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The transport of oversized loads, such as wind turbine components, represents a key logistical challenge due to specific technical and regulatory requirements. The development of the renewable energy sector, particularly wind energy in Poland, has significantly increased the demand for this type of transport. The implementation of wind farm construction projects requires not only advanced technological solutions but also special attention to transport safety and the organization of logistical processes. This study employed the FMEA (Failure Mode and Effects Analysis) risk analysis method, which allows for the identification of potential defects and their causes. Data were collected through surveys, interviews with representatives of transport companies, and field observations. The research sample included 11 companies specializing in oversized transport in Poland and European countries. Based on the gathered information, 15 typical risks associated with the transport of wind turbine components were identified. The most significant risks include the possibility of road accidents and discrepancies between the actual dimensions of the cargo and the transport documentation. The results highlight the need for improvements in route planning, precise verification of cargo parameters, and better management of administrative processes related to obtaining permits. The development of the wind energy sector and dynamic investments in wind farms make the optimization of oversized transport a crucial element in supporting the execution of eco-friendly projects and sustainable development. [ABSTRACT FROM AUTHOR]

Combining wind and hydropower facilities makes it possible to solve the problems caused by power supply shortages in areas that are remote from the central energy system. Hydropower plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power outputs from wind power plants, and the limitations associated with them are significantly reduced when they are integrated into the regional energy system. Such an integration contributes to increasing the efficiency of renewable energy sources, which in turn reduces our dependence on fossil resources and decreases their harmful impact on the environment, increasing the stability of the power supply to consumers. The results of optimisation calculations show that a consumer load security of 95% allows the set capacity of RESs to be used in the energy complex up to 700 MW. It is shown here that the joint operation of HPPs and WPPs as part of a power complex and hydraulic energy storage allows for the creation of a stable power supply system that can operate even in conditions of variable wind force or uneven water flow. The conclusions obtained allow us to say that the combination of hydro- and wind power facilities makes it possible to solve the problem of power supply deficits in the regions of Kazakhstan that are remote from the central power station. At the same time, hydroelectric power plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power output from wind power plants and significantly reduce the limitations associated with them during their integration into the regional energy system. [ABSTRACT FROM AUTHOR]

Renewable electricity sources are now widely used worldwide. Currently, the most common sources are those that use energy contained in biomass, water, sun, and wind. When connected to a medium-voltage grid, individual wind power plants must meet specific conditions to maintain electricity quality. This article presents field study results on the impact of switching operations (turning the power plant on and off) at a 2 MW Vestas V90 wind turbine on the voltage parameters at the connection point of a farm located 450 m from the source. The analysis showed that the wind turbine under study significantly affects customers' voltage near the source, causing it to increase by approximately 2.5%. Sudden cessation of generation during the afternoon peak causes a 3% voltage fluctuation, potentially affecting equipment sensitive to rapid voltage changes. [ABSTRACT FROM AUTHOR]

In this work, a computer Simulink model of a wind power plant has been developed, which uses a magnetic gearbox instead of a mechanical gearbox and also contains a synchronous permanent magnet generator. A separate Simulink model of a magnetic gearbox built on the basis of a modulated magnetic field in the air gap was developed, which allows to study the stability of its operation both in steady-state and transient modes. Calculations of various dynamic modes of the wind power plant’s operation were carried out, based on the developed model, such as the starting mode, an instantaneous increase in the wind speed acting on the wind turbine, and an increase in the load of the electric generator. According to the results of the calculations, it is shown that in transient modes, when short-term overloads occur, both rotors of the magnetic gearbox can fall out of synchronous motion for a certain period of time and then, depending on the parameters of the gearbox (as well as its other elements), the electromechanical system either reaches a certain operating steady-state mode or loses the ability to transfer mechanical power from the wind turbine to the generator. It has been shown that the use of a more powerful magnetic gearbox, with an increased value of the maximum magnetic torque, allows of a more overload-resistant operation of both: a gearbox and the wind plant as a whole. References 9, figures 10. [ABSTRACT FROM AUTHOR]

Combining wind and hydropower facilities makes it possible to solve the problems caused by power supply shortages in areas that are remote from the central energy system. Hydropower plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power outputs from wind power plants, and the limitations associated with them are significantly reduced when they are integrated into the regional energy system. Such an integration contributes to increasing the efficiency of renewable energy sources, which in turn reduces our dependence on fossil resources and decreases their harmful impact on the environment, increasing the stability of the power supply to consumers. The results of optimisation calculations show that a consumer load security of 95% allows the set capacity of RESs to be used in the energy complex up to 700 MW. It is shown here that the joint operation of HPPs and WPPs as part of a power complex and hydraulic energy storage allows for the creation of a stable power supply system that can operate even in conditions of variable wind force or uneven water flow. The conclusions obtained allow us to say that the combination of hydro- and wind power facilities makes it possible to solve the problem of power supply deficits in the regions of Kazakhstan that are remote from the central power station. At the same time, hydroelectric power plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power output from wind power plants and significantly reduce the limitations associated with them during their integration into the regional energy system.

Wind energy is an eco-friendly, renewable, domestic, and infinite resource. These factors render the construction of wind turbines appealing to nations, prompting numerous governments to implement incentives to augment their installed capacity of wind turbines. Alongside augmenting the installed capacity of wind turbines, identifying suitable locations for their installation is crucial for optimizing turbine performance. This study aims to evaluate potential sites for wind power plant installation via a GIS, a mapping technique. The Analytic Hierarchy Process (AHP) was employed to assess the locations, including both quantitative and qualitative aspects that significantly impact the wind farm suitability map. Utilizing the GIS methodology, all datasets were examined through height and raster transformations of land surface temperature, plant density index, air pressure, humidity, wind speed, air temperature, land cover, solar radiation, aspect, slope, and topographical characteristics, resulting in the creation of a wind farm map. The correlation between the five-year meteorological data and environmental parameters (wind direction, daily wind speed, daily maximum and minimum air temperatures, daily relative humidity, daily average air temperature, solar radiation duration, daily cloud cover, air humidity, and air pressure) influencing the wind power plant in Iğdır province, including Iğdır Airport, Karakoyunlu, Aralık, and Tuzluca districts, was analyzed. If wind energy towers are installed at 1 km intervals across an area of roughly 858,180 hectares in Igdir province, an estimated 858,180 GWh of wind energy can be generated. The GIS-derived wind power plant map indicates that the installation sites for wind power plants are located in regions susceptible to wind erosion. [ABSTRACT FROM AUTHOR]

Introduction. When driving cars in winter on intercity routes, problems may arise if the highways are covered with snow as a result of heavy snowfalls, which can last for several days or more, and movement during this period becomes impossible. An analysis of statistical data on weather events in winter has shown that in many regions, the closure of trails as a result of prolonged snowfalls can reach up to fifteen percent. In this case, an autonomous energy source, which it receives through the use of environmental properties, can provide significant assistance in improving the situation and increasing safety. The paper considers the technical solution and carries out a theoretical analysis of its characteristics aimed at solving the problem of autonomous power supply of the car interior in severe weather conditions.Materials and methods. The paper presents a technical solution and a theoretical analysis of its characteristics aimed at solving the problem of autonomous power supply of the car interior in severe weather conditions.Results. Based on the results of the information search, the design of a compact low-power wind power plant is proposed. The calculation of the heat loss of the car interior, the characteristics of a compact wind power plant was performed and the generated power required to heat the car interior in an extreme situation was determined.Discussion and conclusions. It has been established that the presented design of a low-power wind power plant can be used as a prototype for the development of an industrial design of an autonomous energy source for heating a car in extreme conditions. Similar installations can be used in other industries, for example, tourism, agriculture, and geological exploration.

The paper developed a Simulink computer model of a small-power wind power plant (3 kW), which uses a magnetic gearbox instead of a mechanical gearbox, and also contains a synchronous generator with permanent magnets. Based on this model, calculations of related mechanical and electrical processes were carried out in two modes of its operation - start-up mode and mode of instantaneous increase in wind speed acting on the wind turbine (from 10 m/s to 14 m/s and then again to 10 m/ with). According to the results of the calculations, it is shown that in transient modes when short-term dynamic overloads occur, both rotors of the magnetic gearbox may fall out of synchronous motion for a certain period of time and then, depending on the parameters of the gearbox (as well as its other elements), the electromechanical system or reaches a certain working steady state, or loses the ability to transmit mechanical power from the wind turbine to the generator due to the rotors of the magnetic gearbox falling out of synchronism. At the same time, the stability of the wind power plant as a whole depends mainly on the value of the maximum magnetic moment of the reducer. Bibl. 13, Fig. 8. [ABSTRACT FROM AUTHOR]

The Timor system is one of the large systems in the East Nusa Tenggara region. Based on the general plan for electricity supply for 2021-2030, there is a plan to interconnect a 2x11 MW wind power plant. The addition of wind power plants will pose a considerable threat to the system due to the intermittency nature of renewable energy plants. Therefore, a comprehensive grid impact study is needed to convince network managers that adding wind farms will not cause disruptions to the system either locally or in general and is expected to strengthen the electricity system. The power flow simulation results, installing a 2x11 MW wind farm on the Timor system can improve voltage quality and reduce losses on both 70 and 150 kV systems. For transient stability, the frequency value on the Timor system still meets the grid code requirements. In addition, the simulation results of the intermittency impact of the wind power plant output show that the Timor system is still in a stable condition. The stability of the rotor angle of the existing power plant when the transient stability simulation is carried out shows that it is still in a balanced condition. [ABSTRACT FROM AUTHOR]

In the summer of 2021, a federal law concerning the regulation of greenhouse gas emissions appeared in the Russian Federation - Federal Law No. 296 dated 02.07.2021 "On Limitation of Greenhouse Gas Emissions". The law defines the basis of legal regulation of relations in the sphere of activities accompanied by greenhouse gas emissions and carried out on the territory of Russia, as well as on the continental shelf, in the exclusive economic zone of the Russian Federation, in the Russian sector of the Caspian Sea. The law on limiting greenhouse gas emissions introduces the following concepts: (a) greenhouse gases; (b) climate projects; (c) carbon units; (d) carbon footprint as the total volume of greenhouse gas emissions and their absorption in the course of production/provision of a service. The concept of hydrogen civilization, the foundations of which were laid by the romanticist and pioneer of the Hydrogen Era, Prof. T.N. Vesiroglu, attracts attention of more and more scientists and engineers.The hydrogen civilization will require a significant amount of hydrogen for its implementation. For the current stage of development of civilization, the volume of hydrogen generated annually must be at least 560 million tons. The most interesting is the combination of renewable and environmentally friendly non-renewable energy sources to obtain the universal energy carrier hydrogen (Concept of alternative energy and ecology, A.L. Gusev and T.N. Veziroglu, 2000). In particular, wind-hydrogen energy is of great interest as a promising area of innovation in the field of energy at remote sites. The hydrogen civilization will require a significant amount of hydrogen for its implementation. For the current stage of development of civilization, the volume of hydrogen generated annually must be at least 560 million tons. Wind-hydrogen energy can make a great contribution to the implementation of the hydrogen energy concept. It is important that power supply to remote areas requires significant financial costs, and wind energy in this regard is the optimal solution. Thus, the cost of 1 km of power line can range from 20 to 50,000 euros. For remote sites, the cost of creating such a line, as well as the cost of its maintenance in harsh climates, will be extremely high. At the same time, the cost of a wind turbine is equal to the cost of 1 km of power line, and its service life can reach 30 years. However, to optimize the use of wind turbines and wind-hydrogen power plants, it is important to take into account the emission of pollutants into the atmosphere during the production of elements of wind power plants and wind-hydrogen power plants (WPP). The article outlines the main provisions of a new method for determining emissions of pollutants during the life cycle of wind power plants (wind farms) using aggregated indicators. The rationale for the use of aggregated indicators is given. An algorithm is described for determining emissions of pollutants CO 2 eq (carbon dioxide), SO 2 eq (sulfur dioxide) and PO 4 eq (phosphates) during the production of elements of wind turbines and wind farms. The results of calculations of emissions of CO 2 eq, SO 2 eq and PO 4 eq during the life cycle for onshore wind farms (Cossack wind farm and Arkhangelsk wind farm) with an installed capacity of 100 and 340 MW are presented and the environmental effect of their use is determined. Calculated emissions of pollutants, which can be prevented when choosing the wind farms as power sources and determined the environmental effect of their use when comparing with thermal power plants. [ABSTRACT FROM AUTHOR]

Due to the constant increase in energy consumption, remoteness from industrial centers, the need to import organic fuel for economic activities and livelihoods of the population, a wider deployment of wind power plants (WPPs) in hard-to-reach areas of the Arctic is required. The key element influencing the efficiency of a WPP is the wind wheel, the design of which is associated with certain difficulties due to the extreme climatic conditions in the Arctic. The presented work describes an approach to digital design of the aerodynamic shape of a wind turbine blade based on parametric optimization technology. The target indicator is the wind energy efficiency (WEE), which is calculated by direct numerical modeling of the aerodynamics problem using modern computational methods, as well as high-performance supercomputer technologies. The introduction of digital design and modeling principles has enabled the integration of geometric models and associated engineering modeling tools into the computer environment. The main concept of the approach is to describe the geometric characteristics of the blade with a finite number of parameters, changing which one can obtain the shape of the wind wheel blade in a wide range of possible configurations. For each shape, a computational CFD model is created, which, based on the numerical solution of the Navier–Stokes viscous flow equations, makes it possible to determine target indicators in the form of aerodynamic characteristics of the blade at a given wind speed. An example of the use of parametric optimization technology for the design of a wind wheel intended for operation in the Arctic regions is considered. The functionality of the concept for determining the shape of the blade in single-mode and multimode options for using a wind wheel has been demonstrated. It is shown that the obtained geometric characteristics make it possible to improve the target performance of a typical blade used in practice. For a WPP with a power of 100 kW with a wind wheel with a diameter of 24 m, solutions were obtained that provide a WEE value of 0.45 in the range of design wind speeds from 6 to 9 m/s. [ABSTRACT FROM AUTHOR]

Integrating wind power plants into the electricity grid poses challenges due to the intermittent nature of wind energy generation. Energy storage systems (ESSs) have shown promise in mitigating the intermittent variability associated with wind power. This paper presents a distributionally robust optimization (DRO) model for sizing energy storage systems to dispatch wind power plants. The variable wind power is formulated as a moment-based ambiguity set. Dispatchability is described by the expected value of the insufficient power of wind power relative to the dispatch command, which is a sum of nonlinear functions and is taken as the optimal index. A deterministic semi-definite positive model is derived to solve the problem effectively. Numerical studies are conducted to demonstrate the effectiveness and advantages of the proposed method. [ABSTRACT FROM AUTHOR]

Even the best project of a wind power plant (WPP) can fail if there are not favourable legal regulations for its completion. Most of the research has dealt with identification of various obstacles to implement WPP (political, social, legal, environmental). Analyses of legal barriers (LBs) have been usually made at a high degree of generality. This paper offers a thorough overview of LBs for localization of WPPs in Poland. This is the country where restrictive regulations have blocked the possibility of implementing such projects in many areas. Unfriendly law may persuade investors to choose worse wind turbines foundation conditions. In our research we focus on a problem little dealt in scientific studies, i.e. on the localization of WPP in difficult geotechnical conditions. The article presents the analytical engineering method, which includes the mutual influence between foundation piles in carrying on the construction load on a subsoil. The paper presents the geotechnical parameters responsible for calculation outcomes, the theoretical basis of the curve analysis method of settlement of a single pile and of the calculation of piles settlement working in a group and fastened with a stiff head. It also shows the effect of pile arrangement in a foundation and a load distribution of in-dividual piles, as well as a settlement and leaning of foundation of wind power turbine towers. The method enables a more precise, safer and optimal design of a wind turbine foundation.

Abstract The challenge of predicting wind speeds to facilitate site selection and the consistent operation of wind power plants in coastal regions is a global concern. The output of wind turbines is subject to fluctuations corresponding to changes in wind speed. The unpredictable characteristics of wind patterns introduce vulnerabilities to wind power facilities in wind power plants. To address this unpredictability, an effective strategy involves forecasting wind speeds at specific locations during wind power plant operations. While previous research has explored various machine learning algorithms to tackle these issues, satisfactory results have not been achieved, and Bangladesh faces challenges in this regard, especially in low-wind speed areas. This study aims to identify the most accurate machine learning-based algorithm to forecast the short-term wind speed of two areas (Kutubdia and Cox's Bazar) located on the eastern coast of Bangladesh. Wind speed data for a span of 21.5 years, ranging from January 2001 to June 2022, were sourced from two outlets: the Bangladesh Meteorological Department and the website of NASA. Wind speed has been forecasted using 14 different regression-based machine learning models with a comprehensive overview. The results of the experiment highlight the exceptional predictive performance of a boosting-based ensemble method known as categorical boosting, especially in the context of forecasting wind speed data obtained from NASA. Based on the testing data, the evaluation yields remarkable results, with coefficients of determination measuring 0.8621 and 0.8758 for wind speed in Kutubdia and Cox's Bazar, respectively. The study underscores the critical importance of prioritizing optimal turbine site selection in the context of wind power facilities in Bangladesh. This approach can yield benefits for stakeholders, including engineers and project owners associated with wind projects.

Hybrid power plant system is an excellent option for providing electricity for remote and rural locations where access of grid is not feasible or economical. In this paper, a renewable energy-based system which is a combination of wind and hydro power plant is considered to produce electricity. Where, wind power plant has a provision of single rotor and two generators to produce electricity and hydro power plant works as a standby. Some differential equations have been derived with the help of Markov process and solved by Laplace transformation. Reliability, availability, cost benefits and sensitivity analysis of wind–hydro power plant (WHPP) have been derived and illustrate with the help of their graphs. The purpose of this work is to supply significant amount of reliable and renewable energy by combined WHPP and evaluate the reliability characteristics of WHPP. Combining, wind with the hydropower is one way to make the grid more reliable. [ABSTRACT FROM AUTHOR]

The depletion of fossil fuels, environmental issues, and climate change make the development of renewable energy, especially wind energy, essential. The main challenge in developing wind energy is selecting suitable locations for power plants, where land roughness plays a significant role. This study aimed to prioritize suitable areas based on land roughness using remote sensing in Kiashahr. Land use classification results by the SVM algorithm from 2000 to 2020 showed changes in 2,957.66 hectares of the region. Predicted maps from Markov Cellular Automata models for 2030 were used to ensure practical application of results for future years. The simulated map was gridded based on Wieringa roughness length data to generate maps of roughness length and classes. Results showed that 84 cells, equivalent to 1,363.98 hectares, in the first and second classes have the best potential for wind power plants. Additionally, land use maps for 2030 indicated that a large part of the region is used for agriculture, mostly rice cultivation. These areas have a roughness length of 0.25 m for only two months of the year, and for the rest of the year, they have a roughness length of 0.1 m (class 4) and 0.03 m (class 3). Overall, considering a roughness length of up to 0.25 meters, 552 cells, equivalent to 8,963.36 hectares, were identified as suitable for wind power plants. The findings of this research can help identify suitable areas for wind power plant construction and assist in modeling wind speed near the hub of tall wind turbines. [ABSTRACT FROM AUTHOR]

The possibility of stray loss reduction in permanent magnets by reducing the influence of higher harmonics on the magnetic field in the air gap is considered. Various types of stator windings are considered and design solutions are proposed for choosing the optimal shape of magnets in radially excited generators in terms of reducing higher harmonic and, consequently, rotor losses. When solving the problems, methods of numerical modeling of stationary and nonstationary magnetic fields are used. [ABSTRACT FROM AUTHOR]

In the field of energy networks, for their effective functioning, it is necessary to distribute the required load between all online generating units in a proper way to cover the demand. The load schedule is obtained by solving the so-called Economic Dispatch Problem (EDP). The EDP can be solved in many ways, resulting in a power distribution plan between online generating units in the network so that the resulting price per unit of energy is minimal. This article focuses on designing a distributed gradient algorithm for solving EDP, supplemented by models of renewable sources, Battery Energy Storage System (BESS), variable fuel prices, and consideration of multiple uncertainties at once. Specifically, these are: time-variable transport delays, noisy gradient calculation, line losses, and drop-off packet representations. The algorithm can thus be denoted as robust, which can work even in unfavorable conditions commonly found in real applications. The capabilities of the presented algorithm will be demonstrated and evaluated on six examples. [ABSTRACT FROM AUTHOR]

This article deals with the AGC design of diverse sources-integrated multi-area systems. Area 1 is the combination of solar PV, wind farm, and thermal units. Areas 2 and 3 combine wind farms, hydropower, and thermal units. Skill optimization algorithm (SOA) is used to simultaneously optimize secondary controllers' gains and other parameters. The various helpful performance indices, like ITSE, ISE, ITAE, and IAE, are compared, and it found that the ISE is the best performance indices. The proposed cascaded NF-PDF-PIDF controller outperforms PDF-PIDF and PIDF in terms of the system's dynamic performance when compared to those two. It is also found that integrating solar PV and energy storage, like SMES, proves dynamic responses. The impacts of combining HVDC and AC tie-lines on system response are also studied. It is found that parallel AC-HVDC tie-lines provide better dynamics than AC tie-lines alone. Finally, the resiliency of the SOA-optimized proposed cascaded (CNF-PDF-PIDF) has been applied for a broad change of system loading. It is revealed that the CNF-PDF-PIDF controller's performances at nominal conditions are resilient, and there is no need to reset the controller multiple times when the system loading varies. [ABSTRACT FROM AUTHOR]

The challenge of predicting wind speeds to facilitate site selection and the consistent operation of wind power plants in coastal regions is a global concern. The output of wind turbines is subject to fluctuations corresponding to changes in wind speed. The unpredictable characteristics of wind patterns introduce vulnerabilities to wind power facilities in wind power plants. To address this unpredictability, an effective strategy involves forecasting wind speeds at specific locations during wind power plant operations. While previous research has explored various machine learning algorithms to tackle these issues, satisfactory results have not been achieved, and Bangladesh faces challenges in this regard, especially in low-wind speed areas. This study aims to identify the most accurate machine learning-based algorithm to forecast the short-term wind speed of two areas (Kutubdia and Cox's Bazar) located on the eastern coast of Bangladesh. Wind speed data for a span of 21.5 years, ranging from January 2001 to June 2022, were sourced from two outlets: the Bangladesh Meteorological Department and the website of NASA. Wind speed has been forecasted using 14 different regression-based machine learning models with a comprehensive overview. The results of the experiment highlight the exceptional predictive performance of a boosting-based ensemble method known as categorical boosting, especially in the context of forecasting wind speed data obtained from NASA. Based on the testing data, the evaluation yields remarkable results, with coefficients of determination measuring 0.8621 and 0.8758 for wind speed in Kutubdia and Cox's Bazar, respectively. The study underscores the critical importance of prioritizing optimal turbine site selection in the context of wind power facilities in Bangladesh. This approach can yield benefits for stakeholders, including engineers and project owners associated with wind projects. [ABSTRACT FROM AUTHOR]

The introduction of additional controllers is essential in modern electric power systems to enhance their stability, particularly during disturbances. One effective method is the implementation of power system stabilizers (PSS). However, precise coordination of PSS equipment is necessary to determine the optimal locations and parameters. This study focuses on the optimal analysis of Multi-Band PSS3C (MB-PSS3C) coordination in integrated Wind Power Plant (WPP) systems in South, Southeast, and West Sulawesi (Sulselrabar). An artificial intelligence approach, utilizing the Mayfly Optimization Algorithm (MOA), is suggested for optimizing both the location and parameters of the PSS. Comparative investigations were conducted to assess the efficacy of MB-PSS3C in comparison with SB-PSS1A and MB-PSS2B, based on previous research. The performance analysis employed the time domain simulation method, reviewing the speed deviation response, field voltage response, PSS output voltage response, and rotor angle response for each generator. Eigenvalue analysis was performed for each control scheme. Load changes were applied to generators 1 (BAKARU) and 11 (WPP SIDRAP) to evaluate the performance of the system. The application of the MOA-based MB-PSS3C results in an increased damping ratio, improved speed response, and a more optimal rotor angle. MB-PSS3C provides a larger additional damping signal to the generator exciter, as indicated by the increase in the field voltage on the generator.

This article highlights current issues related to the problem of variability of wind power generation, which is becoming increasingly important as wind power’s contribution to the overall energy balance of many countries grows. Various aspects of wind flow volatility, including its random and deterministic components, are considered. The random component is associated with unpredictable changes in wind speed and direction, while the deterministic component is due to known patterns, such as daily and seasonal variations. The article proposes different methods for levelling the stochasticity of wind power flows. This is important for the stability and reliability of the power system, as it reduces the likelihood blackouts and ensures a more even distribution of load. The article also gives examples of the economic and environmental impact of using the proposed methods.

In this work, a computer Simulink model of a wind power plant has been developed, which uses a magnetic gearbox instead of a mechanical gearbox and also contains a synchronous permanent magnet generator. A separate Simulink model of a magnetic gearbox built on the basis of a modulated magnetic field in the air gap was developed, which allows to study the stability of its operation both in steady-state and transient modes. Calculations of various dynamic modes of the wind power plant’s operation were carried out, based on the developed model, such as the starting mode, an instantaneous increase in the wind speed acting on the wind turbine, and an increase in the load of the electric generator. According to the results of the calculations, it is shown that in transient modes, when short-term overloads occur, both rotors of the magnetic gearbox can fall out of synchronous motion for a certain period of time and then, depending on the parameters of the gearbox (as well as its other elements), the electromechanical system either reaches a certain operating steady-state mode or loses the ability to transfer mechanical power from the wind turbine to the generator. It has been shown that the use of a more powerful magnetic gearbox, with an increased value of the maximum magnetic torque, allows of a more overload-resistant operation of both: a gearbox and the wind plant as a whole. References 9, figures 10.

The provisions of the Act on promoting electricity generation in offshore wind farms have been in force since 18 February 2021. They are intended to simplify administrative procedures for obtaining permits and approvals for the implementation of offshore projects and to contribute to the fulfillment of Poland’s international obligations to maintain and increase the mandatory share of renewable energy sources. The Act also amended the Energy Law, which introduced provisions regulating the new license fee. Calculation and payment of this levy to the Energy Regulatory Office is mandatory for companies in the energy sector that conduct business operations involving production of electricity in offshore wind farms. In the author’s opinion, these entities are payers of a new tax, paradoxically referred to as fee, which, contrary to the original assumptions, was not introduced due to extra-legal factors. The article analyzes the legal regulations that introduce taxation of offshore wind farms in Poland against the background of controversial normative solutions concerning the property tax imposed on onshore wind power plants.

Site selection for wind power plant (WPP) installation is a complex process that includes not only technical requirements but also physical, economic, social, and environmental sanctions. This study was carried out to determine optimal sites for WPP installation within the borders of Çanakkale province using spatial multi-criteria decision analysis (MCDA). Within the scope of the study, sites with a high level of suitability where a WPP can be established were determined by the geographic information system (GIS) and the analytical hierarchy process (AHP). The results were examined in two ways: by excluding and not excluding forest areas. After creating the two separate suitability maps, the annual electrical power generation potential (GP) map of the study area was generated. The results show that for the case where the forest areas were excluded, 67.26% of the study area is restricted and 29.94% is highly suitable, and for the case where the forest areas were not excluded, 58.94% is restricted and 36.25% is highly suitable. The total GP value of the highly suitable sites is 104,061.61 GWh/year. When the locations of existing WPPs were examined for control purposes, it was seen that the majority of them were located inside the areas with high suitability and outside the noninstallable areas, but some of them were established in forested areas. [ABSTRACT FROM AUTHOR]

Renewable energy sources are particularly important in clean energy transitions and need to be considered in Generation Expansion Planning (GEP) problems due to low cost, ease of installation, and ability to implement Demand Response (DR) programs. However, challenges such as the stochastic nature of renewable energy sources, consumer unawareness regarding participation in DR programs, and difficulties in integrating some resources have posed challenges to the use of these resources in the GEP problem. This paper addresses these challenges by using the Weibull distribution function to model wind power plants' uncertainty and rewards and penalties to motivate consumer participation in the GEP problem. To achieve these objectives, initially, the adequacy assessment of the generation system is performed analytically using the reliability index, which includes Expected Energy Not Supplied (EENS), considering the forced outage rate of generators in the DIgSILENT power factory through Python programming. Subsequently, an optimized GEP model is presented to enhance the generation system's adequacy against short-term demand for the next year. In this model, wind farms along with the DR program are integrated and optimized using the genetic algorithm, employing Python programming. The genetic algorithm works by selecting the number of existing turbines in the wind power plant and the level of consumer participation needed to reduce the EENS to the desired value at the minimum cost. Validation of the proposed model is conducted on a 9-bus network. The strength of the presented method lies in its applicability to real-world networks modeled in the DIgSILENT power factory. [ABSTRACT FROM AUTHOR]

This paper examines the consideration of the design features of closed-cycle pumped-storage hydroelectric power stations, as well as other gravitational energy accumulators to ensure the accumulation of energy from renewable energy sources by means of a comparative analysis. The tasks of research are a rational way of accumulating electricity from wind and solar power plants require a comprehensive approach, taking into account all the features of renewable energy sources. The growing installed capacity of photo and wind power plants is associated with the need to solve the problem of instability of electric power generation over time. The analysis of various storage technologies, including gravity accumulators, hydroaccumulating power plants of underground and marine types, thermal storage, emphasizes that the closed-cycle pumpedstorage hydroelectric power stations is an effective energy accumulator for autonomous energy systems of renewable energy. A comparative analysis of closed-cycle pumped-storage hydroelectric power stations showed that stations of this type, in comparison with classic ones, require a smaller amount of working fluid to ensure the same power, which is achieved due to the creation of a higher head up to 600m and the fact that the external source of water needed only to cover system losses. The reduction of environmental impacts is also established, as the installation requires a smaller size of exclusion areas, and the possibility of using tunnels and underground stations minimizes the impact on the environment. It was established that the number of potential places for the installation of closed-cycle pumped-storage hydroelectric power stations is over 615,000 around the world with a total accumulation potential of 23.1 million GWh. [ABSTRACT FROM AUTHOR]

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Ensuring the quality of energy supply to remote regions is relevant for grid companies and the state. One of the solutions to this problem is the use of renewable energy sources to generate electrical energy. Given this, the article considers an integrated approach to designing combined autonomous energy systems of an individual residential building based on renewable energy sources with the complete replacement of traditional energy carriers. In addition to the combined power system, the proposed solution implies using an insulated facade of the building, which will reduce heat loss by 1.5 times, compared with an un-insulated building. to increase the reliability of the energy supply, the project provides for a wind power plant, a backup diesel generator station and a battery pack with an inverter. Estimated calculations have shown that the probability of failure of the power system of this configuration is 3%. The conducted ecological and economic justification of the use of an autonomous combined power system allows us to conclude that 2.1 tons of conventional fuel per year is saved and the payback of the energy supply system for a period of up to 8 years. [ABSTRACT FROM AUTHOR]

The paper describes the possibility of hybrid electricity generation in already existing wind power plants (WPP) by additional installation of photovoltaic power plants (PVPP) on individual wind turbines (WT). Wind turbines have the lowest generation of electricity in the summer months, while PVPPs have the opposite, the highest generation in those months. Connecting the PVPP to the existing WT (hybrid electricity generation) brings a more even generation and a greater degree of use of the infrastructure of the existing wind farms (HV/MV transformer station, medium voltage cable distribution...). This way the variation of generation in relation to the average annual generation is reduced, which reduces the problems of balancing electricity. [ABSTRACT FROM AUTHOR]

The focus of this research is optimizing a wind power plant using a Permanent Magnet Synchronous Generator (PMSG). The backpropagation method of the artificial neural network system was chosen to optimize the output power of the wind power generator. Based on the simulation results, the backpropagation algorithm of the artificial neural network obtains the output power based on the input variable in the form of changing wind speed. The results show that the best value is learning rate = 0.5, error = 0.0001, max. epoch= 100000, neuron hidden layer = 5. The Mean Square Error (MSE) value obtained is 0.1026 reaching the goal at epoch 14845. The reverse training regretion reaches 0.99917. The optimization results are close to the specified error, which is 0.0001, while what is obtained is 0.0145. The power generated by the wind speed is 10.7 m/s before being optimized using the back propagation neural network method worth 321 watts, while the optimized power results are 409 watts. The difference in the average target power obtained is 88 watts compared to the power of the Artificial Neural Network (ANN).

The need for electrical energy continues to increase over time. However, in Indonesia power plants are still dominated by fossil fuel power plants, and there are still many areas without access to electricity. The use of renewable energy is needed to replace fossil fuels considering that fossil fuels can run out one day. The coastal area of Batakan Village in Tanah Laut Regency, South Kalimantan Province, was chosen as the focus location for conducting hybrid power plant simulations because this village is located in a coastal area where wind and solar energy sources are abundant. Batakan Village is approximately 40 km from Pelaihari City. Medium-voltage network transmission system (JTM) is supplied from Pelaihari City, and it is almost certain that this village experiences large power losses over long distance. This power loss will be detrimental if an effort is not made to reduce it. The purpose of this research is first to determine the optimal hybrid power plant configuration design to reduce power loss in the electricity system in Batakan Village. Second, it will analyze the power loss of the hybrid power plant system in Batakan Village, and finally, this research is going to analyze the investment feasibility of the hybrid power plant system in Batakan Village. In this study, the design of renewable energy plants, such as solar power plants (PLTS) with a total capacity of 406.1 kW and wind power plants (PLTB) with a total capacity of 125 kW, and the electricity network (grid system) are used together in a hybrid power generation system. The ETAP software was used to analyze the power losses of the hybrid power generation system, while the HOMER software was used to determine the net present value (NPV) and cost of energy (COE) of the hybrid power generation system. The results show that the configuration of the solar, wind, and grid systems is the most optimal. It is obtained from the results of ETAP simulations that have been carried out during average load and peak load conditions that by including the Solar Power Plant and Wind Power Plant power losses in the electricity system in Batakan Village can be reduced from the previous one using the system configuration only connected to the PLN power grid (grid system only). The total power losses incurred was 269.1 kW of active power and 1613.5 kvar of reactive power at average load reduced to 266.9 kW of active power and 1568.9 kvar of reactive power. At peak load the total power losses were 423.4 kW of active power and 2573.0 kvar of reactive power and they deceased to 41.,5 kW of active power and 2510.5 kvar of reactive power. In terms of investment, the COE value decreased by IDR 111, and the NPC decreased by IDR 6,600,000,000 at the average load. At the peak load COE decreased by IDR 88, while NPC by IDR 7,000,000,000. The return of investment (ROI) value is 13.2%, which indicates that the investment is still in the profitable stage.

This paper deals with improving the feed-in tariff policy for green energy advancement in Ukraine's households based on assessing the economic efficiency of investment project implementation under the current state support mechanisms. This study was conducted for solar and wind power plants with different installed capacities. The Levelized Cost of Electricity and the payback period for such power plants were calculated considering the ongoing feed-in tariffs and discount rates determined by various equity and debt capital ratios. The results showed that the state support provides attractive payback periods for solar and wind power plants with an installed capacity of ≥30 kW. In comparison, 5 kW solar power plants and wind power plants with a capacity of up to 10 kW are not paid off during the power plants' lifecycle. It confirmed that the ongoing energy policy in Ukraine's residential sector is still designed to obtain profits by the owners of generating facilities by selling the excess electricity. In the meantime, its main goal—providing households energy independence—has been levelled. To resolve the issues caused by such a state support model, a methodical approach to improve the feed-in tariff calculation is proposed. In addition, recommendations for reconsidering other policy measures to ensure effective renewable energy development in the residential sector have been made. [ABSTRACT FROM AUTHOR]

Appropriate investments are necessary for the development of the wind energy industry in Ukraine. The main volumes of investments are invested by Ukrainian national companies in the construction of wind power plants. Small wind energy is developing at the expense of small investors and individual enthusiasts. It is also necessary to take into account the low purchasing power of the majority of the population, which requires the most accurate determination of the direction of investment in this industry in order to guarantee the return of funds to the investor. The issue of determining investment directions was considered in a number of works, where the analysis of the main structures of wind turbines was carried out and the power range of turbines, in which the consumer is most interested, was determined, namely from 1 kW to 10 kW. This range is too wide, as it includes installations that differ significantly in their functionality. To solve the problems, as in previous works, the method of paired comparisons was used and two groups of criteria were proposed for analysis. The first group includes criteria in which potential buyers are interested, i.e.: consumer interest in this wind turbine capacity; the possibility of installation without the use of transport and lifting equipment; the possibility of maintenance and minor repairs by the consumer; the possibility of accumulation. The second group of criteria includes criteria of interest to the investor: availability of technical documentation; availability of an experimental or experimental sample; availability of technologies and equipment for serial production. The choice of capacity segments was also determined and substantiated, namely: from 2 to 3 kW; from 3 to 4 kW; 4 to 6 kW and from 6 to 10 kW. Based on the comparative analysis, the 3 kW to 4 kW capacity segment, which is proposed for further investment, received the highest integrated score of 85,813. Bibl. 15, Tabl. 5. [ABSTRACT FROM AUTHOR]

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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.)

In comparison to other alternative energy sources, wind power is more affordable and environmentally friendly, making it one of the most significant energy sources in the world. It is vital to monitor the condition of each wind turbine in the farm and recognize the various states of alert since difficulties with the operation as well as maintenance of wind farms considerably contribute to the rise in their overall expenses. The Supervisory Control and Data Acquisition (SCADA) data-based continuous observation of wind turbine conditions is the most widely used existing strategy to detect the fault early by preventing the wind turbine from reaching a shutdown stage. Several parameters irrelevant to the faults are saved in the SCADA system while the wind turbine is operating. To increase the efficacy of wind turbine fault diagnostics, optimally selected SCADA data parameters are required for fault prediction. Hence, this paper introduces an optimized Convolutional Neural Network (CNN)-based wind turbine fault identification method. For more precise detection, a Self-Improved Slime Mould Algorithm (SI-SMA) is used for the optimal selection of SCADA parameters as well as weight optimization of CNN. The proposed SI-SMA method is an enhanced form of the standard Slime Mould Algorithm (SMA). Eventually, an error analysis and a stability analysis are carried out to check the overall effectiveness of the suggested approach. In particular, the root mean square error (RMSE) of the implemented algorithm is lower, and it is 0.69%, 1.58%, 0.81% and 1.71% better than the existing FF, GWO, WOA and SMA models. [ABSTRACT FROM AUTHOR]