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This paper proposes a fault current limiting scheme (FCLS) for full-scale wind power generators based on logic bang-bang funnel control (LBFC). Different from the convention methods such as frequency droop control and sliding control, which design the control strategy according to the specific fault currents, LBFC is able to restrict various fault current within acceptable range in the shortest time, and it is robust to system nonlinearities and external disturbances. The control signal of the LBFC is bang-bang with the upper and lower limits of control variables. In the model of full-scale wind power generators connecting with the power grid, LBFC is designed to control the switches of inverter bridges when over-current is detected, and a vector controller is applied during the normal operation. Time-domain simulations were conducted with PSCAD, and the performance of LBFC was validated. [ABSTRACT FROM AUTHOR]

Due to high probability of blade faults, bearing faults, sensor faults, and communication faults in pitch systems during the long-term operation of wind turbine components, and the complex operation environment which increases the uncertainty of fault types, this paper proposes a fault diagnosis method for wind turbine components based on an Improved Dung Beetle Optimization (IDBO) algorithm to optimize Support Vector Machine (SVM). Firstly, the Halton sequence is initially employed to populate the population, effectively mitigating the issue of local optima. Secondly, the subtraction averaging optimization strategy is introduced to accelerate the dung beetle algorithm in solving complex problems and improve its global optimization ability. Finally, incorporating smooth development variation helps improve data quality and the accuracy of the model. The experimental results indicate that the IDBO-optimized SVM (IDBO-SVM) achieves a 96.7% fault diagnosis rate for wind turbine components. With the proposed IDBO-SVM method, fault diagnosis of wind turbine components is more accurate and stable, and its practical application is excellent. [ABSTRACT FROM AUTHOR]

Renewable energies have a fundamental role in sustainability, with wind power being one of the most important due to its low production costs. Modern wind turbines are becoming bigger and more complex, and their operation and maintenance must be as optimized as possible. In this context, supervisory control and data acquisition systems provide valuable information, but there is no precise methodology for their analysis. To overcome this need, a generalized methodology is proposed to determine the recognition of critical subsystems through alarm analysis and management. The proposed methodology defines each subsystem in a precise way, shows the indicators for the alarms, and presents a theoretical framework for its application using the quantity and activation times of alarms, along with the real downtime. It also considers the transition of states when the wind turbine is operationally inactive. To highlight the proposal's novelty, the methodology is exemplified with a case study from the Southern Cone, applying the method through a data management and analysis tool. Four critical subsystems were found, with the alarms of wind vanes, anemometers, and emergency speeds being of relevance. The indicators and the graphical tools recommended helped guide the applied analysis. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is difficult to detect effective transient impact characteristics of wind turbine generator bearing fault signals due to non-stationary and strong noise, a fault diagnosis method based on adaptive redundant lifting wavelet dictionary and Bayesian biorthogonal sparse representation (SR) algorithm is proposed. First, a Bayesian model is integrated into the biorthogonal matching pursuit (MP) algorithm to improve the use of dictionary atoms in the effective support set. Then, an adaptive redundant lifting wavelet is used to construct a dictionary matching the transient characteristics of the signal. Finally, the SR algorithm is established by integrating the Bayesian biorthogonal MP model and adaptive redundant lifting wavelet dictionary. Simulation and experimental results show that the proposed method can improve the accuracy of signal reconstruction of transient components and effectively extract bearing fault features, thus verifying the effectiveness and robustness of the method. [ABSTRACT FROM AUTHOR]

This paper proposes a variable-power-tracking-operation-based frequency regulation scheme for a wind turbine generator (WTG) that employs a frequency-excursion-based control parameter to suppress frequency excursion under various wind speeds and disturbances. To this end, an improved system frequency response model is built, and then the frequency regulation characteristics of the WTG are investigated. The frequency-excursion-based control parameter is determined. Simulations based on the Matlab/Simulink simulator verify the effectiveness of the proposed variable-power-tracking-operation-based frequency regulation strategy. The simulation results clearly indicate that the suggested scheme is beneficial for reducing the maximum frequency deviation. The proposed frequency regulation scheme could enhance the networking capacity of wind farms and improve the capacity of the power grid to absorb renewable energy. [ABSTRACT FROM AUTHOR]

This paper presents a case study on condition monitoring of power generators at offshore wind turbines. Two fault detection models are proposed for detecting sudden changes in the sensed value of metallic debris at the generator. The first model uses an exponentially weighted moving average, while the second monitors first-order derivatives using a fixed threshold. This is expected to improve the maintenance activities by avoiding late or early part replacement. The economic impact of the proposed approach is also provided with a realistic depiction of the cost structure associated with the corresponding maintenance plan. While the specifics of the case study are supported by real-life data, considering the prevalence of the use of generators not only in offshore wind turbines but also in other production environments, we believe the case study covered in this paper can be used as a blueprint for similar studies in other applications. • Large scale condition monitoring demonstrates economic benefits. • Case study from real wind turbine population with economic impact assessment. • Sensor for monitoring fault mode results in lead time for maintenance planning. • Sensitivity analysis assesses results despite downtime and power price uncertainty. [ABSTRACT FROM AUTHOR]

This paper proposes a fault current limiting scheme (FCLS) for full-scale wind power generators based on logic bang-bang funnel control (LBFC). Different from the convention methods such as frequency droop control and sliding control, which design the control strategy according to the specific fault currents, LBFC is able to restrict various fault current within acceptable range in the shortest time, and it is robust to system nonlinearities and external disturbances. The control signal of the LBFC is bang-bang with the upper and lower limits of control variables. In the model of full-scale wind power generators connecting with the power grid, LBFC is designed to control the switches of inverter bridges when over-current is detected, and a vector controller is applied during the normal operation. Time-domain simulations were conducted with PSCAD, and the performance of LBFC was validated.

Purpose: Particle dampers are dynamic vibration absorbers that can be attached or inserted into a vibrating structure for broadband vibration attenuation. The particle damping technique is widely used across various industries for vibration attenuation because of its conceptual simplicity, cost-effectiveness, and suitability for harsh environments (Gagnon et al. in J Sound Vib, 2019. https://doi.org/10.1016/j.jsv.2019.114865; Lu et al. in Struct Control Health Monit, 2018. https://doi.org/10.1002/stc.2058). However, designing a particle damper for real-world applications is significantly challenging primarily due to the interaction among the numerous parameters that influence the damping effectiveness of a particle damper. Therefore, this contribution aims to experimentally investigate the particle dampers performance in the context of their designs. Methods: We introduce three different design variants, namely thin-walled cavity (TWC), thin-walled cavity with additional sheets (TWC-AS), and ring cavity (RC). Different strategies are detailed and evaluated in the current paper. Following the comprehensive study of various design variants at the laboratory scale, several tests were conducted on a real-scale wind turbine generator, subjected to real-world loading conditions. Additionally, the effect of particle damper size and its location for the structure on vibration attenuation has been studied. Results: Based on the experimental investigation, all these variants are effective in reducing the vibration amplitude of a structure. Furthermore, it has been found that for practical applications, particularly in the case of large-scale mechanical structures such as wind turbines, it is advisable to combine the most successful variants to design a particle damper. This approach can achieve significant vibration attenuation, and also minimize the additional mass of the granular material compared to a conventional particle damper. Conclusion: The findings from our experimental studies offer valuable insight into the design of particle dampers for large-scale hollow mechanical structures. [ABSTRACT FROM AUTHOR]

This paper suggests day-ahead scheduling of microgrid with and without demand side management considering hydrogen storage and plug-in electric vehicles. This is a highly constrained mixed integer nonlinear programming problem which is solved by using quasi-oppositional fast convergence evolutionary programming (QOFCEP) technique. The concept of the quasi-opposition-based learning is incorporated in fast convergence evolutionary programming (FCEP) to improve the efficiency and quality of the solution. QOFCEP employs quasi-oppositional based learning (QOBL) for population initialization and generation jumping. The studied microgrid comprises three diesel generators, one mini-hydro power plant, two wind turbine generators, two solar PV plants, one hydrogen storage system and plug-in electric vehicles. Simulation outcomes of the suggested QOFCEP technique have been compared with those obtained by FCEP and differential evolution (DE). It is seen from numerical results that the cost obtained with DSM is about 0.81% lower than the cost obtained without DSM. It is also seen that the cost obtained from QOFCEP is about 0.52% and 0.78% lower than the cost obtained from FCEP and DE, respectively. The suggested QOFCEP technique has the ability to bestow superior-quality solution. [ABSTRACT FROM AUTHOR]

Existing shortages on the market of critical and strategic raw materials and problems with the supply chain of selected raw materials, mainly those from China, indicate the need to develop recycling technologies for devices containing the above-mentioned materials. The aim of this work should be to ensure a sustainable supply of raw materials for industry in the EU. One potential source of raw materials may be small-power wind turbine generators equipped with permanent magnets (NdFeB). This research allowed for the development of a methodology for disassembling a generator containing NdFeB magnets in order to determine the shares of individual elements. Due to the significant shares of critical and strategic elements in permanent magnets, a detailed economic analysis was carried out. Based on the research results, economic benefits resulting from the recovery of valuable elements were indicated. The significant market value of critical and strategic raw materials contained in neodymium magnets was demonstrated. The risk of the loss of supplies, the recycling rate and the possibility of replacing the elements in permanent magnets were assessed. [ABSTRACT FROM AUTHOR]

As wind turbine generator systems become more common in the modern power grid, the question of how to adequately protect them from cyber criminals has become a major theme in the development of new control systems. As such, artificial intelligence (AI) and machine learning (ML) algorithms have become major contributors to preventing, detecting, and mitigating cyber-attacks in the power system. In their current state, wind turbine generator systems are woefully unprepared for a coordinated and sophisticated cyber attack. With the implementation of the internet-of-things (IoT) devices in the power control network, cyber risks have increased exponentially. The literature shows the impact analysis and exploring detection techniques for cyber attacks on the wind turbine generator systems; however, almost no work on the mitigation of the adverse effects of cyber attacks on the wind turbine control systems has been reported. To overcome these limitations, this paper proposes implementing an AI-based converter controller, i.e., a multi-agent deep deterministic policy gradient (DDPG) method that can mitigate any adverse effects that communication delays or bad data could have on a grid-connected doubly fed induction generator (DFIG)-based wind turbine generator or wind farm. The performance of the proposed DDPG controller has been compared with that of a variable proportional–integral (VPI) control-based mitigation method. The proposed technique has been simulated and validated utilizing the MATLAB/Simulink software, version R2023A, to demonstrate the effectiveness of the proposed method. Also, the performance of the proposed DDPG method is better than that of the VPI method in mitigating the adverse impacts of cyber attacks on wind generator systems, which is validated by the plots and the root mean square error table found in the results section. [ABSTRACT FROM AUTHOR]

Superconducting rotating machines are more efficient, smaller and lighter than conventional ones. Thus, they can reduce energy consumption and can be an enabling technology in applications that require light-weight machines. Using high temperature superconducting (HTS) materials in machines simplifies cooling designs compared to using low temperature superconductors. This review presents a summary of all major HTS machines built worldwide in the 21st century, covering several different types of machines, e.g., synchronous, induction, dc homopolar, ac homopolar, reluctance, hysteresis and flux modulation machines. A classification of the machines is also described based on the form of superconductor used: wires/tapes, bulks and stacked tapes. The working principles of the more unusual HTS machine types are qualitatively explained, such as machines with claw poles, dc and ac homopolar machines, magnetic gears, vernier permanent magnet machines and flux switching dc machines. Finally, the targeted, practical applications of HTS machines are explored and the significant trends and challenges in HTS machine design in recent years – and in the future – are described.

Renewable energies have a fundamental role in sustainability, with wind power being one of the most important due to its low production costs. Modern wind turbines are becoming bigger and more complex, and their operation and maintenance must be as optimized as possible. In this context, supervisory control and data acquisition systems provide valuable information, but there is no precise methodology for their analysis. To overcome this need, a generalized methodology is proposed to determine the recognition of critical subsystems through alarm analysis and management. The proposed methodology defines each subsystem in a precise way, shows the indicators for the alarms, and presents a theoretical framework for its application using the quantity and activation times of alarms, along with the real downtime. It also considers the transition of states when the wind turbine is operationally inactive. To highlight the proposal’s novelty, the methodology is exemplified with a case study from the Southern Cone, applying the method through a data management and analysis tool. Four critical subsystems were found, with the alarms of wind vanes, anemometers, and emergency speeds being of relevance. The indicators and the graphical tools recommended helped guide the applied analysis.

Implementation of renewable energy sources (RESs) in power systems can reduce the dependence on fossil-fuel-based thermal power generation systems. At the same time, however, the system inertia decreases as synchronous generators decrease; this is crucial for maintaining the stability of the power system. Virtual inertia control (VIC) can regulate the output of an inverter-based resource (IBR) by increasing the inertia. For a wind turbine generator (WTG), output control factors such as pitch angle control and maximum power point tracking (MPPT) significantly affect the performance of the VIC. This paper theoretically clarifies that the pitch angle control contributes to improvements in the performance of the VIC and helps avoid a loss of operation of the WTG in frequency drop events by analyzing the movement of the operational point of the WTG based on the physical characteristic of the WTG and control characteristics of the pitch angle control and MPPT; an electromagnetic transient (EMT) simulation, performed to verify the analysis, is also presented. [ABSTRACT FROM AUTHOR]

This paper examines an inertial response control for wind turbines in order to provide the system inertia decreased by the integration of asynchronous variable renewable energy sources. Specifically, an application of the temporal power surge, a strategy by which the output of a wind turbine can be temporarily increased with releasing the kinetic energy stored in the rotating mass, was proposed to address significant frequency drops in a microgrid. Since the rotational speed of turbine has to be decreased by this approach, it is necessary to further reduce the wind power output to recover the rotational speed after the temporal power surge. This drawback may lead to a second frequency drop, and it is effective to intentionally increase the rotational speed beforehand to mitigate this negative effect. However, this measure causes output curtailment under normal operating conditions. Hence, a determination method of the rotational speed considering the output curtailment was proposed in this paper to facilitate frequency regulation through the temporal power surge. The proposed methods for adjusting rotational speed are evaluated and their effectiveness were verified through numerical simulations. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

As the power generation sector moving towards the sustainability to achieve clean and renewable energy source, the wind power generation plays a vital role due to its abundance in nature. A big chunk of the decrease in carbon emission is a major attribute to the growth of the wind energy sector. Wind turbine production, structural development, logistics, maintenance and R&D are just some of the areas that could benefit from the growth of the wind energy industry. This brought out the attention of researchers of the electrical engineering to focus on wind power generation. It can be more efficient and cost-effective to operate wind turbines as a wind farm rather than individually. This has led to a surge in the construction of wind farms, both onshore and offshore wind farms. Therefore, in this paper, the study and analyse of single Induction generator with wind turbines and 33MW windfarm performance is presented. The simulation result demonstrates the efficiency of DFIG in producing energy at a constant wind speed, as well as its ability to regulate both active and reactive power at steady-state.

AbstractMost of the generations in Bangladesh power system are based on fossil fuels which is 99% of its total generation. Following other countries, Bangladesh is also planning to adopt renewable energy system (RES). It has a plan to incorporate 55 MW wind turbine generator (WT) and 100 MW solar photovoltaic generator (PV) in Western grid of its power system. Though RES is green energy but from stability aspect it needs to be studied as RES has limitations in generating reactive power and maintaining inertia. So, voltage stability and rotor angle stability should be given more attention. However, if any stability problem arises, flexible alternating current transmission system (FACTS) devices can be adopted. With a tuned power oscillation damper, FACTS can reduce the expected rotor angle and voltage stability problem which are associated with RES. This paper examines the stability of the Western grid with the incorporation of hybrid energy of both wind and solar power and shows the positive effect of FACTS devices like thyristor controlled series compensator and static synchronous compensator with respective tuned controller. In present paper, the combination of WT and PV is also examined which shows only incorporation of WT reduces both the steady and dynamic stability more than the only adoption of PV. Inclusion of both WT and PV, reduce the both types of stability more than their individual inclusion. This paper shows that FACTS can improve the stability with individual or both kinds of RES penetration.

The micro-grid (μ-grid) has picked up momentum worldwide with the ability to supply cost-effective, clean, and reliable electrical power to the present-day demand. The practical μ-grids are comprised of non-conventional and conventional sources such as wind turbine generators (WTG) and diesel generators (DG). Due to the encouragement of wind power which is exceedingly sporadic in nature and thus the frequency of the μ-grid is exceedingly vulnerable due to the erratic nature of wind speed. Variations in the load demand have also added to the vulnerability of the μ-grid at distinctive moments of time. Consequently, this paper appears to be a novel plan that utilizes artificial neuro-fuzzy inference system (ANFIS) within the built frequency regulation of the μ-grid. The proposed research has been employed within the μ-grid, and the application outcomes have taken all possibilities, such as load variety at the distinctive moment of time, modification of the load demand on the μ-grid, and step alteration of the wind input. The achieved results are coordinated with a few of the most recent results, which presents the ANFIS ahead over other strategies. Although there is a probable scope for improvement which subsequently involves the fuel cell (FC) with a hydrogen aqua electrolyzer (HAE) unit, as well as a redox flow battery (RFB), that is introduced one at a time in the μ-grid and the results of μ-grid are calculated for various working conditions to show the impact that the ANFIS technology has upon storage devices with regards to the μ-grid architecture. [ABSTRACT FROM AUTHOR]

As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. [ABSTRACT FROM AUTHOR]

This paper presents the optimization of a 10 MW solar/wind/diesel power generation system with a battery energy storage system (BESS) for one feeder of the distribution system in Koh Samui, an island in southern Thailand. The main objectives are to maximize the deployment of renewable energy-based power generation and to minimize the levelized cost of energy (LCOE). A hybrid renewable energy-based power generation system, consisting of solar PV, wind turbine generators, diesel generator (DiG), bi-directional grid-tied charging inverter (CONV) and BESS, was simulated using HOMER Pro®. This study accessed the database of the National Aeronautics and Space Administration (NASA) for the Surface meteorology and Solar Energy (SSE) for the global solar radiation and temperature, along with the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) wind database. The simulations show that Scenario 1 (PV/Wind/DiG/BESS/CONV) and Scenario 3 (PV/DiG/BESS/CONV) are the optimal configurations regarding the economic indicators (i.e. minimum net present costs (NPC) of 438 M$ and LCOE of 0.20 $/kWh) and the environmental indicators (i.e. lowest greenhouse gases (GHG) emission avoidances of 6,339 tonnes/year and highest renewable fraction (RF) of 89.4%). Furthermore, the sensitivity analysis illustrates that Scenario 3 offers the optimal system type with the largest annual energy production (AEP). Besides contributing to the body of knowledge of optimization methodologies for microgrid hybrid power systems, the outcome of this work will assist the regional energy practitioners and policy makers regarding optimal configurations of microgrid hybrid systems in the development of a Green Island concept for Koh Samui.

The shift towards RES introduces challenges related to power system stability due to the characteristics of inverter-based resources (IBRs) and the intermittent nature of renewable resources. This paper addresses these challenges by conducting comprehensive time and frequency simulations on the IEEE two-area benchmark power system with detailed type 4 wind turbine generators (WTGs), including turbines, generators, converters, filters, and controllers. The simulations analyse small-signal and transient stability, considering variations in active and reactive power, short-circuit events, and wind variations. Metrics such as rate of change of frequency (RoCoF), frequency nadir, percentage of frequency variation, and probability density function (PDF) are used to evaluate the system performance. The findings emphasise the importance of including detailed models of RES in stability analyses and demonstrate the impact of RES penetration on power system dynamics. This study contributes to a deeper understanding of RES integration challenges and provides insights for ensuring the reliable and secure operation of power systems in the presence of high levels of RES penetration. [ABSTRACT FROM AUTHOR]

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Some coastal cities are sometimes exposed to floods, mainly caused by strong winds or earthquakes on the seafloor. This causes the water waves heading to the coastal cities to rise quickly, possibly destroying civilization. The proposed study will introduce an intelligent rubber balloon that automatically acts as a water repellent to absorb the momentum of water hammers from the sea. The proposed system has been energized by wind power energy. This enables the control of the bus voltage of the DC link. Sequential balloons could be arranged in such a matter to form a repel flood wall. Wind turbine generators could be used for charging the storage batteries. These batteries energize the smart control system and DC motors coupled with air pumps. These pumps are used to inflate the sequential air balloons. The theoretical models of the proposed system components have been simulated by MATLAB environment. Three DC motors are connected based on the master-salve mechanism, and the third is considered in standby mode. These motors are controlled by a model reference adaptive controller. The tracking speed between reference and measured speeds has been accomplished. Control of switching ON-OFF balloons using fuzzy logic control and classical control has been compared. After using several control scenarios for air pressure in balloons, it is observed that the best response is obtained using fuzzy logic control since it reduces the setting time and faster time response compared to the classical PID controller. Also, it was noticed that time response improved when using a PID controller instead of proportional or PD control scenarios, and the system dynamic response became acceptable. [ABSTRACT FROM AUTHOR]

The wind turbine generator participates in the primary frequency regulation of the power system by releasing kinetic energy from the rotor. It is necessary to ensure that the rotor speed and converter capacity are within the safe range during the frequency regulation process; otherwise, it will have serious negative effects on the frequency stability of the power system. As an important primary frequency regulation parameter, the dead zone affects the evaluation of the frequency regulation ability of WTG. Therefore, the influence of the dead zone should also be further considered. In order to evaluate the frequency regulation capability of wind turbine generators more comprehensively and accurately, this paper proposes an optimized method for the parameter of virtual synchronous control for wind turbine generators by considering the dead zone and physical constraint boundary of primary frequency regulation. After establishing the time domain expression by considering the frequency regulation dead zone, the real-time frequency regulation capacity of the wind turbine generator is quantified by considering the speed limit of the rotor and the capacity limit of the converter. Furthermore, the optimal value of the frequency regulation coefficient can be derived. Simulation results show that the proposed method can effectively reduce the frequency deviation and frequency change rate of the power system, which can also keep the response within the physical constraint boundary. Consequently, the proposed method can fully utilize the ability for frequency regulation of the wind power generation system and effectively improve the frequency stability of the power system. [ABSTRACT FROM AUTHOR]

Without energy storage or reserves, wind turbine generators (WTGs) can provide temporary additional power when participating in frequency regulation (FR) by releasing rotor kinetic energy. Because the FR process is not long, the impact of the changes in the wind speed during FR was not directly considered in most of the previous studies. The field-measured wind speed data were analyzed first, and the results indicate that the wind speed remaining constant during the FR period is a small probability event. Then, a variable-coefficient fuzzy droop control strategy (DC-FLC) is proposed. The DC-FLC modifies the droop control parameter directly according to wind speed variations, which can effectively improve the adaptability of the control strategy to wind speed variations. When exiting FR control, the DC-FLC adopts a smooth exit strategy to solve the problem of smooth switching of maximum power point tracking control and adopts a rotor speed recovery strategy that takes into account the direction of the frequency change, eliminating or delaying the occurrence of the second frequency decrease under unfavorable conditions such as a high wind power penetration rate and continuous wind speed decrease. The comparison of the FR response of the WTG itself proves the superiority of the DC-FLC. The comparison of the FR effects shows that the advantage of using a DC-FLC is significant when the wind speed continues to rise or first decreases and then rises. In situations where the wind speed continues to decrease or rises first and then decreases and the wind power penetration rate is high, the main function of the DC-FLC is to delay the decrease in frequency. The simulation results indicate that under adverse conditions, simply improving the FR response capability of WTGs may not be effective. Moreover, achieving coordination between wind power generation and other FR resources in the system is more important, which is one of the focuses of future research.

Access to reliable electricity is crucial for rural development and improving the quality of life in remote areas. Standalone photovoltaic PV systems and hybrid power systems HPS are promising solutions for rural electrification. However, frequency stabilization is a critical challenge in such systems, and conventional control techniques are inadequate. This work proposes a novel approach to optimize the PID controller gains for the standalone PV-based isolated HPS (IHPS). The student psychology-based optimization algorithm (SPBOA) and quasi-oppositional-based whale optimization algorithm (QOWOA) are employed to enhance the performance of the IHPS models separately. The objective function considered is the integral of time absolute error (ITAE), and the frequency response profile is studied in the presence of the proposed SPBOA and QOWOA-based PID controllers. The results show that the proposed SPBOA outperforms the QOWOA in terms of reducing the ITAE by nearly 5% and minimizing the peak and settling time of the frequency response by 5%-7% in different scenarios. The transient responses of the systems to different input conditions are also analyzed, indicating that both the IHPS-I and IHPS-II models are feasible for remote rural electrification. Overall, the proposed approach offers an efficient solution to optimize the PID controller gains for frequency stabilization in standalone PV and HPS. The results demonstrate the benefits of using the SPBOA and QOWOA algorithms to enhance the performance of the systems, making them suitable for remote rural electrification.

Abstract This paper investigates automatic generation control (AGC) of a realistic hybrid four-control area system with a distinct arrangement of thermal units, gas units and additional power generation. A proportional-integral-double derivative cascaded with proportional-integral (PIDD-PI) controller is employed as secondary controller in each control area for robust restructured AGC considering bilateral transactions and contract violations. The Harris Hawks algorithm is used to determine the optimal controller gains and system parameters under several scenarios. Electric vehicle (EV) aggregators are employed in each area to participate fully along with thermal and gas units to compensate for the unscheduled system demand in the local area. A comparison of non-cascaded controllers such as PI-PD, PD-PID and the proposed PIDD-PI proves the superiority of the last. The effect of the decline in inertia is closely examined because of the sudden outage of a generating unit while at the same time considering the change in area frequency response characteristics and area control error. EV fleets make significant contributions to improving the system dynamics during system inertia loss. The use of EVs in the presence of a wind energy-supported grid can provide a stable efficacy to the power grid. Numerous simulations with higher load demands, stochastic communication delays in presence of the WTG plant, and violations in system loadings and changes in gas turbine time constants in the absence of WTG demonstrate the robustness of the proposed control approach.

The present paper discusses the modeling and analysis of a diesel–wind generating system capable enough to cater to the electrical power requirements of a small consumer group or society. Due to high variations of the load demand or due to changes in the wind speed, the frequency of the diesel–wind system will be highly disturbed, and hence to regulate the frequency and power deviations of the wind turbine system, an effective controller design is a necessary requirement, and therefore this paper proposes a novel controller design based on PID scheme. The parameters of this controller is effectively optimized through a new snake optimizer (SO) in an offline manner to minimize frequency and power deviations of an isolated diesel–wind system. The performance of SO-PID for the diesel–wind system is evaluated by considering the integral of time multiplied absolute error (ITAE), integral absolute error (IAE), and integral of time multiplied square error (ITSE). The results were calculated for a step change in load, step change in wind speed, load change at different instants of time with diverse magnitude, and for random load patterns, and they were compared with some of the recently published results under similar working conditions. In addition, the effect of an ultracapacitor (UC) and redox flow battery (RFB) on SO-PID was investigated for the considered system, and the application results demonstrated the advantages of our proposal over other studied designs. [ABSTRACT FROM AUTHOR]

In this work, a method of optimal relay coordination for improving system reliability has been presented in association with the Wind Energy Conversion System (WECS). The graphical method as well as changes in Plug Setting Multiplier (PSM) and Time Dial Setting (TDS) have been used to test the system’s reliability with the help of ETAP. Load flow analysis, short circuit testing under different fault conditions, reliability assessment, and relay coordination have been performed on the proposed WECS. In this research work, a test system with relay coordination is proposed that is used for transformer protection using over-current relays (OCR) and ground-fault relays (GFR) devices with a wind energy induction generator. It is shown that coordination is off when WECS is added to the system. Therefore, maximum values of the circuit breaker’s trip device setting, the relay’s pickup, and the time dial settings are desirable to increase the coordination. Further, it has been revealed that the comprehensive analysis of load flow analysis, short circuit analysis, and reliability assessment play vital roles in achieving suitable relay coordination. Also, the use of ETAP software in this analysis improves the accuracy and speed of the circuit breaker operation at a reduced cost. [ABSTRACT FROM AUTHOR]

This paper presents the optimization of a 10 MW solar/wind/diesel power generation system with a battery energy storage system (BESS) for one feeder of the distribution system in Koh Samui, an island in southern Thailand. The main objectives are to maximize the deployment of renewable energy-based power generation and to minimize the levelized cost of energy (LCOE). A hybrid renewable energy-based power generation system, consisting of solar PV, wind turbine generators, diesel generator (DiG), bi-directional grid-tied charging inverter (CONV) and BESS, was simulated using HOMER Pro®. This study accessed the database of the National Aeronautics and Space Administration (NASA) for the Surface meteorology and Solar Energy (SSE) for the global solar radiation and temperature, along with the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) wind database. The simulations show that Scenario 1 (PV/Wind/DiG/BESS/CONV) and Scenario 3 (PV/DiG/BESS/CONV) are the optimal configurations regarding the economic indicators (i.e. minimum net present costs (NPC) of 438 M$ and LCOE of 0.20$/kWh) and the environmental indicators (i.e. lowest greenhouse gases (GHG) emission avoidances of 6,339 tonnes/year and highest renewable fraction (RF) of 89.4%). Furthermore, the sensitivity analysis illustrates that Scenario 3 offers the optimal system type with the largest annual energy production (AEP). Besides contributing to the body of knowledge of optimization methodologies for microgrid hybrid power systems, the outcome of this work will assist the regional energy practitioners and policy makers regarding optimal configurations of microgrid hybrid systems in the development of a Green Island concept for Koh Samui. [ABSTRACT FROM AUTHOR]

A copetitive electricity market ensures that there is sufficient energy and that the system functions effectively, despite the fact that system congestion is one of the most significant problems. A method for calculating the ATC for Contingency Management is demonstrated in the current work. ATC assists in locating the most efficient line within the system so that additional power can be transmitted from that line. It is necessary for system operators to be aware of available transfer capability (ATC) in order to ensure that the electricity market is both equitable and transparent. There are a great number of different approaches that can be taken in order to determine the ATC value in the power system and improve it. Therefore, in order to increase the ATC value, it is necessary to find a way to incorporate renewable energy into the system. This is because the world is currently concentrating on green energy technologies. When it comes to integrating wind power in order to increase the ATC value, a significant amount of research has been done on how to use active power support. The reactive power is of utmost significance when there is a significant amount of load. The active and reactive power of wind turbines were taken into consideration for the purpose of the ATC calculation that was presented in this paper. For the purpose of determining the reactive power limit, the capability curve of the wind turbine generator was utilised. For the purpose of determining the amount of power that can be generated by the wind, data on wind speed are collected in real time. The impact that the generation of wind power has on the changes that occur in ATC in both normal and emergency circumstances has been investigated. For the purpose of determining how well the proposed method functions, it is tested on the IEEE-30 bus system.

Implementation of renewable energy sources (RESs) in power systems can reduce the dependence on fossil-fuel-based thermal power generation systems. At the same time, however, the system inertia decreases as synchronous generators decrease; this is crucial for maintaining the stability of the power system. Virtual inertia control (VIC) can regulate the output of an inverter-based resource (IBR) by increasing the inertia. For a wind turbine generator (WTG), output control factors such as pitch angle control and maximum power point tracking (MPPT) significantly affect the performance of the VIC. This paper theoretically clarifies that the pitch angle control contributes to improvements in the performance of the VIC and helps avoid a loss of operation of the WTG in frequency drop events by analyzing the movement of the operational point of the WTG based on the physical characteristic of the WTG and control characteristics of the pitch angle control and MPPT; an electromagnetic transient (EMT) simulation, performed to verify the analysis, is also presented.

Existing shortages on the market of critical and strategic raw materials and problems with the supply chain of selected raw materials, mainly those from China, indicate the need to develop recycling technologies for devices containing the above-mentioned materials. The aim of this work should be to ensure a sustainable supply of raw materials for industry in the EU. One potential source of raw materials may be small-power wind turbine generators equipped with permanent magnets (NdFeB). This research allowed for the development of a methodology for disassembling a generator containing NdFeB magnets in order to determine the shares of individual elements. Due to the significant shares of critical and strategic elements in permanent magnets, a detailed economic analysis was carried out. Based on the research results, economic benefits resulting from the recovery of valuable elements were indicated. The significant market value of critical and strategic raw materials contained in neodymium magnets was demonstrated. The risk of the loss of supplies, the recycling rate and the possibility of replacing the elements in permanent magnets were assessed.

In recent decades, numerous distributed energy resources (DER) have been linked to distribution networks. Among these wind turbine generators (WTG) are popular for their uncertain power fluctuations. Using battery-based energy storage devices (BESS) as a solution to these unwanted fluctuations might be a realistic option. However, the integration of BESS with WTG on a wider scale requires additional attention to the size, position, and charge-discharge schedules. This article discusses these perspectives in addition to the location and power penetration levels of WTGs. In addition, a new charge-discharge control model is created for deciding when batteries should be charged or discharged at each hour. A multi-objective optimization problem is created with the goal of optimizing the economic, environmental, and technological goals of the unbalanced distribution network (UDN). The optimization task is solved using a Search Group Algorithm (SGA). The planning model leverages the average demand of the feeder at a particular hour of the day as the decision criteria for charging or discharging the battery. The charging of the BESS devices is totally done by the WTG power output. Furthermore, the conservative and free-running discharge approaches of the battery are studied. The proposed approach is tested using IEEE 37 bus UDN and the results demonstrate improvement in distribution system performance by coordinating BESS dispatches appropriately. The active and reactive power loss reduction for the three-phase system were 30.4% and 30.8% for the free-run mode, respectively, while the same for the conservative mode was 40.3% and 37.4%. [ABSTRACT FROM AUTHOR]

Most of the generations in Bangladesh power system are based on fossil fuels which is 99% of its total generation. Following other countries, Bangladesh is also planning to adopt renewable energy system (RES). It has a plan to incorporate 55 MW wind turbine generator (WT) and 100 MW solar photovoltaic generator (PV) in Western grid of its power system. Though RES is green energy but from stability aspect it needs to be studied as RES has limitations in generating reactive power and maintaining inertia. So, voltage stability and rotor angle stability should be given more attention. However, if any stability problem arises, flexible alternating current transmission system (FACTS) devices can be adopted. With a tuned power oscillation damper, FACTS can reduce the expected rotor angle and voltage stability problem which are associated with RES. This paper examines the stability of the Western grid with the incorporation of hybrid energy of both wind and solar power and shows the positive effect of FACTS devices like thyristor controlled series compensator and static synchronous compensator with respective tuned controller. In present paper, the combination of WT and PV is also examined which shows only incorporation of WT reduces both the steady and dynamic stability more than the only adoption of PV. Inclusion of both WT and PV, reduce the both types of stability more than their individual inclusion. This paper shows that FACTS can improve the stability with individual or both kinds of RES penetration. [ABSTRACT FROM AUTHOR]

Wind Turbine Generators (WTG) are being integrated into distribution systems on a large scale worldwide as part of a global effort to capture green energy. Wind turbine generator intermittency may be mitigated by Battery Energy Storage Systems (BESS), which have emerged as a viable option in recent years. To find the best position and capacity for wind power generation and BESS charging/discharging dispatches, a Red Fox Optimisation (RFO) algorithm is used while optimising the imbalanced distribution network's performance under technological restrictions. The charging or discharging criteria for this method is the average feeder load. The charging techniques for BESS using WTG and Sustainable Average Load (SAL) are evaluated in terms of the free-running mode of dispatch cycle. The suggested approach is tested on an IEEE-37 bus Unbalanced Radial Distribution Network (UDN). It has been shown that the suggested method enhances several performance objectives of the distribution system. [ABSTRACT FROM AUTHOR]

This paper investigates automatic generation control (AGC) of a realistic hybrid four-control area system with a distinct arrangement of thermal units, gas units and additional power generation. A proportional-integral-double derivative cascaded with proportional-integral (PIDD-PI) controller is employed as secondary controller in each control area for robust restructured AGC considering bilateral transactions and contract violations. The Harris Hawks algorithm is used to determine the optimal controller gains and system parameters under several scenarios. Electric vehicle (EV) aggregators are employed in each area to participate fully along with thermal and gas units to compensate for the unscheduled system demand in the local area. A comparison of non-cascaded controllers such as PI-PD, PD-PID and the proposed PIDD-PI proves the superiority of the last. The effect of the decline in inertia is closely examined because of the sudden outage of a generating unit while at the same time considering the change in area frequency response characteristics and area control error. EV fleets make significant contributions to improving the system dynamics during system inertia loss. The use of EVs in the presence of a wind energy-supported grid can provide a stable efficacy to the power grid. Numerous simulations with higher load demands, stochastic communication delays in presence of the WTG plant, and violations in system loadings and changes in gas turbine time constants in the absence of WTG demonstrate the robustness of the proposed control approach. [ABSTRACT FROM AUTHOR]

Renewable energy technologies (RETs) have been universally accepted as the prospective choice to increase the reliability of the power system and reduce the effects of emission cost (EC), fuel cost (FC), maintenance cost (MC), power loss (PL), total annual cost (TAC) and voltage deviation (VD). The performance indicators are used in the study to assess the effects of diesel generator (DG), electric storage system (ESS), photovoltaic (PV) and wind turbine generator (WTG) on the environmental, economic, and technical performance of a microgrid system with modified Roy Billiton Test System (RBTS) bus 4 distribution network. The proposed model is utilized to achieve the goals of the study by minimizing the costs that are identified with the power outages, TAC, MC, EC, FC, PL, and VD of the system with the application of an intelligent optimal control method based on the fmincon solver. The outcomes of the study can be used as benchmarks to assess the cost-effectiveness of increasing the capacity of universal power supply and resolve the universal power crisis owing to the depletion of fossil fuels. The study provides vital information to enhance the efficiency of the power system and the guidelines to promote the development of sustainable energy. [ABSTRACT FROM AUTHOR]

We present key design parameters of an innovative 10 MW low-speed direct-drive superconducting generator by high-temperature superconductor coated conductors for the rotor windings. In the simulations, the generator has an iron rotor with the superconducting coils operating at 20 K while the rotor core and the cooper stator are at room temperature. The calculations have been performed by Finite Element Software Comsol Multiphysics. Electromagnetic design parameters, magnetic flux distributions, phase current, voltage, and loss distributions of the superconducting generator are introduced. In addition, the AC losses that arise during the current increase in the superconducting rotor were calculated separately using both the H- and AV-formulation forms of Maxwell's equations employing the non-linear current–voltage relation of the superconductor. The current distribution and magnetic field distribution of the superconductor coils, volumetric loss density distribution, and comparison of the losses of each coil layer have been analyzed and discussed in detail. [ABSTRACT FROM AUTHOR]

As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid.