrid model, it's performance is compared to robust models using data from two wind farms across six different time horizons such as 5-min, 10-min, 15-min, 30-min, 1-hour, and 2-hours. The results from two experiments demonstrate that the proposed approach outperforms other models, leading to a significant improvement in WSF accuracy across all evaluated time intervals. [ABSTRACT FROM AUTHOR]

Wind energy has gained attention as an alternative to fossil fuels due to its effectiveness as a renewable energy source. The precise and reliable prediction of wind speed is crucial for the effective utilization and harnessing of wind power. This study proposes a novel hybrid methodology for wind speed prediction (WSP) by combining improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and a memory-efficient Reformer model. This hybrid methodology is proposed to improve the accuracy of WSP. This approach involves decomposing the input data into multiple sub-series using the intrinsic mode function (IMF) obtained from the ICEEMDAN algorithm. The resulting sub-series are then processed through a Reformer (REF) model to predict wind speed. The verification of the efficiency and progression of the hybrid model that is proposed is conducted through the utilization of wind speed data obtained from two distinct wind farms. The current WSP methods exhibit a decline in performance as the time ahead increases. Therefore, this study addresses the viability of the proposed model by examining six different time horizons: 5-minutes, 10-minutes, 15-minutes, 30-minutes, 1-hour, and 2-hours. For evaluating the efficiency of proposed model for WSP, ten individual WSP models and ten hybrid WSP models are used for the comparative analysis. Based on the results of the experiments and comparative analysis, it has been observed that the hybrid model proposed in this study exhibits superior performance compared to other models across all time horizons while simultaneously preserving memory efficiency. [ABSTRACT FROM AUTHOR]

The article explores the potential benefits of integrating vertical farming with renewable energy sources such as wind, solar, and hydrogen fuels. Vertical farming is presented as a sustainable solution to the environmental issues caused by traditional agriculture, offering advantages such as reduced water usage, land requirements, and food waste. The authors also highlight the potential for vertical farming to contribute to the green hydrogen economy by utilizing wind power and green oxygen to enhance crop yields and reduce greenhouse gas emissions. The report is written in a clear and concise manner, making it accessible for library patrons conducting research, and is respectful of diverse perspectives. [Extracted from the article]

This study examines the seasonal and intraseasonal modulation of near-inertial wind power associated with fluctuations in unidirectional wind speed in the Bay of Bengal (BoB). For that purpose, we use concurrent measurements of high-resolution in situ near-surface current and wind speed from six moorings in the BoB. It is found that the annual mean of near-inertial wind power in the BoB shows roughly similar magnitude (0.25–0.35 mW m−2) at all the mooring locations. However, in response to the seasonal evolution of monsoonal wind forcing, near-inertial wind power shows significant annual variability, with a maximum during summer (~ 0.4–0.5 mW m−2) and fall (~ 0.3–0.4 mW m−2) and a minimum during winter (~ 0.1 mW m−2) and spring (~ 0.2 mW m−2). In addition, it is also found that modulation of near-inertial wind power due to summer monsoon intraseasonal oscillation (MISO), such as its magnitude, reaches as large as ~ 1 mW m−2 at the mooring in the northern BoB during phases 3–4 of MISO. Using a high vertical resolution of current profile data, the near-inertial kinetic energy (NIKE) budget in the mixed layer in the northern BoB shows good temporal correspondence with the magnitude of the rate of change of NIKE and near-inertial wind power, with a maximum magnitude of the rate of change of NIKE lags the wind power by 24 hr. The NIKE budget also indicates that a significant portion of near-inertial wind power dissipates in the mixed layer and rarely energises the depth regime underneath the mixed layer. [ABSTRACT FROM AUTHOR]

Currently, a standardized design and calculation specification for suction drum foundations has yet to exist in China. The engineering design currently depends mainly on the subjective understanding and engineering experience of the designers, which can be considered somewhat blind and subjective. In this paper, we utilize the offshore wind power project in Yangjiang City, Guangdong Province, as our case study. Building upon domestic and international research results, relevant investigations, design specifications, and engineering applications in related fields, we conduct a systematic study on the design calculation and construction control technology of the suction drum foundation. The document presents the design calculation and inspection of the suction drum foundation. Building on this foundation, we propose a sinking feasibility analysis method and a parameter value method for the suction drum foundation calculation. We also examine the suction drum foundation construction process, examining its control parameters, technology, and standards. Finally, based on the measured data from six four-barrel guided frame platform suction drum foundations that were successfully installed, the proposed design and control method are evaluated, and their effectiveness is verified. The results of this study can provide valuable references for the design and construction of similar suction drum foundation platforms. [ABSTRACT FROM AUTHOR]

Wind energy, as a renewable energy source, offers the advantage of clean and pollution-free power generation. Its abundant resources have positioned wind power as the fastest-growing and most widely adopted method of electricity generation. Wind speed stands as a key characteristic when studying wind energy resources. This study primarily focuses on predictive models for wind speed in wind energy generation. The intense intermittency, randomness, and uncontrollability of wind speeds in wind power generation present challenges, leading to high development costs and posing stability challenges to power systems. Consequently, scientifically forecasting wind speed variations becomes imperative to ensure the safety of wind power equipment, maintain grid integration of wind power, and ensure the secure and stable operation of power systems. This holds significant guiding value and significance for power production scheduling institutions. Due to the complexity of wind speed, scientifically predicting its fluctuations is crucial for ensuring the safety of wind power equipment, maintaining wind power integration systems, and ensuring the secure and stable operation of power systems. This research aims to enhance the accuracy and stability of wind speed prediction, thereby reducing the costs associated with wind power generation and promoting the sustainable development of renewable energy. This paper utilizes an improved Hilbert–Huang transform (HHT) using complementary ensemble empirical mode decomposition (CEEMD) to overcome issues in the traditional empirical mode decomposition (EMD) method, such as component mode mixing and white noise interference. Such an approach not only enhances the efficiency of wind speed data processing but also better accommodates strong stochastic and nonlinear characteristics. Furthermore, by employing mathematical analytical methods to compute weights for each component, a dynamic neural network model is constructed to optimize wind speed time series modeling, aiming for a more accurate prediction of wind speed fluctuations. Finally, the optimized HHT-NAR model is applied in wind speed forecasting within the Xinjiang region, demonstrating significant improvements in reducing root mean square errors and enhancing coefficient of determination. This model not only showcases theoretical innovation but also exhibits superior performance in practical applications, providing an effective predictive tool within the field of wind energy generation. [ABSTRACT FROM AUTHOR]

It is noted that the traditional direct filed-oriented control (DFOC) is widely used in the field of electric power generation from wind due to its fast response dynamic, ease of implementation and simplicity, but this strategy is characterized by the presence of large ripples at the level of both active and reactive powers. This work presents a new algorithm for DFOC strategy of an asynchronous generator (AG) in a wind power (WP) system, which is based on the use of a new nonlinear controller called fractional-order synergetic control–fractional-order proportional-integral (FOSC–FOPI) controller, where the proposed technique parameters are calculated using the particle swarm optimization (PSO) strategy. It has been observed that the DFOC–FOSC–FOPI–PSO strategy is robust and works well in case of changing generator parameters. Three tests were performed to study the behavior of the designed technique under different working conditions, where the behavior of the DFOC–FOSC–FOPI–PSO strategy was compared with the behavior of the traditional DFOC technique in terms of power ripple ratio, overshoot, steady-state error, response time, tracking reference, and current quality. The simulation of the designed technique based on the FOSC–FOPI–PSO strategy of the AG–WP system is carried out using Matlab software, where the simulation results showed that the suggested technique is better than the classical technique (with PI controller) in terms of improving response time of active power (33.33%) and reactive power (10%) in second test, reduction of the steady-state error of reactive power (96.95%) and active power (97.14) in first test, minimization of harmonic distortion of current (96.57%) in third test and significant minimization of ripples of active power (99.67%, 44.69%, and 98.95%) and reactive power (99.25%, 53.65%, and 70.50%) in the three tests. The effectiveness of the DFOC–FOSC–FOPI–PSO strategy is very high, so it can be a reliable solution for controlling various generators. [ABSTRACT FROM AUTHOR]

For decentralized electrification in remote areas, small-sized wind energy systems (WESs) are considered sustainable and affordable solution when employing an efficient, small-sized component converter integrated with a less-sophisticated, cost-effective MPPT controller. Unfortunately, using a conventional buck DC/DC converter as a MPP tracker suffer from input current discontinuity. The latter results in high ripples in the tracked rectified wind power which reduces the captured power and affects system operation especially in standalone applications which are self-sufficient and independent of grid support. Furthermore, these ripples propagate to the machine side causing vibration and torque stress which impacts turbine performance and safety. To solve this issue, a large electrolytic capacitor is placed at the buck converter input to buffer these ripples, yet at the cost of larger size, losses and reduced reliability. Oppositely, the developed C1, D4 and D6 buck converters have the merit of continuous input current at small component-size. In this paper, dynamic modelling of these three converters is developed to select the one with the least input current ripples to replace the traditional buck converter in the considered WES system. Consequently, fluctuations in the tracked power are minimized and the large buffer capacitor is eliminated. This enhances system lifetime, reduces its cost and increases tracking efficiency. Moreover, mechanical power and torque fluctuations are minimized, thus maintaining machine protection. Furthermore, a sensorless MPPT algorithm, based on converter averaged state-space model, is proposed. Being dependent on variable-step P&O algorithm, the proposed approach features simple structure, ease of control and a compromise between tracking time and accuracy besides reduced cost due to the eliminated current sensor. Simulation results verified the effectiveness of the selected converter applying the proposed MPPT approach to efficiently track the wind power under wind variations with cost-effective realization. [ABSTRACT FROM AUTHOR]

Behavioral hearing thresholds and noise localization acuity were determined using a conditioned avoidance/suppression procedure for three Helmeted guineafowl (Numida meleagris). The guineafowl responded to frequencies as low as 2 Hz at 82.5 dB SPL, and as high as 8 kHz at 84.5 dB SPL. At a level of 60 dB SPL, their hearing range spanned 8.12 octaves (24.6 Hz–6.86 kHz). Like most birds, they do not hear sounds above 8 kHz. However, the guineafowl demonstrated good low-frequency hearing (frequencies below 32 Hz), showing thresholds that are more sensitive than both the peafowl and pigeon, both of which hear infrasound. It thus appears that infrasound perception may be more common than previously thought and may have implications for species that inhabit areas with wind energy facilities. The guineafowls' minimum audible angle for a 100-ms broadband noise burst was 13.8 °, at the median for birds and near the mean for mammals. Unlike in mammals, the small sample of bird species and limited representation of lifestyles do not yet allow for meaningful interpretations of the selective pressures or mechanisms that underlie their abilities to locate sound sources. [ABSTRACT FROM AUTHOR]

Better understanding on the phases of Indian summer monsoon i.e., onset, progress and withdrawal helps in the decision making and proper management. In this paper, date of onset of monsoon (DOM) and date of withdrawal of monsoon (DWM) is estimated using the long-term daily rainfall data observed by the India Meteorological Department (IMD) and cumulative rainfall anomaly concept, as the onset/withdrawal represents a signature of rainfall transition. The results are promising with a better match between the estimated DOM and IMD announced DOM over Kerala. The length of monsoon season variability is also analysed. The concept of onset at grid point (OGP) in India is also evaluated and progress of monsoon is monitored by considering the latitudinal variation, persistent & strength of rainfall in the continental India. The zonal classification of the spread of monsoon in terms of the intensity and time (duration) is presented. Zone wise pentad analysis of onset clearly signifies the progress of monsoon and its dependency on various physical factors like SST, OLR, TTG, ITCZ, Energy budget and wind circulation. The impact of ENSO on the OGP is brought out, which clearly shows that DOM, DWM and progress is almost influenced by the largescale processes. The intensity–duration–frequency analysis quantified the actual ISM length, seasonal rainfall and rainy days at all locations in India. This study will help modellers in better understanding of onset and progress of monsoon dynamics in India and can be integrated with NWP for the accurate and advance prediction of DOM and the progress. [ABSTRACT FROM AUTHOR]

Offshore wind power is clean energy with rapid growth in recent years. As a key part of wind turbines, improving the combination performance of wind turbine cable insulation has a crucial impact on the development of wind power systems. In this paper, kaolin is selected to improve the tensile strength of Ethylene-Propylene-Diene Monomer (EPDM) rubber, and Boron Nitride Nanosheeets (BNNSs) with good electrical insulation and thermal conductivity are co-doped into kaolin/EPDM to improve the breakdown strength and thermal conductivity of the composite. The results show that the properties of the composites are improved when the powders are doped into EPDM. When the kaolin doping amount is 30wt%, the dielectric properties and the mechanical properties are improved, but the breakdown strength has deteriorated. Based on 30wt% kaolin content, BNNSs are added to EPDM. The breakdown strength is improved. The breakdown strength of the 30wt% Kaolin/5wt%BNNSs co-doped EPDM is 83.33 kV/mm. In addition, due to the synergistic effect between the two powders, the tensile strength of the composite is increased to 8.06 MPa. Meanwhile, with the increase of BNNSs, the thermal conductivity of composite is improved. It increases to 1.247 W/(m⋅K) This work has important guiding significance for improving the combination performance of the wind turbine cable insulation. [ABSTRACT FROM AUTHOR]

An extreme torrential rain (ETR) event occurred in Henan Province, China, during 18–21 July 2021. Based on hourly rain-gauge observations and ERA5 reanalysis data, the ETR was studied from the perspective of kinetic energy (K), which can be divided into rotational wind (VR) kinetic energy (KR), divergent wind kinetic energy (KD), and the kinetic energy of the interaction between the divergent and rotational winds (KRD). According to the hourly precipitation intensity variability, the ETR process was divided into an initial stage, a rapid increase stage, and maintenance stage. Results showed that the intensification and maintenance of ETR were closely related to the upper-level K, and most closely related to the upper-level KR, with a correlation coefficient of up to 0.9. In particular, the peak value of hourly rainfall intensity lagged behind the KR by 8 h. Furthermore, diagnosis showed that K transformation from unresolvable to resolvable scales made the ETR increase slowly. The meridional rotational wind (uR) and meridional gradient of the geopotential (φ) jointly determined the conversion of available potential energy (APE) to KR through the barotropic process, which dominated the rapid enhancement of KR and then caused the rapid increase in ETR. The transportation of K by rotational wind consumed KR, and basically offset the KR produced by the barotropic process, which basically kept KR stable at a high value, thus maintaining the ETR. [ABSTRACT FROM AUTHOR]

Renewable energy sources are seen as a sustainable solution to the problem of global energy security. Among the renewable energy sources, wave energy has great prospects for development in a few countries, including South Africa. However, South Africa's wave energy projects are still underinvested in practice compared to wind energy and solar PV. This paper investigates several questions related to the influence of both quantitative and qualitative factors on the effectiveness of wave energy projects (WEPs) and the appropriate placement for WEP in South Africa. For this purpose, a novel two-phase framework novel two-phase data envelopment analysis (DEA) supporting integrated multiple criteria decision-making (MCDM) framework is proposed. The first phase aims to identify potential locations for WEPs and calculate the technical advantage of these locations using the DEA model. In the second phase, other qualitative criteria, which affect the sustainable development of WEPs, are identified. Based on expert surveys, potential locations are analyzed and ranked by a novel integrated MCDM approach called OPA-EDAS. In the proposed approach, the advantages of the Ordinal Priority Approach (OPA) are utilized to simultaneously determine the weight of the criteria and prioritize the alternatives. However, the results of OPA depend on the priorities of the experts participating in the assessment. Therefore, this study attempted to overcome that by integrating the EDAS technique to assess the expertise. Furthermore, the DEA model is applied to increase the objectivity of the results. In addition, the robustness of the study's findings is validated by comparing the location with upcoming WEPs in South Africa. The result shows that the coast of Cape Nature Walker Bay has the most effectiveness for South Africa's WEPs. [ABSTRACT FROM AUTHOR]

As demand for renewable energy is rising, wind power development is rapidly growing worldwide. In its wake, conflicts arise over land use changes converting pristine nature into industrial power plants and its associated adverse biodiversity effects, crowned by one of the most obvious and deadly consequences: bird collisions. Most post-construction studies report low levels of avian mortality, but the majority of these studies are conducted primarily on larger birds. However, the diversity and abundance of small passerine birds are rarely reflected in the carcass surveys, although they in numeric proportion to their abundances should be the most numerous. The assumption that surveys find all carcasses seems thus rarely fulfilled and passerine mortality is likely to be grossly underestimated. We therefore designed an experiment with dummy birds to estimate mortality of small-bodied passerines and other small-bodied birds during post-construction surveys, tested in a medium-sized wind farm in western Norway. The wind farm was surveyed weekly during the migration periods by carcass survey teams using trained dogs to find killed birds. The dogs in the carcass surveys were more successful in locating the large than the small dummy birds (60–200 g), where they found 74% of the large dummy birds. Detecting the smaller category (5–24 g) was more demanding and the dogs only found 17% of the small dummy birds. Correcting the post-construction carcass survey outcome with the results from the experiment leads to an almost fourfold increase in estimated mortality rates, largely due to the low detection rate of the smallest category. The detection rates will naturally vary between wind farms, depending on the specific habitat characteristics, the efficiency of the carcass surveys and the search intervals. Thus, implementing a simple experiment with dummy birds to future post-construction surveys will produce more accurate estimates of the wind turbine mortality rates, and thus improve our understanding of the biodiversity effects of conforming to a more sustainable future. [ABSTRACT FROM AUTHOR]