Wind Power Applications Research Articles

Global warming potential and energy dynamics of conservation tillage practices for different rabi crops in the Indo-Gangetic Plains

A field experiment was conducted during 2007–2019 under various rabi (winter) crops (viz., wheat, maize, barley and mustard) on a Vertisol in sub-tropical Indo-Gangetic Plains (IGP) with different tillage systems to assess energy indices, greenhouse gas (GHG) emission and carbon sustainability index in assured irrigated fields. The tillage systems were: no tillage sown by a zero till drill (NT), no tillage with retention of previous crop residues at 6 t ha−1 and sowing by a happy turbo seeder (HT), and conventional tillage (CT) where sowing was performed by a multi-crop zero till drill after twice harrowing + twice tilling + once rotavator operations. Significantly higher input energy was observed in wheat followed by maize, barley and mustard. Among tillage systems, CT plots consumed higher input energy that was about 20, 21 to 22, 25 to 26 and 20–22% higher than HT and NT in wheat, maize, barley and mustard, respectively. However, output energy and energy use efficiency were highest in HT. The total GHG emission (kg CO2 equivalent ha−1) was highest in wheat (2,351) followed by maize (2,274), barley (1,859) and mustard (1,652). Among tillage systems, CT produced about 31–34%, 33–34%, 37–40% and 28–30% higher GHG emission than HT and NT under wheat, maize, barley and mustard, respectively. The CT plots had lower carbon sustainability index and carbon efficiency than ZT and HT in all crops. In short, HT recorded significantly higher energy use efficiency and lower global warming potential (GWP) than CT in all crops. Thus, HT could be a promising agro-technique for production of rabi crops in the IGP. Among rabi crops, barley production was energy efficient and had less GWP. In rabi crop production, the highest energy sources was mineral fertilizer use (25–49%) and second highest source was irrigation water (14–44%). These can be substituted with use of the organic sources of fertilizers and application of solar and wind power in irrigation, respectively.

Sensorless adaptive control of brushless doubly-fed reluctance generators for wind power applications

A novel model reference adaptive system for the rotor position/speed estimation and sensorless operation of a brushless doubly fed reluctance generator with maximum power point tracking is presented. Its main advantage over the existing designs are the inherent robustness and stability afforded by the complete parameter independence of the reference model using only the measured currents of the converter-fed (secondary) winding. In addition, the respective stationary frame current components are estimated by the adaptive model using the voltage and current measurements of the grid-connected (primary) winding at line frequency, offering higher accuracy. The simulation and experimental results have demonstrated the excellent real and reactive power controller performance for typical operating characteristics of wind turbines.

Design of a Medium Voltage Generator with DC-Cascade for High Power Wind Energy Conversion Systems

This paper shows a new concept to generate medium voltage (MV) in wind power application to avoid an additional transformer. Therefore, the generator must be redesigned with additional constraints and a new topology for the power rectifier system by using multiple low voltage (LV) power rectifiers connected in series and parallel to increase the DC output voltage. The combination of parallel and series connection of rectifiers is further introduced as DC-cascade. With the resulting DC-cascade, medium output voltage is achieved with low voltage rectifiers and without a bulky transformer. This approach to form a DC-cascade reduces the effort required to achieve medium DC voltage with a simple rectifier system. In this context, a suitable DC-cascade control was presented and verified with a laboratory test setup. A gearless synchronous generator, which is highly segmented so that each segment can be connected to its own power rectifier, is investigated. Due to the mixed AC and DC voltage given by the DC-cascade structure, it becomes more demanding to the design of the generator insulation, which influences the copper fill factor and the design of the cooling system. A design strategy for the overall generator design is carried out considering the new boundary conditions.

High-resolution mesoscale wind-resource assessment of Fiji using the Weather Research and Forecasting (WRF) model

This study presents a high-resolution mesoscale wind-resource assessment of the small island developing state (SIDS) of Fiji using a 10-year simulation of the Weather Research and Forecasting (WRF) model with convection-permitting resolution. Our analysis evaluates the wind speed and Weibull distributions, diurnal and seasonal wind speed patterns, resource maps of annual and seasonal wind speed, power density, model statistical analysis and interannual wind speed variability. The results reveal that the WRF-model simulated wind resource parameters are in good agreement with observations at 24 existing weather stations. At 55 m above ground, the annual mean wind speed and wind power density varies from 1.5 m/s to 8 m/s and 50 W/m2 to 300 W/m2, respectively, for onshore land areas. Higher wind speeds are observed during austral winter than in austral summer. Forty high wind-resource areas are identified in this study, which were previously unknown. This indicates that there is potential for utility-scale wind power generation at selected locations with wind speed and power density greater than 6.4 m/s and 300 W/m2 (NREL, Wind Power Class 3). An estimated 1000 MW theoretical potential installed capacity is available for utility-scale wind power applications on Viti Levu and Vanua Levu.

A novel hybrid grey wolf optimization algorithm and artificial neural network technique for stochastic unit commitment problem with uncertainty of wind power

The unit commitment (UC) is highly complex to solve the increasing integrations of wind farm due to intermittent wind power fluctuation in nature. This paper presents a hybrid methodology to solve the stochastic unit commitment (SUC) problem depending on binary mixed integer generator combination with renewable energy sources (RESs). In this combination, ON/OFF tasks of the generators are likewise included to satisfy the load requirement as for the system constraints. The proposed hybrid methodology is the consolidation of grey wolf optimization algorithm (GWOA) and artificial neural network (ANN), hence it is called the hybrid GWOANN (HGWOANN) technique. Here, the GWOA algorithm is used to optimizing the best combination of thermal generators depending on uncertain wind power, minimum operating cost and system constraints – that is, thermal generators limits, start-up cost, ramp-up time, ramp-down time, etc. ANN is utilized to capture the uncertain wind power events, therefore the system ensures maximal application of wind power. The combination of HGWOANN technique guarantees the prominent use of sustainable power sources to diminish the thermal generators unit operating cost. The proposed technique is implemented in MATLAB/Simulink site and the efficiency is assessed with different existing methods. The comparative analysis demonstrates that the proposed HGWOANN approach is proficient to solve unit commitment problems and wind integration. Here, the HGWOANN method is compared with existing techniques such as PSO, BPSO, IGSA to assess the overall performance using various metrics viz. RMSE, MAPE, MBE under 50 and 100 count of trials. In the proposed approach, the range of RMSE achieves 9.26%, MAPE achieves 0.95%, MBE achieves 1% in 50 count of trials. Moreover, in 100 count of trials, the range of RMSE achieves 7.38%, MAPE achieves 1.91%, MBE achieves 2.87%.

Diagnosis of Fault in Doubly-Fed Three-Phase Induction Generator in Wind Power Applications

Inter-turn short-circuits faults are one of the most common problems in Induction machines, especially in the Doubly-Fed Induction Generator Based-Wind Energy Conversion system. Accurate and fast fault diagnosis and detection minimize the down-time of the units as further damages can be prevented. In this paper, a robust fault detection approach for Doubly-Fed Induction Generator (DFIG) based on wind generators is proposed. The faults’ smart diagnosis and detection are based on the Sliding Mode Observer and Second Order Sliding Mode Control. The observer generates a residual for detection of stator Inter-Turn Short Circuit faults which can affect a system model. A decision system is used to process the residual vector to detect faults. In order to shed more light on the designed approach performances regarding the inter-turn short-circuit fault occurrence, simulations were implemented in MATLAB/Simulink environment.

A novel hybrid model based on Bernstein polynomial with mixture of Gaussians for wind power forecasting

In recent years, the effective application of wind power forecasting in power system has been approved. However, owing to the intermittence and nonlinearity of wind power time series, accurate wind power forecasting is difficult for traditional forecasting methods. To improve the accuracy and stability of wind power forecasting, a new hybrid forecasting model is proposed in this study. The original wind power series is first decomposed into several intrinsic mode functions by complete ensemble empirical mode decomposition, and then a Bernstein polynomial forecasting model with mixture of Gaussians is constructed. Finally, a population-based multi-objective state transition algorithm with parallel search mechanism is developed to optimize the parameters of the hybrid model. To verify the effectiveness of the proposed hybrid forecasting model, a large number of comprehensive experiments are carried out with wind power data from a wind farm in Xinjiang, China. The experimental results show that the proposed hybrid model has higher forecasting accuracy and stronger stability compared with other popular forecasting models.

3D printed carbon fiber reinforced thermoplastic composites: A review

Additive manufacturing (AM) has been extensively used for producing desired parts with complex geometries without scrap production in short time. From past few years, it has been developed to produce prototypes, but its advantages have made researchers to deeply investigate and explore the possibility for manufacturing of functional parts. But the major limitation of AM technique which limits its use for manufacturing functional parts is that there is size limitation according to printer used, low production rate and low strength of the printed parts is not appropriate for direct replacement of functional parts. Many researchers have focussed on improving the strength of pure thermoplastic materials made from fused filament fabrication (FFF). One possible method is to build composite material by adding different fillers (such as carbon fiber, glass fiber, jute fiber, wood fiber, kevlar fiber etc.) to form a combination of fiber reinforced plastic (FRP) that can be applied directly to aerospace, automotive, and wind power applications. After adding fiber reinforcement, it is important to properly investigate the mechanical properties and quality of fiber synthesized manufactured plastic parts. This short review summarizes all research work that has been carried out to investigate the effect of carbon fiber on FFF printed fiber reinforced composite.

Application of wind power for chimney exhaust with a new chimney outlet configuration unnecessary to depend on wind directions

Application of wind power for chimney exhaust with a new chimney outlet configuration unnecessary to depend on wind directions

Averaged Dynamic Modeling and Control of a Quasi-Z-Source Inverter for Wind Power Applications

Typically, permanent magnet synchronous generator (PMSG)-driven wind turbines (WTs) present a two-stage power converter topology based on a DC/DC boost converter and voltage source inverter. In this study, this configuration is substituted by a quasi-Z-source inverter (qZSI), which is an attractive solution for boosting and converting the voltage from DC to AC in a single stage. A 2 MW PMSG WT with qZSI was studied herein. A switched dynamic model (SDM) of the qZSI (including the modeling of all switches and firing pulses) is not recommended for steady-state stability studies, long-term simulations, or large electric power systems. For such studies, two averaged dynamic models are proposed in this work. Both models present the same control system as the SDM, except for the generation of firing pulses, which is not necessary in the averaged models. The two proposed models were evaluated and compared with the SDM in the large-scale WT under different operating conditions, such as wind speed fluctuations, variable power references, and grid disturbances (voltage sag and 3rd and 5th order harmonics injection), in order to demonstrate their adequacy to represent the system response with a high reduction in the simulation time and computational efforts.

Investigation of Inner/Outer Rotor Permanent Magnet Flux Switching Generator for Wind Turbine Applications

In this paper two permanent magnet flux switching generator (PMFSG) are designed for 2 kW output power and 220 V phase voltage at 1500 rpm and comparatively analyzed for wind power application. Both PMFSG share same C-core stator connected back-to-back through flux bridge (β) with different rotor position i.e., inner rotor PMFSG (IR-PMFSG) and outer rotor PMFSG (OR-PMFSG). A detailed comparative analysis with various β for both IR-PMFSG and OR-PMFSG are performed under static characteristics, rated condition, overload capability and over-speed capability for generating output voltage, current, power and efficiency. Comparison of the static characteristics reveal that IR-PMFSG offers 47.93% higher rated power, 2.83% higher efficiency, 22.78% more magnetic flux, 56.91% reduced cogging torque and 83.18% lower torque ripples at the cost of 62.69% higher voltage regulation factor. Furthermore, under rated operating condition and overload capability with same specifications it is found that IR-PMFSG exhibits 1.47 times power than that of OR-PMFSG counterpart. Finally, over-speed capability is investigated in term of the output power which shows that IR-PMFSG significantly generate almost 2.25 time of the specification power whereas OR-PMFSG exhibits nearly 1.25 times power. This analysis shows that IR-PMFSG can be operated at wide-speed rage for higher power specification requirements maintaining efficiency greater than 90%.

A New Method for Design and Optimization of DFIG for Wind Power Applications

Doubly fed induction generator (DFIG) is one of the important generators that is used in the wind turbines structure. In the previous years, DFIGs based wind turbine system that have installed in the onshore and offshore wind farms have more number than other generators. In this paper, a new method has been presented for design and optimization of a 500 kW DFIG. At first, equations of the optimal design are reviewed for this generator, and then a model is presented for the study of the generator operation. The detailed design of DFIG is done and finite element analysis (FEA) is used to verify the design. In the following, a link is created by a software between FEA tool and genetic algorithm (GA) that is used for optimization. In each iteration, input parameters are changed by GA and is sent to FEA tool for calculation of cost functions. In other words, GA presents a new rotor, and stator slot dimension in each iteration and effect of these parameters is checked on generator operation by FEA tool, e.g., Ansys Maxwell Software. Input parameters that are created the best cost functions are selected as optimized parameters. Rotor and stator slots dimension have been selected as input parameters and cost functions are efficiency, rotor copper loss, and electromagnetic torque. In the results section, a comparison is done between analytical design and FEA design and then output wave of designed DFIG is proposed. In the following, sensitivity analysis is presented that is a study about effect of changing slot dimension on DFIG parameters. Finally optimization results are proposed for each cost function. Results show effectiveness of the proposed method, i.e., we can improve output parameters of DFIG via changing slot dimension.

Performance investigation of stand-alone induction generator based on STATCOM for wind power application

Self-Excited induction generators (SEIG) display a low voltage and frequency regulation due to variable applied load and input rotation speed. Current work presents a simulation and performance analysis of a three-phase wind-driven, SEIG connect to a three-phase load. In addition, an investigation of the dynamic operation of the induction generator from starting steady state until no-load operation. It is assumed that the input mechanical power is constant where the rotor of the SEIG rotates at a constant speed. The value of the excitation capacitance which is necessary to the operation of the induction generator also computed to ensure a smooth and self-excitation starting. The output voltage of the generator is adjusted by varying the reactive power injected by STATCOM. A 3-phase IGBT voltage source inverter with a fuel cell input supply is connected as STATCOM which is used to compensate for the reduction in the supply voltage and its frequency due to variation occurred in the applied loads. This work includes introducing a neuro-fuzzyy logic controller to enhance the performance of the SEIG by regulation the generated voltage and frequency The dynamic model of SEIG with STATCOM and loads are implemented using MATLAB/SIMULINK

Design and Characteristic Investigation of Novel Dual-Stator V-Shaped Magnetic Pole Six-Phase Permanent Magnet Synchronous Generator for Wind Power Application

This paper describes the characteristic investigation of the Novel Dual-stator V-Shape Magnetic Pole Six-Phase Permanent Magnet Synchronous Generator (NDSVSMPSP-PMSG) for wind power application. The proposed generator has V-shaped embedded magnetic pole in the rotor and six-phase winding in both the stator. The proposed generator has high-power density and high efficiency. For emphasizing the significance of the proposed generator, the characteristics of the NDSVSMPSP generator are analyzed and compared to one of the traditional generators, i.e., the Dual-stator Surface Mounted Six-Phase Permanent Magnet Synchronous Generator (DSSMSP-PMSG). For the design and characteristic investigation of both the generator, Finite Element Method (FEM) is chosen because of its high accuracy. Two modes of FEM analysis are considered, namely magneto-statics and transients. The magneto static analysis is used for the study of flux line and flux density distribution, while the transient analysis is considered for the generator’s characteristic investigation. The performance characteristics such as generated Electromotive Force (EMF) for both inner and outer stator, Percentage Total Harmonic Distortion (THD) of developed voltage, Developed EMF vs rpm, terminal voltage vs. current, developed rotor torque vs time, percent (%) ripple content in torque, and percent efficiency vs current for both generators are investigated. As a result, it can be stated that the power density and reliability of the proposed generator is higher than that of the traditional generator.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

FAULT LOCATION IN A VSC-HVDC LINK USING NEURAL NETWORKS

High-voltage direct current (HVDC) using voltage source converter (VSC) in transmission systems applications are currently a competitive alternative to the traditional AC transmission systems, especially for offshore wind power applications. The increases of rated power and distance to the shore have made VSC-HVDC transmission systems economically more efficient than the conventional solution based on an AC lines. Locating a fault in a submarine DC line must be fast and accurate because of the high cost of the submarine repairs as well as the operation cost (not-supplied energy). This paper proposed a fault location methodology based on artificial neural networks (ANN) for VSC-HVDC transmission system. The methodology only uses instantaneous values of electrical quantities (voltage and current) at one of the VSC terminal eliminating the problem of synchronisation. The proposed methodology has been tested and demonstrated using a typical VSC-HVDC test network, and simulation results show the appropriate performance of the methodology. Keywords: Artificial Neural Networks, Fault Location, HVDC Transmission, VSC-HVDC

Drivers of extreme wind events in Mexico for windpower applications

AbstractIn this study, we use a k‐mean clustering approach to investigate the weather patterns responsible for extreme wind speed events throughout Mexico using 40 years of the ERA‐5 atmospheric reanalysis. Generally, we find a large geographical split between the weather patterns that generate the strongest winds across the country. The highest wind power production periods therefore occur at different times in different regions across the country. In the South, these are associated with cold surge events, where an anticyclone is present in the Gulf of Mexico resulting in a strong Northerly flow across the Isthmus of Tehuantepec. In the North‐East, Easterly trade winds are responsible for the strongest wind events, whereas in the North‐West, it is the proximity of the North Pacific High. However, the weakest winds and lowest power production periods occur at the same times for all stations with the exception of Baja California Sur, meaning that low wind power production may be unavoidable at these times. The El Niño Southern Oscillation is found to influence wind speeds at some locations across Mexico at sub‐seasonal time‐scales. We report that statistically stronger wind speeds are observed during the Summer during El Niño months than during La Niña months for both sites in Chiapas and Oaxaca.

WRF Modeling of Deep Convection and Hail for Wind Power Applications

AbstractDeep convection and the related occurrence of hail, intense precipitation, and wind gusts represent a hazard to a range of energy infrastructure including wind turbine blades. Wind turbine blade leading-edge erosion (LEE) is caused by the impact of falling hydrometeors onto rotating wind turbine blades. It is a major source of wind turbine maintenance costs and energy losses from wind farms. In the U.S. southern Great Plains (SGP), where there is widespread wind energy development, deep convection and hail events are common, increasing the potential for precipitation-driven LEE. A 25-day Weather Research and Forecasting (WRF) Model simulation conducted at convection-permitting resolution and using a detailed microphysics scheme is carried out for the SGP to evaluate the effectiveness in modeling the wind and precipitation conditions relevant to LEE potential. WRF output for these properties is evaluated using radar observations of precipitation (including hail) and reflectivity, in situ wind speed measurements, and wind power generation. This research demonstrates some skill for the primary drivers of LEE. Wind speeds, rainfall rates, and precipitation totals show good agreement with observations. The occurrence of precipitation during power-producing wind speeds is also shown to exhibit fidelity. Hail events frequently occur during periods when wind turbines are rotating and are especially important to LEE in the SGP. The presence of hail is modeled with a mean proportion correct of 0.77 and an odds ratio of 4.55. Further research is needed to demonstrate sufficient model performance to be actionable for the wind energy industry, and there is evidence for positive model bias in cloud reflectivity.

Multilevel CSC System Based on Series–Parallel Connected Three-Phase Modules With Optimized Carrier-Shift SPWM

Current source converter (CSC) is widely used in high power applications. To increase the system power rating, both series and parallel connections can be adopted and implemented easily. In this article, a mixed series-parallel CSC structure is proposed for high power application. An optimized carrier-shift sinusoidal pulsewidth modulation (SPWM) is adopted for the mixed system to simultaneously improve the dc-link voltage quality and achieve multilevel ac output, which can potentially reduce the size of dc- and ac-side filters. Meanwhile, the system reliability can be significantly improved due to the modular design with carrier-shift SPWM and inherent short-circuit protection of CSC. With these advantages, the proposed mixed series-parallel CSC structure can be an attractive candidate for medium-voltage drives, high-voltage direct current, and offshore wind power applications. Simulation and experimental results verify the effectiveness of the novel mixed series-parallel CSC system with optimized carrier-shift SPWM.

Study of the Total Demagnetization Fault of an AFPM Wind Generator

This article investigates the total demagnetization fault in Axial Flux Permanent Magnet (AFPM) synchronous generator, suitable for wind power applications, using the three-dimensional Finite Element Method (3D-FEM). The machine, in which the demagnetization diagnosis has been investigated, consists of one coreless stator with concentrating winding, embed in resin and two rotors. In the current study, faulty cases of different number and relative position of total demagnetized magnets are studied. Finally, simulation results are compared to experimental results for validation. The stator current spectrum is studied as fault identification mean and it is shown that the fault signatures depend on the number of total demagnetized magnets, the relative position of the magnets on the rotor and the stator winding topology. In addition, there is an investigation of the partial demagnetization fault for comparison purposes. Moreover, analytical expressions for the magnetic flux density in the healthy case and in every faulty case are exported. These novel expressions, related to every demagnetized case, are presented for the first time in the literature.