Wind System Research Articles

Deep learning‐based barrier‐function super‐twisting sliding mode control for integrating renewables in smart grid

AbstractThis study presents a two‐step controller design for integrating wind and photovoltaic energy systems into the smart grid. In the first stage, an enhanced deep neural network (DNN), optimised by particle swarm optimisation and a genetic algorithm, is employed to generate maximum power point (MPP) targets for both wind and solar systems. The DNN incorporates advanced features like hyperparameter tuning, softmax attention, dropout, and early stopping to improve prediction accuracy and prevent overfitting. In the second stage, a barrier‐function‐based adaptive super‐twisting sliding mode controller is developed to track the MPP and maintain stable DC bus voltage. This controller effectively reduces chattering and operates without requiring detailed knowledge of disturbance limits. The proposed design aims to maximise power extraction, ensure DC bus voltage stability, and enable smooth power delivery to the grid. MATLAB simulations and real‐time hardware testing validate the controller's performance, demonstrating significant improvements over traditional methods.

Research on Voltage Stability Strategy of Energy Storage Access to High Penetration Wind and Solar Power Distribution Network System with SOP (Soft Open Point)

Research on Voltage Stability Strategy of Energy Storage Access to High Penetration Wind and Solar Power Distribution Network System with SOP (Soft Open Point)

ENERGY MANAGEMENT IN HYBRID PV-WIND-BATTERY STORAGE-BASED MICROGRID USING MONTE CARLO OPTIMIZATION TECHNIQUE

The paper presents an efficient energy management system designed for a small-scale hybrid microgrid incorporating wind, solar, and battery-based energy generation systems using three types of Monte Carlo simulation techniques. The heart of the proposed system is the energy management system, which is responsible for maintaining power balance within the microgrid. The EMS continuously monitors variations in renewable energy generation and load demand and adjusts the operation of the energy conversion systems and battery storage to ensure optimal performance and reliability. The primary objective of the energy management system is to maintain power balance within the microgrid, even in the face of fluctuations in renewable energy generation and load demand. This involves dynamically adjusting the operation of the renewable energy sources and battery storage system to match the instantaneous power requirements of the microgrid. Overall, the paper presents a comprehensive approach to designing and implementing the Monte Carlo technique to extract maximum energy profit using the hybrid microgrid. By integrating renewable energy sources with energy storage and advanced control algorithms, the proposed system aims to enhance the reliability, stability, and sustainability of the microgrid's power supply.

Optimal reconfiguration of a distribution network integrated photovoltaic and wind systems using blood-sucking leech optimizer

This paper presents a planning strategy for integrating renewable distributed generation (DG) units into a distribution network, incorporating network reconfiguration to enhance the network's technical, economic, and environmental performance. Utilizing a novel meta-heuristic algorithm, the Blood-Sucking Leech Optimizer (BSLO), the study addresses a multi-objective optimization problem aimed at determining the optimal placement and sizing of DG units, as well as the most effective network topology. This approach seeks to minimize active power losses, improve voltage profiles, reduce installation costs, and lower greenhouse gas emissions. The model accounts for variable load demands, climatic factors (such as ambient temperature, solar irradiation, and wind speed), and fluctuating energy prices, reflecting realistic operating conditions. Tested on the IEEE 69-bus distribution network, the BSLO algorithm demonstrated rapid convergence to the global optimum by effectively balancing exploration and exploitation phases. Compared to other meta-heuristic methods, such as the Grey Wolf Optimizer, Gorilla Troops Optimizer, Walrus Optimization Algorithm, and Artificial Hummingbird Algorithm, the BSLO consistently achieved superior accuracy and faster convergence, resulting in higher precision and optimization efficiency. The optimal deployment of two PV generators and two wind turbines, combined with selective line switch openings, resulted in an 87.66% reduction in active power losses, a 73.30% decrease in voltage deviation, a 51.91% reduction in overall system costs, and a 62.74% decrease in greenhouse gas emissions compared to the base case.

Investigating the feasibility of nano-grid infrastructure integration into street lighting systems based on energy production and economic evaluation

To enhance efficient and sustainable energy usage in street lighting systems, a nano-grid infrastructure comprising an energy harvesting, storage, and management system is integrated. This paper investigated the feasibility in terms of energy production and economic evaluation of using various energy harvesting for photovoltaic, piezoelectric, and wind energy in a nano-grid street lighting system. The photovoltaic system was evaluated based on the factors of annual actual solar radiation, power losses, and system performance using the PVsyst software. The piezoelectric energy production was studied and designed. Optimal piezoelectric installation for maximum power generation was analyzed in terms of deformation and stress using ANSYS software. For wind power generation, the wind turbine characteristics, along with its location, were designed to optimize power output using computational fluid dynamic simulations in ANSYS software. After that, economic evaluation for the proposed energy harvesting systems for nano-grid street lighting system are analyzed and compared in terms of DPP, NPV, IRR, and LCOE. In addition, the optimization of using PV, a wind system, a hybrid PV—wind system for nano-grid street lighting systems was conducted using HOMER Pro software. The results indicated that generating power through PV, piezoelectric, and wind energy was feasible. However, economic evaluation unveiled the infeasibility of employing piezoelectric and wind energy systems due to their elevated investment costs relative to their power generation capabilities. The dynamics of power generation from PV and wind systems, along with street lighting consumption, significantly impacted the dimensions of energy harvesting and storage systems, as well as their economic feasibility. The hybrid PV-wind system exhibited strong economic feasibility.

Fault diagnosis of cells in PEM electrolyzer stack under fluctuating power source

The scale of hydrogen production using renewable energy is expanding with the global energy transition accelerating. Safety in hydrogen production is gaining increased attention. Compared to stable power supplies, the voltage of the electrolyzer stack fluctuates dynamically with input power in the wind and photovoltaic systems. For this reason, a fault diagnosis method for electrolyzers under fluctuating power sources is proposed. Firstly, the faults of the sensor and electrolyzer are distinguished by interleaved voltage detection to avoid the misdiagnosis caused by the sensor failure. Secondly, an improved variable mode decomposition method is introduced to process the raw voltage signals to weaken the influence of inter-cell inconsistency on fault diagnosis. Furthermore, the fault characteristics are highlighted with a shortened fault identification time. Then, the fault characteristics are extracted by the degree of cell voltage fluctuation with the occurrence of faults is judged by the difference in the degree of fluctuation between neighboring electrolyzers. Finally, faults such as short circuits and water shortages in the electrolyzer are diagnosed using the correlation differences in cell voltage between different faults. The feasibility of this fault diagnosis method is validated through case studies and comparative analyses.

The Impacts of Far‐Field Typhoon‐Generated Coastal Trapped Waves on the Hydrodynamics in the Northern South China Sea: A Case Study of Typhoon In‐Fa

AbstractCoastal Trapped Waves (CTWs) have the potential to transmit significant energy from atmospheric wind systems, causing dramatic coastal changes over vast areas, even far from the wind systems. This study investigated the impacts of CTWs generated by Typhoon In‐fa (2021) on the northern South China Sea (NSCS) hydrodynamics using tide gauge observations, reanalysis data, and numerical model outputs. The analysis results indicate that the CTWs induced by Typhoon In‐fa exhibit distinct characteristics in different phases of wave crest and trough. During the crest phase, coastal currents generated by CTWs flow opposite to the background circulation, while during the trough phase, they flow in the same direction. This process is accompanied by changes in cross‐shore currents, such that during the crest phase of CTWs, the cross‐shore currents are landward at the surface and seaward at the bottom, while during the trough phase of CTWs, the cross‐shore currents become reversed. These changes further lead to downwelling in temperature, salinity, and density during the crest phase of CTWs, and upwelling during the trough phase of CTWs. Results from a linear CTW model demonstrated that the above characteristics agreed with the traditional CTW theory. Sensitivity experiments with the Regional Ocean Model System (ROMS) explored key factors influencing NSCS hydrodynamics, including local winds and CTWs from Typhoon In‐fa. The local winds and CTWs have different effects: they compete during the crest phase and co‐work during the trough phase, with local winds dominating the sea surface and CTWs dominating the seabed.

DC microgrid for EV charging station with EV control by using STSM controllers

Abstract This study explores innovative control strategies for electric vehicle (EV) charging stations in a DC Microgrid powered by solar and wind energy. A new methodology regulates the dc-link voltage through various converters while a modified vector control method enhances the performance of switched reluctance motors (SRMs). The implementation of super twisting sliding mode (STSM) controllers show superior performance compared to traditional PI and Fuzzy controllers. The design of an asymmetrical converter with four battery banks also minimizes charging durations. The real-time test system (RTS) effectively managed power generation within a DC microgrid, demonstrating a stable voltage at the DC bus despite variations in total generation from photovoltaic (PVS) and wind systems. In Case 1, the controller successfully maintained power balance while charging electric vehicles and managing DC loads. During load torque adjustments, the system maintained a steady motor speed of 320 RPM even with a load torque increase from 5 Nm to 50 Nm at 3 s, showcasing its robust vector control strategy. Notably, the system facilitated a reverse operation at 10 km h−1 (80 RPM) by seamlessly adjusting the engine’s reference speed from 80 RPM to −80 RPM at t = 4.0 s. The vector control causes the engine speed heading to be opposite in a natural manner., indicating its innovative capability to handle diverse operational scenarios. The MATLAB/Simulink package serves as the foundation for the proposed model, which is then integrated into OPAL-RT modules to create a Hardware-in-the-Loop (HIL) system for showcasing diverse outcomes. Different outcomes are deliberated with validated justifications of the suggested approach. The research is linked to Sustainable Development Goals 7 (Affordable and clean energy) and 13 (Climate action).

Technical and economic simulation of a hybrid renewable energy power system design for industrial application

Countries in Africa rank the highest in low energy accessibility and air pollution globally. Presenting the urgent need to explore renewable energy sources to tackle the power challenge and reduce the carbon footprint for a greener atmosphere. A novel hybrid wind and solar renewable energy power system (HREPS) coupled to a battery that is capable of powering industrial appliances in the Basse district of The Gambia has been proposed. The HREPS size was estimated automatically with the PVsyst software taking into account the PV power and battery capacity based on the load profile and loss of load probability, with all the necessary meteorological, technical, and economic factors. The optimal size was possible with 20 photovoltaic modules (250 W) and 1 Wind generator (1 KW) compatible with the annual load requirement of about 2555 MWh. These results suggested that the HREPS is reliable for the user’s load demand in all the tested meteorological conditions of the study area. When the HREPS is linked to any other renewable source, it shows the potential of gaining about 8395 kWh annually in the battery. The continuous operation of the hybrid system for 21 years presents a net gain of > 400% for the standalone systems with a projected gain of > 600% when linked to a small smart grid system. Since high taxes may scuttle these gains, it is recommended that the Government encourage investment in renewable energy power systems by subsidizing the taxes on the purchase of items to make them more affordable.

Investigation of flow and heat transfer characteristics in a coupled cooling system of thermoelectric refrigeration and ion wind

This paper focuses on the flow and heat transfer characteristics of a cooling system that combines thermoelectric cooling technology with ion wind technology. Through experimental exploration and data analysis, the factors affecting the performance of the sawtooth-plate ion wind were first investigated using the orthogonal experimental method. Particle Image Velocimetry (PIV) was employed to visualize the internal flow field and investigate the impact of voltage and plate spacing on the performance of the ion wind generator with a mesh and a parallel plate receiving electrode. Lastly, the heat transfer characteristics of the standalone thermoelectric cooling system and the coupled system were compared. The study found that voltage has the greatest impact on the performance of the ion wind, followed by the spacing of the parallel plate electrodes. Compared to the standalone thermoelectric cooling system, the temperature drop of the heat source in the coupled system increased by 6.7%, and the COP increased by 7.9%, proving that the coupled system has significantly improved heat transfer performance.

Assessing the potential of large-scale geological hydrogen storage in North Dakota's Bakken Formation: A case study integrating wind-powered hydrogen production

The research seeks to assess the feasibility of utilizing depleted oil and gas reservoirs for large-scale hydrogen storage through wind energy in the Middle Bakken, North Dakota, USA. Despite the region's vast oil and gas reserves and development activities, wind energy for hydrogen production and storage remains largely untapped. The study discovered significant hydrogen storage capacities in Well A, Well B, and Well C, using a real gas behavior mathematical model. This presents a large-scale, co-located renewable energy storage solution serving as a model for the sustainable energy transition. The results show hydrogen storage potentials of 250.27, 401.48, and 163.296 ktons, respectively, with 50 % cushion gas. The cumulative hydrogen production and energy content from hydrogen over the study period were for Well B is 367,278 kg and 12,430 MWh, enabling hydrogen storage for up to 1088 days. A sensitivity analysis reveals that a lower cushion gas percentage is preferable for hydrogen storage efficiency. This approach is valuable for stakeholders, including government bodies, geological services, renewable energy facilities, and the chemical/petrochemical industry, as it provides opportunities in developing a co-located wind and hydrogen system to tackle the intermittent nature of wind energy and offers a sustainable repurposing of depleted oil and gas infrastructure, enhancing energy security and reducing greenhouse gas emissions while supporting sustainable energy transitions.

Dynamic response and power performance of a combined semi-submersible floating wind turbine and point absorber wave energy converter array

With the global demand for renewable energy rising, offshore renewable energy development has gained more attention. The combination of wind and wave energy is a new trend. Ensuring stability in combined systems is crucial for efficiency of absorbing energy. A novel combined wind and wave energy system with a semi-submersible floating wind turbine (FWT) and an array of six torus-shaped point absorber wave energy converters (WECs) is proposed. The dynamic response of combined system is investigated using 3D potential flow theory by comparing to the original system. The effects of power take-off (PTO) damping, WEC float shape and seasonal variation on the dynamic response and power performance of combined system are studied. The results show that the addition of WEC array improves the stability and power production of combined system. Meanwhile, the total power of combined system is approximately 2.5%–6.5 % higher than that of original system. PTO damping mainly affects the heave motion of combined system. As PTO damping increases, the first peak of mean power of WEC array shifts towards the long period, while the second peak of that shifts towards the short period. The conical-bottom WEC generates the most power compared to the flat-bottom WEC, hemispherical-bottom WEC and concave-bottom WEC. The combined system generates the most power in winter, and the total annual electricity output can be up to 2.99 × 104 MWh.

Optimal capacity configuration of joint system considering uncertainty of wind and photovoltaic power and demand response

AbstractTo reduce phenomenon of abandoning wind and photovoltaic power, improve the limitations of traditional methods in dealing with uncertainty of wind and photovoltaic power and system planning, and improve the optimal configuration of resources, an optimal capacity configuration of joint system considering uncertainty of wind and photovoltaic power and demand response is proposed. Firstly, using probability distribution information of wind and photovoltaic power output, the distance between actual probability distribution and forecast probability distribution is constrained based on the 1‐norm and ∞‐norm. A fuzzy set considering uncertainty probability distribution is constructed, and a two‐stage distributed robust planning model is established. The first stage involves optimizing joint system capacity for scenarios with the lowest probability of wind and photovoltaic power; the second stage builds on capacity optimization scheme from the first stage and aims to minimize operating costs through simulation optimization. Secondly, column and constraint generation is used to solve the model. Finally, constructing an example based on actual data from a power grid in Northeast China for simulation and analysis, the results show that the method achieves a balanced optimization of robustness and economy, effectively reduces carbon emissions and improves ability of the system to consume wind and photovoltaic power.

Cyber attacks detection and mitigation in hybrid power system using type-2 fuzzy controller

Abstract This paper presents a novel control technique using Fuzzy Type-2 controller for regulating the frequency deviations in an independent Hybrid Power System (HPS). The HPS comprises of a wind system and a solar photovoltaic (PV) system as primary energy sources, along with Fuel Cells (FCs) as additional generation systems and Double Layer Capacitor (DLC) Banks as storage devices to meet the load demand. The frequency variations occur in the HPS due to the intermittency in power outputs from the primary sources, the load changes as well as any attacks in the system. The frequency regulation is achieved by effective coordination control of FC and DLC with the aid of a Fuzzy Type-2 controller and a high pass filter (HPF). The DLC technology adequately satisfies the residual power of hybrid systems resulting from the slow dynamics of FCs. The Fuzzy Type-2 controller is trained using an input-output data set of a PID controller whose gains are tuned to their optimal values using Monte-Carlo state estimators. The proposed system is simulated using real weather data to validate the capability of the Hybrid Power System (HPS) in supplying isolated loads while maintaining power frequency balance conditions. Also the HPS is subjected to attacks in daily load variation and the results are compared with the system without attacks. The simulation results show that the peak over shoots are reduced considerably but the settling time is 0.2 s in the system with no attacks where as the settling time is prolonged to 1.2 s with the attacks. This paper demonstrates the effectiveness of the Fuzzy Type-2 controller for the coordination control of DLC and FC to achieve generation-load balance condition in comparison with that of the PID controller for HPS system with and without attacks.

Coastal lake sediments from Arctic Svalbard suggest colder summers are stormier

The Arctic is rapidly losing its sea ice cover while the region warms faster than anywhere else on Earth. As larger areas become ice-free for longer, winds strengthen and interact more with open waters. Ensuing higher waves also increase coastal erosion and flooding, threatening communities and releasing permafrost carbon. However, the future trajectory of these changes remains poorly understood as instrumental observations and geological archives remain rare and short. Here, we address this critical knowledge gap by presenting a continuous Holocene-length reconstruction of Arctic eolian activity using coastal lake sediments from Svalbard. Exposed to both polar Easterlies and Westerly storm tracks, sheltered by a bedrock barrier, and subjected to little post-glacial uplift, our study site provides a stable baseline to assess Holocene changes in the dominant wind systems of the Barents Sea region. To do so with high precision, we rely on multiple independent lines of proxy evidence for wind-blown sediment input. Our reconstructions reveal quasi-cyclic summer wind maxima during regional cold periods, and challenge the view that a warmer and less icy future Arctic will be stormier.

A Comprehensive Review of Remaining Useful Life Estimation Approaches for Rotating Machinery

This review paper comprehensively analyzes the prognosis of rotating machines (RMs), focusing on mechanical-flaw and remaining-useful-life (RUL) estimation in industrial and renewable energy applications. It introduces common mechanical faults in rotating machinery, their causes, and their potential impacts on RM performance and longevity, particularly in wind, wave, and tidal energy systems, where reliability is crucial. The study outlines the primary procedures for RUL estimation, including data acquisition, health indicator (HI) construction, failure threshold (FT) determination, RUL estimation approaches, and evaluation metrics, through a detailed review of published work from the past six years. A detailed investigation of HI design using mechanical-signal-based, model-based, and artificial intelligence (AI)-based techniques is presented, emphasizing their relevance to condition monitoring and fault detection in offshore and hybrid renewable energy systems. The paper thoroughly explores the use of physics-based, data-driven, and hybrid models for prognosis. Additionally, the review delves into the application of advanced methods such as transfer learning and physics-informed neural networks for RUL estimation. The advantages and disadvantages of each method are discussed in detail, providing a foundation for optimizing condition-monitoring strategies. Finally, the paper identifies open challenges in prognostics of RMs and concludes with critical suggestions for future research to enhance the reliability of these technologies.

Structural Decomposition of the Passivity-Based Control System of Wind–Solar Power Generating and Hybrid Battery-Supercapacitor Energy Storage Complex

Wind–solar power generating and hybrid battery-supercapacitor energy storage complex is used for autonomous power supply of consumers in remote areas. This work uses passivity-based control (PBC) for this complex in accordance with the accepted energy management strategy (EMS). Structural and parametric synthesis of the overall PBC system was carried out, which was accompanied by a significant amount of research. In order to simplify this synthesis, a structural decomposition of the overall dynamic system of the object presented in the form of a port-Hamiltonian system, which was described by a system of differential equations of the seventh order, into three subsystems was applied. These subsystems are a wind turbine, a PV plant, and a hybrid battery-supercapacitor system. For each of the subsystems, it is quite simple to synthesize the control influence formers according to the interconnections and damping assignment (IDA) method of PBC, which locally performs the tasks set by the EMS. The results obtained by computer simulation of the overall and decomposed systems demonstrate the effectiveness of this approach in simplifying synthesis and debugging procedures of complex multi-physical systems.

Digital twin for advanced optimal coordination scheme of distance and Dual-Stage overcurrent relays

Integrating Distributed Generators (DGs), particularly renewable energy sources such as wind systems, into traditional power network presents significant protection coordination challenges. This study introduces a new optimal coordination scheme for distance and double-Stage Overcurrent (OCR) characteristics relays, utilizing digital twin technology. The proposed dual-stage of OCR protection to enhance the efficacy of the coordination between distance relays and OCRs. By employing advanced digital twin models and Hardware-in-the-Loop (HIL) testing, the proposed scheme aims to enhance fault management and relay coordination for microgrids. The scheme’s effectiveness is evaluated using a reference power network (CIGRE radial and mesh network) with and without wind systems under various fault types and locations. The study demonstrates substantial improvements over traditional and modern dynamic distance relays coordination approaches, including a reduction in maximum tripping time from 0.85 s to 0.19 s with the dual-stage scheme. Comparative analysis of digital simulation and physical twin relays further validates the accuracy and robustness of the proposed scheme.

Fluvial-aeolian interactions in a partly confined reach of the Yarlung Tsangpo River, Tibet

Fluvial-aeolian interactions (FAI) exert a primary influence on landscape morphodynamics in arid regions. Such process interactions are well studied for large-scale open systems such as dryland deserts and plains, but little is known about FAI in partly confined valley settings. Here we show how aeolian sand availability and transport pathways and connectivity relationships influence morphodynamic interactions with fluvial processes in a braided reach of the Yarlung Tsangpo River in Southern Tibet, China. Analyses of remote sensing imagery, field data, and the hydrology record show how dune fields and wind systems influence the magnitude and frequency of channel change. While the dunes along the trunk stream have limited impact on river morphodynamics, mid-channel dune fields significantly decrease the frequency of channel adjustment. Combined impacts of valley winds and mountain-valley winds create aeolian sand ramps that stimulate sediment recirculation within this landscape setting.

Hybrid Testing System Development for Single Point Mooring Lines FOWT’s

Abstract To advance the development of various concepts for floating offshore wind turbines, it is imperative to have access to experimental data. These data are used in the validation of the tools for the simulation of floating turbines and also for the tuning of the models. CENER has developed a hybrid testing methodology that enhances the performance of wave basin tests for scaled models of Floating Offshore Wind Turbines (FOWTs). This approach allows us to apply forces and moments from the wind turbine to the floating platform without needing to replicate wind within the testing facility or create a complex model of the wind turbine rotor. However, when it comes to testing single point moored (SPM) platforms, a unique challenge arises. These platforms have an additional degree of freedom as they can freely rotate around the vertical axis of their mooring attachment (yaw degree of freedom). These type of platforms can present important misalignments with respect to the wind depending on the combination of wind, wave and current directions. Consequently, accurately capturing the impact of misalignment on platform dynamics, especially in yaw, is essential to assess the platform’s ability to self-align with the wind direction, a key factor known as weathervaning capacity. The X1Wind platform is an innovative floating wind system, based on a single point mooring solution with a downwind wind turbine configuration that allows it to be passively self-orientated. The concept has been extensively tested on prototypes at real sea conditions as well as on scaled models at wave basins. For the last wave basin testing campaign, X1Wind has entrusted CENER with the development of the hybrid testing methodology adapted to the requirements of SPM platforms. The testing campaign has covered different wave and wind conditions, including misalignment scenarios and has shown a good dynamic behavior of the platform on yaw. This study outlines the advancements made in the CENER Software-in-the-Loop (SiL) hybrid testing system for wave basin tests of SPM platforms. In order to correctly introduce the direction of the aerodynamic forces on the wind turbine under misaligned conditions, improvements on the software and hardware (loads actuator) of the SiL system were developed and tested. An actuator system consisting of 6 propellers was used. The numerical model that calculates the rotor aerodynamic loading were expanded to take into consideration the direction of the aerodynamic loads with respect to the platform. Additionally, the drag of the wind over the tower and other platform elements must be considered, as they can play a relevant role in the generation of the weathervaning moment. The study concludes that the use of the upgraded SiL hybrid testing system is an effective and afordable solution for the testing of scaled SPM platforms at wave basin facilities. It also summarizes the different considerations that the system has to overcome for the particularity of this type of testing application.