Wind Turbine Energy Research Articles

Data-driven mapping of hourly wind speed and its potential energy resources: A sensitivity analysis

Renewable energies play a significant role to mitigate the impacts of climate change. In countries like Spain, there is a significant potential of wind energy production which might be a key resource. In this research, we obtain wind power at 80 m height and wind turbine energy (assuming a specific turbine). To achieve this objective we produce an optimal mapping of the hourly “instantaneous surface wind speed” (height 10 m), based on the available data. An extensive region (Granada Province, south Spain) is studied with a spatial resolution of 300 m, during a long period (1996–2016). It allows us to assess the intra- and inter-daily variability of wind energy resources. Several interpolation approaches are tested and a cross validation experiment is applied to identify the optimal approach. The obtained maps were compared with the results obtained in the stations with two common frequency distributions (Rayleigh and Weibull). This is the first time that this sensitivity integrated analysis is performed over an extensive region (12600 km2) for a long time period (20 years) at fine spatiotemporal resolution (300 m, hourly scale). The results can be very valuable for a preliminary analysis of potential optimal location of wind energies facilities.

Improved Frequency Control Strategy for Offshore Wind Farm Integration via VSC-HVDC

Voltage source converter based high voltage DC system (VSC-HVDC) has become a very promising solution to integrate offshore wind farm. However, the equivalent inertia of the modern power system with large renewable energy integration becomes small, which will arouse some frequency stability problems. To tackle this problem, this paper proposes an improved frequency regulation strategy for VSC-HVDC integrated offshore wind farm. Firstly, in the frequency decrease stage, the rotor kinetic energy of wind turbines (WTs) is used to suppress the decrease of the frequency, and the control parameters are determined to make full use of the mechanical power and rotor kinetic energy of WTs, the frequency nadir is improved. Secondly, in the rotor speed recovery stage, the DC capacitors of VSC-HVDC are used to release power to compensate the deficiency value of wind farm output power and avoid the secondary frequency drop (SFD) problem. Lastly, the simulation is conducted in PSCAD/EMTDC to validate the effectiveness of the proposed coordinated frequency control strategy.

Study of shoot-through control pulse generation for a Z-source converter with wind turbine energy system

In this paper, there is a discussion about different modulation schemes for a dc-to-ac ZSC, also named Z-source inverter (ZSI), for triggering the main switches of three-phase legs or poles of an inverter. A prototype of an 8.5-kilowatt wind turbine with a 5.8-kilowatt Permanent Magnet Synchronous Generator (PMSG) system employed with voltage-controlled ZSI is implemented in this paper. For voltage control of load side of a wind turbine generation system (WTGS), a Proportional Integral (PI) controller is used. Three types of PWM schemes namely simple boost pulse width modulation (SB-PWM), third harmonic injection boost control (THIBC-PWM) and the space vector pulse width modulation (SV-PWM) techniques are compared on the basis of total harmonic distortion of the output ac-waveform of the Z-source Converter (ZSC) to find out that, which modulation technique is the best fit for a ZSI integrated with WTGS. The pros and cons of these techniques are compared in terms of line-voltage harmonics, phase-voltage harmonics, phase-current harmonics and switching stress of switches with detailed simulation results. These different modulation techniques are implemented on the MATLAB-Simulink domain. From Total Harmonic Distortion (THD) analysis, simple boost control technique is found to be the most appropriate shoot-through control technique for a ZSI in collaboration with WTGS.

Investigating capacity credit sensitivity to reliability metrics and computational methodologies

Assigning capacity value to renewable energy sources (RES) is a challenge faced in planning their integration with the grid. The difficulties stem from the natural characteristics of variability and intermittency of wind and solar sources. The capacity credit (CC) analysis evaluates the system’s actual power output compared with a constant capacity generator, i.e., conventional generator and determines an effective capacity to use for planning and operation. This paper presents different factors that could affect the CC of a system. Two methods are proposed to determine the CC, namely equivalent firm capacity (EFC) and effective load carrying capability (ELCC). Since these methods are based on satisfying reliability criteria, daily loss of load expectation (LOLE), hourly loss of load (LOLH), and expected energy not served (EENS) have been employed as indices. To obtain the CC value, both methods apply two techniques: traditional and optimization. Genetic algorithm (GA) is the optimization approach used in this paper. Then, this work compares the two techniques and shows the superior performance of the optimization approach. Two hybrid systems, stand-alone (SA) and grid-connected (GC) modes, are proposed and used as case studies. The hybrid systems consist of photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS). In this work, three different scenarios are used to compare capacity credit: system as a whole, only wind, and no batteries. Finally, sensitivity analysis is carried out to examine the impact of varying the wind speed, solar irradiation, and load. It is demonstrated that the choice of reliability index plays an important role in determining the capacity credit and it is shown that EENS is a more comprehensive and consistent index of reliability.

Impacts of mechanical energy storage on power generation in wave energy converters for future integration with offshore wind turbine

While offshore wind energy uptake is growing steadily, offshore wave energy remains largely untapped, despite having significant potential globally. The high cost and complexity of wave energy conversion systems are the main challenges to their commercial development globally, while they can be offset if they are integrated into the well-developed offshore structure of wind turbines. Since the source of the wave energy is associated with wind resources, these two ocean renewable resources have strong synergies that are yet to be combined effectively. Therefore, this paper aims to explore the idea of introducing wave energy converters into the offshore wind system as a hybrid system with a specific focus on wave energy converter (WEC) systems from their power characteristic perspective. In this paper, wave power fluctuations characteristics have been analysed and compared with wind power and two mechanical energy storage strategies, added inertia and gas accumulators, are investigated at the power take-off (PTO) system level on a typical point absorbed WEC. A sensitivity study of the impact of various mechanical storage systems on WEC performance was conducted under a set of real wave data. In addition, the significance of mechanical storage systems at the WEC PTO level in a DC-linked hybrid system is discussed along with enabling a better understanding of a future combined system. The results indicate that both mechanical storage options can effectively enhance energy production, reduce the power variations in the WEC system, and lead to the feasibility of integrating wave energy with the well-known offshore wind energy turbine system.

Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review

Renewable energy-based power generation technologies are becoming more and more popular since they represent alternative solutions to the recent economic and environmental problems that modern society is facing. In this sense, the most widely spread applications for renewable energy generation are the solar photovoltaic and wind generation. Once installed, typically outside, the wind generators and photovoltaic panels suffer the environmental effects due to the weather conditions in the geographical location where they are placed. This situation, along with the normal operation of the systems, cause failures in their components, and on some occasions such problems could be difficult to identify and hence to fix. Thus, there are generated energy production stops bringing as consequence economical losses for investors. Therefore, it is important to develop strategies, schemes, and techniques that allow to perform a proper identification of faults in systems that introduce renewable generation, keeping energy production. In this work, an analysis of the most common faults that appear in wind and photovoltaic generation systems is presented. Moreover, the main techniques and strategies developed for the identification of such faults are discussed in order to address the advantages, drawbacks, and trends in the field of detection and classification of specific and combined faults. Due to the role played by wind and photovoltaic generation, this work aims to serve as a guide to properly select a monitoring strategy for a more reliable and efficient power grid. Additionally, this work will propose some prospective with views toward the existing areas of opportunity, e.g., system improvements, lacks in the fault detection, and tendency techniques that could be useful in solving them.

Techno-socio-economic-environmental estimation of hybrid renewable energy system using two-phase swarm-evolutionary algorithm

A multi-objective optimal sizing model for an off-grid hybrid renewable energy system (HRES) consisting of solar photo-voltaic (PV), wind turbine (WT), diesel generator (DG) and lead-acid battery-based energy storage (ES) system is developed including techno-socio-economic and environmental considerations. The problem is formulated using six objectives; levelized cost of energy (LCOE), renewable fraction (RF), loss of power supply probability (LPSP), human development index (HDI), job creation (JC) and emission curtailment (EMC). To solve this real-world problem with complex practical constraints, a hybrid two-stage PSO-DE optimization (HPSODE) algorithm is constructed by connecting the improved variants of PSO and DE in series. The exploration capability of swarm intelligence is synthesized with the exploitation potential of classical evolutionary concepts, to achieve better performance with least dependence on algorithmic tuning parameters. A fuzzy satisfaction module (FSM) is appended to identify the solution with the highest possible attainment level for all the considered objectives. The selected optimization goals have a significant bearing on the optimal design, some are contradictory while others are similar in nature; therefore, impact analysis is presented. For the minimum cost solution, attainment of LCOE is 100%, HDI attainment is 0.27%, JC is 4.04%, emission curtailment is 6.29%, LPSP attainment is 91.25% and attainment of RF is 92.33%. On the other hand, when all six objectives are optimized, LCOE is attained by 68.61%, HDI by 92.97%, JC by 84.04% and EMC goal is satisfied by 78.98% while attainment of both LPSP and RF is 100%. For the selected location, the best configuration of HRES is PV-WT-ES, with total capacity of 175.44 kW. The levelized cost is 0.0779 $/kWh, human development index (HDI) is 0.6454, 0.2711 jobs are created and annual emission curtailment is 290147.28 kg, whereas unmet power is zero. Well distributed Pareto-optimal solutions are obtained, which offer multiple options to the designer. The results of the proposed HPSODE-FSM approach are compared and corroborated with results from literature and also with other state-of-the-art algorithms.

Power performance and dynamic responses of an integrated system with a semi-submersible wind turbine and four torus-shaped wave energy converters

To improve the power production of offshore wind farms, a combined wind turbine and wave energy converters concept is proposed in the present work. This concept is composed of a semi-submersible floating horizontal axis wind turbine and four torus-shaped wave energy converters. The relative heave motion between the tori and the columns on the semi-submersible platform is used to harvest wave energy. A coupled model of this combined concept is established by integrating the aerodynamic loads on blades, hydrodynamic loads on the platform with moorings and the wave energy converters and controller of the wind turbine. Coupled time-domain simulations are carried out to predict the power performance and dynamic responses of this combined concept under various conditions with turbulent wind and irregular waves. The results indicate that the introduced wave energy converters can obviously contribute to the annual power production of the combined concept when compared with an individual floating wind turbine. Moreover, the combined concept has benign dynamic responses under different environmental conditions and plays a positive synergy in improving power production.

Realization of Fuzzy Logic Controller in Microgrid for Mongolian case


 
 
 This paper presents the development and simulation of photovoltaic (PV), wind turbine and battery energy storage system (BESS) based microgrid in a Mongolian case. Although many standalone solar and wind microgrids are installed in Mongolia, they are not operating at total capacity and reliably due to a lack of control and proper use. The microgrid system operates in autonomous mode to serve the loads. To effectively control the microgrid voltage and frequency and achieve smoother power flow control between the generation and consumption, voltage–frequency (V/F) control based on the fuzzy logic controller (FLC) is proposed. Even though there are sudden load variations in the system and fluctuations in PV output power, the microgrid voltage and frequency are effectively maintained within limits by the proposed FLC. A fuzzy logic controller is used for an off-grid operated Microgrid constituted by the solar system, wind system and battery. The PV, wind turbine and BESS based microgrid system are simulated using Matlab/Simulink.
 
 

Land Subsidence Assessment for Wind Turbine Location in the South-Western Part of Madagascar

Finding a suitable location is a key factor for long-term investment in wind turbine energy. It includes understanding the area of interest, such as the subsidence of the land. Land subsidence is a gradual decrease in the surface of the Earth due to natural and/or induced causes. It can cause damage, such as settlement problems in the ground near infrastructure including buildings and wind turbines, thus not being a suitable place for long-term investment. Here, we show a case study of land subsidence prediction and assessment of the Atsimo Andrefana region, the great south-western part of Madagascar, using theoretical simulation and satellite images from the Sentinel-1 mission using D-InSAR method. The predicted land subsidence related to the depletion of groundwater reservoirs in the Atsimo Andrefana region is around 12 mm. We found ~5 mm of subsidence related to the growing city of Toliary and with an average subsidence of 124 mm and the highest record of 167 mm in the most southern part of the region for a period of 6 months. The spatial distribution of land subsidence allows us to choose the ideal location for wind turbine settlement, where land subsidence is not that severe, i.e., the areas with subsidence relatively low of equal or less than 10 mm within 6 months of observation, based on the processed data. Such results are essential for future environmentally friendly investments in the affected region, as the demand for green energy will always grow.

Hybrid Energy Storage System Using Pv-Wind Source for Power Quality Management

New natural power sources (HRES) like Photovoltaic (PV) system, wind turbine (WT) and battery energy capacity system (BESS) into the grid associated framework have been massively expanding its significance to satisfy the worldwide energy need. The coordinated plan mostly aims around power quality (PQ) issues because of the non-linear load condition. In this situation, dynamic power filters plays an important and huge part for development in power quality. Also, at transmission ground, there is a high necessity to control reactive power and voltage stability. Ordinarily, passive and dynamic filters (shunt and series channels) were utilized for the advancement of power quality. However, they experienced the issues like resonance, fixed compensation and other PQ issues. In this manner, to limit these issues, a cross combination of filters, it is intended to utilize passive and dynamic filters.The proposed framework is executed in MATLAB/Simulink stage to improve the performance during voltage drop, current drop, real power, reactive power and with regards to total harmonic distortions (THD’s).

Hybrid Energy Storage System Using Pv-Wind Source for Power Quality Management

New natural power sources (HRES) like Photovoltaic (PV) system, wind turbine (WT) and battery energy capacity system (BESS) into the grid associated framework have been massively expanding its significance to satisfy the worldwide energy need. The coordinated plan mostly aims around power quality (PQ) issues because of the non-linear load condition. In this situation, dynamic power filters plays an important and huge part for development in power quality. Also, at transmission ground, there is a high necessity to control reactive power and voltage stability. Ordinarily, passive and dynamic filters (shunt and series channels) were utilized for the advancement of power quality. However, they experienced the issues like resonance, fixed compensation and other PQ issues. In this manner, to limit these issues, a cross combination of filters, it is intended to utilize passive and dynamic filters.The proposed framework is executed in MATLAB/Simulink stage to improve the performance during voltage drop, current drop, real power, reactive power and with regards to total harmonic distortions (THD’s).

Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA).

Today, due to the end of fossil fuels and efforts to reduce the use of renewable resources, wind energy is a suitable option for the production of electrical energy due to its high-power generation. To increase the output efficiency of wind turbines, maximum power point tracking techniques are required for wind turbine energy conversion systems. In this research, the maximum power point (MPPT) method for two-way fed wind turbine systems (DFIG) is presented. The performance of the induction generator is presented on both sides of the power and the values of this generator such as speed, torque, voltage, current and maximum power at the time of wind speed changes. The presented work is presented in two scenarios and the model is performed without the algorithm then, a maximum power point tracking method based on the Colonial Competition Algorithm (ICA) has been applied to estimate the power of the two power induction generators. According to the results, it can be said that in the scenario with the algorithm of generating electric power by the turbine, several times in the production state is 9 MW, which is the rate of the turbine's nominal power, while in another scenario, the power generated by the turbine is 85% of the power in the state with the algorithm.

Minimization of the Cost of Energy of Wind Turbine through Various Power Models

Wind energy is the world’s free form of energy, besides that it has expenses, because of the wind turbine construction and maintenance. The Cost of Energy (CoE) of the wind turbine is used to estimate the amount of time it takes to recover the cost of an investment by the wind farm owners. Hence optimization of the wind turbine CoE will make wind a very competent source of energy. In this article, the wind speed is modified using three alternative distributions in order to reduce the wind turbine CoE, and the turbine Annual Energy Production (AEP) is evaluated. Mathematical functions such as linear, quadratic and cubic have been used to model the wind power. This study enables us to figure out the minimum turbine CoE among the mathematical distributions, along with the optimum mathematical function for wind power modelling and to optimize the rotor radius of turbine.

Combined wind and wave resource assessment and energy extraction along the Indian coast

The present study analyses the combined offshore wind and wave resource potential along the Indian coast. The state-of-the-art ERA5 reanalysis datasets that provide wind fields at 100 m height have been used for the first time to assess wind resources along the Indian Coast. Further, wave parameters were generated using the WAVEWATCH III (WWIII) model. Long-term spatial air density was considered to find accurate wind power potential. The results reveal that the southern coast of India exhibits higher wind power density and moderate wave energy flux (up to 0.65 kW/m2 and 10 kW/m), respectively. This region has the lowest variability (coefficient of variation <1, skewness <1.5, and kurtosis <4) and less correlation (<0.4). A suitable hotspot is identified based on the collocation feasibility index and depth constraint after excluding conflicted regions. A comprehensive investigation of local wind and wave characteristics was performed at the hotspot. Further, the yearly and monthly cross-correlations between wind and wave at different time lags were analysed. Actual estimation of power generation is carried out with various combinations of wind turbine (SG8.0-167 DD) and wave energy converter (Oceantec). The outcome of the present study will help to initiate the development of joint offshore wind and wave energy farms in India.

Parameterising the Impact of Roughness Evolution on Wind Turbine Performance

This paper presents a study investigating the effects of surface roughness on airfoil performance and its consequences for wind turbine energy yield. This study examined 51 sets of experimental data across 16 airfoils to identify trends in roughened airfoil performance. The trends are used to formulate a novel ‘roughness evolution parameter’ that can be applied to airfoils with no roughened data available to predict the impact of roughness on performance. Blade element momentum theory is used to model the performance of the DTU 10 MW reference wind turbine, with uniformly roughened blades emulated using the roughness evolution parameter. An annual energy production loss between 0.6–9.6% is found for the DTU 10 MW turbine when considering a plausible range of values for the roughness evolution parameter derived from the experimental data. A framework has been developed to evaluate how the roughness evolution parameter changes over time, informed by observed changes in wind farm performance from previous studies.

Evaluation of NDE Characteristics for Measuring the Painting Thickness in Wind Energy Turbine Power Blades Based on Ultrasonic Wave Simulation

In recent years, wind energy turbine blades have been manufactured using composite materials. Post manufacturing, these blades are painted with special coatings to protect the surface. Subsequently, they are generally tested by breaking a specimen and checking the uniform coating state using an optical microscope. A non-destructive technique is considered as an inspection tool; therefore, ultrasonic techniques are widely selected to measure thin painting thicknesses. In this study, the NDE (Nondestructive evaluation) CIVA package (CIVA 2020 software, NDE CIVA) was adopted for ultrasound simulation. The package was used to propose parameters, which brings the measurement of painting thickness based on the non-destructive ultrasonic waves. An optimal technique was also proposed with a use of the time and amplitude reflected from the surface and the back in the samples according to the blade painting thicknesses.

A hybrid renewable energy production system using a smart controller based on fuzzy logic

Introduction. This article proposes an improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology with multiple inputs and outputs (I/O). It is used to control hybrid electric energy sources built around photovoltaic solar panels, wind turbine and electric energy storage system assisted by the electric grid. The novelty in this work that solar photovoltaic, wind turbine and storage system energy sources are prioritized over the grid network which is solicited only during adverse weather conditions, in order to supply a typical household using up to 4,000 Wh per day. In addition of that, the surplus of renewable energy produced during favorable climatic condition is used to produce hydrogen suitable for household heating and cooking using eletrolyzer system. Purpose. Development of improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology. This system is embedded on Arduino 2560 mega microcontroller, on which the fundamental program of fuzzy logic and the distribution of events with all possible scenarios have been implemented according to a flowchart allowing the management of the hybrid system. Methods as well as a parametric search and a simulation to characterize the system, are carried out in order to put on the proposed techniques to ensure continuous accommodation at home. Results. The proposed system results confirm their effectiveness by visualizing the output control signals from the electronic switches. Practical value of which transmits power through a single-phase DC/AC converter to power the AC load for the accommodation.

Potential of fibre metal laminates in root joints of wind energy turbine rotor blades

The length of rotor blades is showing continuous growth for future wind energy turbines leading to high bending moments, which must be transferred to the hub by the root section. As the growth of the root diameter is limited by factors such as transportability, motivation to improve the load carrying capacity without changing the geometry is high. Hybridisation with metals shows a possibility to intrinsically increase the bearing strength of fibre-reinforced plastics. This publication presents experimental investigations into hybrid laminates to be used in so-called T-joints for connecting rotor blades to the hub of the nacelle of a wind energy turbine. An overview is given about the bearing strength of several material combinations hybridising glass- and carbon fibre-reinforced plastics (GFRP, CFRP) with aluminium, titanium and steel alloys. A GFRP-steel-hybrid can be identified as a material with a high reinforcing effect even for low amounts of steel. A hybrid T-joint demonstrator is manufactured by resin infusion and tested under static tension. In comparison with a GFRP reference, a joining strength increase of about 33% is achieved for a steel content of 3%. Further coupon level tests reveal a weak spot in the transition zone between the monolithic GFRP region and full hybrid region as the static and fatigue resistance clearly decreases in comparison with monolithic GFRP and full hybrid references.

Multidisciplinary aeroelastic optimization of a 10MW-scale wind turbine rotor targeting to reduced LCoE

In the present paper, multidisciplinary optimization (MDAO) is applied with the aim to reduce the levelized cost of energy (LCoE) of the DTU-10MW Reference Wind Turbine (RWT) rotor. As application paradigm, the widely applied in the literature passive load control method of Bend Twist Coupling (BTC) is considered. The integrated optimization framework combines in a common loop, rotor aerodynamic and full wind turbine structural elasto-dynamic analyses, aiming at determining the optimum rotor diameter, the planform of the blade in terms of twist and chord distributions, the offset ply angle for BTC and the inner structure of the blade with cost function directly the LCoE. It is based on an in-house servo-aero-elastic analysis tool for determining the ultimate loads along the span of the blades and the power yield, whereas a cross-sectional analysis tool is employed for acquiring structural properties of the modified blade and stresses distributions over the blade sections. A cost model of the overall wind turbine is implemented by combining existing in the literature models and open data. The new rotor design is found to have a reduced LCoE by 0.71% and to produce 2.4% higher energy annually due to its increased by 3.7% diameter.