Wind Turbine Energy Research Articles

Numerical modeling of an innovative hybrid wind turbine and WEC systems performance: A case study in the Persian Gulf

Due to the high cost of using offshore wind turbines, increasing the efficiency and amount of energy absorbed in different ways needs to be considered. This research work aims to study the dynamics and power absorption of the wave energy converter by proposing a new hybrid mono-pile wind turbine with two pitching WECs. Each WEC has a power-take-off mechanism activated by the pitch motion of the device linked to the mono-pile via a hinged type connection. The installation point was off the coast of Dayyer port in the Persian Gulf. First, the study area's wave, current, and wind characteristics were modeled and analyzed. Then a numerical model was developed to investigate and analyze the dynamics of the hybrid system and the effect of the damping coefficient between WT and WECs concerning power production under operational conditions. Hydrodynamic forces exerted on each part of the system were estimated using BEM in the time domain. The connections were also modeled as a linear, rotational damper and stiffness. The WECs' PTO's damping coefficient was established to optimize wave energy generation. By analyzing the damping coefficient of connections between the wind turbine and WECs, appropriate coefficients were obtained for maximum WECs performance. The results show that for this fixed hybrid arrangement installed in the coastal zone of Dayyer port in the Persian Gulf, 26% of the wind turbine energy is added to the device's energy by employing wave absorption systems.

Optimization of University Campus Microgrid for Cost Reduction: A Case Study

This paper presents an optimization model to minimize the fuel cost and CO2 emision on university campuses using an hybrid power system (HPS). The HPS is made up of solar photovoltaic (PV), diesel generator (DG), wind turbine (WT) and battery energy storage system (BESS). Two university campuses are used as case study to investigate the efficiency of the proposed HPS. The objective function is formulated such that each campus load is met by the renewable energy source (RES) when available and the DG only swicthes on when the output of the RES is not eneough to meet the load. The resulting non linear optimization problem is solved using a function in MATLAB called “quadprog”. The results of the simulation are analyzed and compared with the base case in which the DG is used exclusively to meet the entire load. The results show the effectiveness of the optimized HPS in saving fuel when compared to the base case and reflect the effects of seasonal variations in fuel costs.

Wind Turbine Pitch Actuator Regulation for Efficient and Reliable Energy Conversion: A Fault-Tolerant Constrained Control Solution

Motivated for improving the efficiency and reliability of wind turbine energy conversion, this paper presents an advanced control design that enhances the power regulation efficiency and reliability. The constrained behavior of the wind turbine is taken into account, by using the barrier Lyapunov function in the analysis of the Lyapunov direct method. This, consequently, guarantees that the generated power remains within the desired bounds to satisfy the grid power demand. Moreover, a Nussbaum-type function is utilized in the control scheme, to cope with the unpredictable wind speed. This eliminates the need for accurate wind speed measurement or estimation. Furthermore, via properly designed adaptive laws, a robust actuator fault-tolerant capability is integrated into the scheme, handling the model uncertainty. Numerical simulations are performed on a high-fidelity wind turbine benchmark model, under different fault scenarios, to verify the effectiveness of the developed design. Furthermore, a Monte-Carlo analysis is exploited for the evaluation of the reliability and robustness characteristics against the model-reality mismatch, measurement errors and disturbance effects.

Joint exploitation potential of offshore wind and wave energy along the south and southeast coasts of China

There is an increasing interest in co-exploiting marine energies of various types, as it can reduce grid connection and maintenance costs and enhance electricity production. A threefold objective of this work is as follows: i) investigate offshore wind and wave energy potential, complementarity & synergy, and correlation between the two resources in southern China's coastal region using long-term data; ii) analyze the benefits of wind-wave joint exploitation considering specific offshore wind turbine (OWT) and wave energy converter (WEC); and iii) propose a new index to determine the suitability for co-developing wind-wave projects. The results show that the Beibu Gulf and Taiwan Strait experience the highest correlation between the two resources, in contrast to the Zhejiang coast that exhibits the lowest one. On the other hand, the east waters of Taiwan and Zhejiang coast have the highest synergy. Moreover, quantitative and qualitative analysis shows that the combined device generates less variable power output and zero production in the areas with low correlation and high synergy than the OWT/WEC operating alone. The suggested best sites for future joint exploitation are along the Zhejiang coast, with the potential of generating nearly 40 GWh/year per combined device of SWT-6.0-154 and 6 MW Wave Dargon.

EPLL Control Technique Optimum Controller Gains to Control Voltage and Frequency in Standalone Wind Energy Conversion System

This study describes how to regulate the frequency and terminal voltage of a freestanding wind energy conversion system using an Enhanced Phase Locked Loop (EPLL)-based strategy to supply power to varied loads regardless of wind speed. In a standalone wind turbine energy conversion system, the EPLL control scheme extracts the reference source currents (SWECS). The control algorithm employs two proportional-integral (PI) controllers to create the active and reactive power components of the consumers' load currents, estimate reference source currents, and connect the zigzag transformer to PCC with VSC for neutral current compensation. To obtain optimal PI controller gains and most-suited settings to apply to SWECS, optimization approaches are used. The control algorithm is the most significant aspect of the system, and the speed with which it calculates, evaluates, and guesstimates determines the generation of source currents based on the algorithm's ideal controller PI gains. By properly estimating source currents, the EPLL control method improves dynamics and power quality issues, and the optimization technique is employed to acquire the gains of PI controllers. The proposed system employs the EPLL algorithm on a three-phase, four-wire system with changing loads to achieve ideal total harmonic distortion of source currents and voltages on the PCC, as defined by IEEE-519 standards. A battery energy storage device coupled to the VSC dc link keeps the load's necessary power constant. If the generator output exceeds the consumer demand, the excess power is delivered to BESS for temporary storage. When consumer demand exceeds generated power, a BESS delivers deficit power to the load, which adjusts and the frequency under various load conditions. The suggested system simulated results were tested with 3-phase 4-wire for harmonics reduction, load balancing, neutral wire current compensation, frequency and voltage control using MATLAB / Simulink.

A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties

The optimal device capacity can impose the hybrid combined cooling, heating and power (CCHP) system integrated with renewable energy on both the significant energy, economy, and environment benefits and the low dependence on the grid. However, the multiple uncertainties pose enormous challenges in the modeling framework and corresponding solving strategy. This paper proposes a two-stage multi-objective stochastic-robust hybrid optimization model for the optimal device capacity of a hybrid CCHP system. The multiple uncertainties are incorporated into this model, and they are modeled by integrating the stochastic hierarchy scenario-generation method into the robust box uncertainty set. The problems of multi-objective optimization and multi-stage coupling are handled by the ε-constraint method and column constraint generation, respectively. Eventually, the vital parameter influence of this model is analyzed by an industrial park case. The results show that the befitting scenario number can make scenario-based stochastic optimization save 97.71% of computation time and ensure the reliability of the optimized results. Moreover, the uncertain budget value significantly influences the successive device capacity while hardly impacting discrete device numbers. Besides, the installed capacities of the wind turbine, photovoltaic system and electrical energy storage considerably determine the economic performance of the hybrid system.

Winding Layout Considerations for an Integrated Generator–Rectifier System

An integrated generator–rectifier system is a promising architecture to harvest energy in offshore wind turbines. The system processes the majority of the incoming power using reliable, efficient, and inexpensive passive diodes operating at the generator line frequency. Elimination of capacitors at the diode rectifiers’ output by appropriately phase shifting the voltages of a multiport generator further improves the reliability of the overall architecture. This article creates a generalized framework to evaluate the interactions among different generator ports, diode-bridge rectifiers, and the active rectifier that is used to control the power flow. The framework enables quantifying the effect of integration on the dc bus power ripple and power imbalance among different generator ports. An exemplary winding layout is proposed that ensures theoretically zero interaction between the passive ports, although all the ports are mounted on a magnetic structure. A 10-MW integrated generator–rectifier design and simulation proves the accuracy of the framework using coupled circuit and finite-element simulation. Finally, a laboratory prototype shows the realization of the winding layout. The proposed inductance-matrix-based framework can be used to evaluate other winding layouts to estimate the effect of magnetic coupling on the performance of the system.

A reference open-source controller for fixed and floating offshore wind turbines

Abstract. This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5 MW reference wind turbine and International Energy Agency 15 MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10 % compared to the NREL 5 MW reference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30 % when using the platform feedback routine instead of a more traditional low-bandwidth controller.

Wind Turbine Efficiency Under Altitude Consideration Using an Improved Particle Swarm Framework

In this work, the concepts of particle swarm optimization-based method, named non-Gaussian improved particle swarm optimization for minimizing the cost of energy (COE) of wind turbines (WTs) on high-altitude sites are introduced. Since the COE depends on site specification constants and initialized parameters of wind turbine, the focus was on the design optimization of rotor radius, hub height and rated power. Based on literature, the COE is converted to the Saudi Arabia context. Thus, the constrained wind turbine optimization problem is developed. Then, non-Gaussian improved particle swarm optimization is provided and compared with the conventional particle swarm optimization for solving the optimization design in wind turbine efficiency under different altitudes ranging from 2500 to 4000 m. The results show that as altitude rises, the optimal rotor radius grows, but the optimal hub height and rated power drop, resulting in an increase in COE. Further, the non-Gaussian method display a faster convergence compared to the classical particle swarm optimization. These findings will be useful as a reference for wind turbine design at high altitudes. Thus, it could be employed to optimize the initialized parameter of wind turbine for the planned and largest wind farm in Saudi Arabia in Dumat Al-Jandal selected site.

The Selection of Optimal Structure for Stand-Alone Micro-Grid Based on Modeling and Optimization of Distributed Generators

The configuration programming of Distributed Generators (DGs) in a micro-grid (MG) through the achievement of multi-objective is an inevitable and primary issue ahead of micro-grid’s construction. The motivation of this paper is to select the most suitable catalog of MG from DC micro-grid (DC-MG), AC micro-grid (AC-MG), and hybrid MG by means of uncertainties’ models and corresponding DGs’ configurations. The DGs in all catalogs of MG are composed of wind turbine (WT), photovoltaic (PV), biomass generation (BG), and battery energy storage (BES) system. In terms of uncertainties’ models, the proposed mathematical models are combined with multifarious scenarios which are considered the uncertainties of variations in solar irradiance and wind speed, temperature, and load demand. Particularly, this paper also proposes differences in allocations and sizes of all the equipment based on the assumed specific structure for each catalog of MG. Then, the non-dominated sorting genetic algorithm III (NSGA-III) is utilized by MATLAB working platform to compute the multi-objective functions associating with the minimized system cost, the loss of power supply probability (LPSP), and the greenhouse gas (GHG) emissions for each catalog of MG. Finally, the results and comparisons demonstrate that the AC-MG is the optimal catalog for the case study, which has superiorities of economy and reliability. Although the DC-MG has lower GHG emissions, the AC-MG is the optimal choice after the comprehensive comparisons and analyses depended on three objectives.

Reliability Constrained Optimal Sizing and Examining Capacity Credit and Alternatives for Renewable Energy Sources

The growing penetration of renewable energy resources (RES) is changing its role from supplementary to alternative energy resources. If not properly planned, this transformation can significantly increase uncertainty due to the intermittent and non-dispatchable nature of resources such as solar irradiation and wind speed, potentially jeopardizing reliability of power supply. In this paper, a multi-objective approach is introduced to simultaneously optimize reliability and cost. Also, to deal with multiple types of RESs, a new concept, cost credit, is proposed as a supplement or alternative to capacity credit. Cost credit is a parameter that can be used to quantify the cost during planning and increase the reliability of the system. The overall objective is to combine and size the RESs, i.e., photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS), to meet the customer demand based on the total cost and reliability of the system. Two optimization methods, multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm (NSGA-II), are explored for grid connected and stand-alone systems. The best combined size that gives optimal reliability and cost, is then obtained from their outputs utilizing a Fuzzy technique. Then, capacity and cost credit are assessed for the obtained optimal solution. Finally, sensitivity analysis is conducted to examine the impact of changing different parameters, purchasing/selling price, capacity of grid-connected, and swept area of RES, on the system size.

Current-Source Solid-State DC Transformer Integrating LVDC Microgrid, Energy Storage, and Renewable Energy Into MVDC Grid

Solid-state dc transformer to integrate low-voltage dc (LVdc) microgrid, wind turbine (WT) generator, photovoltaic (PV), and energy storage (ES) into medium-voltage (MV) direct-current (MVdc) distribution grids is attractive. This article proposes current-source dc solid-state transformer (SST) for MVdc collection system in WT, PV, and ES farms or as an interface between the MVdc grid and the LVdc microgrid. Compared to conventional current-source converter (CSC) based SSTs, a switch reduction scheme on reverse-blocking device bridges is proposed to reduce device count and the number of devices on the dc-link current path. Importantly, the proposed switch reduction scheme is generic and can be applied to the dc ports of dc–ac, ac–dc, or dc–dc hard-switching or soft-switching CSC-based SSTs. Based on this scheme, the proposed current-source dc SSTs are derived, which have reduced electrolytic-capacitor-less dc-link. The proposed dc SSTs also achieve single-stage isolated dc–dc or dc–ac conversion, full-range zero-voltage switching (ZVS) for main switches, zero-current switching (ZCS) for resonant switches, and controlled <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ dv/dt $</tex-math></inline-formula> . The proposed dc SSTs, operating principles, predictive control method, the ZVS, and the controlled <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ dv/dt $</tex-math></inline-formula> under voltage buck-boost ranges are verified with MV simulations and an experimental prototype based on SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfets</small> , diodes, and a nanocrystalline transformer.

TWO DIMENSIONAL AEROFOIL WIND TURBINE BLADE DESIGN AND ANALYSIS USING CFD ANALYSIS

In the current scenario, wind turbine energy accounts for 70% of total renewable energy used in India. The Indian wind energy sector has a capacity of 20 GW installed (as on 31.5.2017). In terms of installed wind power capacity, India ranks fifth in the world and is regarded as a major player in the global wind energy market. For the current work, a design method based on modelling in Uni-graphics and followed by simulation using the CFD (Computational Fluid Dynamics) star ccm + programme is chosen, so that the expense and time required to find the optimum aerodynamic design of a wind turbine blade by experiment can be minimised.

Coupled Dynamic Analysis of Hybrid Offshore Wind Turbine and Wave Energy Converter

Abstract The combined offshore wind and wave energy on an integrated platform is an economical solution for the offshore energy industry as they share the infrastructure and ocean space. The study presents the dynamic analysis of the Submerged Tension-Leg Platform (STLP) combined with a heaving-type point absorber wave energy converter (WEC). The feasibility study of the hybrid concept is performed using the aero-servo-hydro-elastic simulation tool FAST. The study analyzes the responses of the combined system to understand the influence of the WECs on the STLP platform for various operating conditions of the wind turbine under regular and irregular waves. Positive synergy is observed between the platform and the WECs, and the study also focuses on the forces and moments developed at the interface of the tower and platform to understand the effect of wind energy on the turbine tower and the importance of motion amplitudes on the performance of the combined platform system. The mean and standard deviation for the translation and rotational motions of combined wind and wave energy converters are determined for different sea states under both regular and irregular waves to analyze the change in responses of the structure. The study observed a reduction in motion amplitudes of the hybrid floating system with the addition of the wave energy converters around the STLP floater to improve the energy efficiency of the hybrid system. The study helps in understanding the best possible arrangement of point absorber-type wave energy converters at the conceptual stage of the design process.

Impact of corner modification on wind characteristics and wind energy potential over flat roofs of tall buildings

Wind energy development in built environment is important for the future sustainable cities. The effects of corner modifications (benchmark, recessed, chamfered, and rounded roofs) and wind angles (θ = 0°, 22.5°, and 45°) over the flat rooftops of tall buildings were investigated through computational fluid dynamics (CFD) simulations. The velocity, turbulence intensity, skew angle, wind energy, and installation of wind turbines over roofs were also examined. The vertical wind profiles over the rooftops showed similar patterns at various corner modifications. The rounded and chamfered roofs showed higher velocities and lower turbulence intensities than the benchmark and recessed roofs, which can be attributed to the smooth flow separation from leading edges and the flow reattachment over the rounded and chamfered roofs. The hub heights were significantly lower at θ = 45° than those at 0° and 22.5°, due to the thinner boundary layer over roofs at θ = 45°. The highest wind energy amplification factor of 2.0 occurred over the rounded roof. The rounded roof was found to be ideal for the installation of wind turbines, due to the high velocity (more energy), low turbulence (small fatigue loads of wind turbines), and low installation height (low cost).

Fuzzy model predictive MPPT control of interconnected wind turbines drivetrain

AbstractThis paper provides a novel fuzzy‐based model predictive control (MPC) of a hydraulic‐based drivetrain that can combine the harvested energy of multiple wind turbines into one generator. The modeling is based on the sector nonlinearity approach and Takagi–Sugeno (T‐S) fuzzy. In addition, prediction and quadratic programming (QP) are formulated to obtain suitable control commands for the displacement of hydraulic pumps. Input–output linearization is utilized to control the generator torque load to regulate the speed. Minimizing the cost function for T‐S fuzzy‐based interconnected hydraulic wind turbine systems is converted to a QP problem to reduce the computation complexity. Therefore, the proposed nonlinear fuzzy‐based MPC scheme is more realistic to be implemented in real time. The feasibility of the optimization problem is improved when a new ellipsoidal terminal constraint is considered in the controller design process. Offline linear matrix inequalities (LMIs) are utilized to obtain the terminal cost of T‐S fuzzy‐based nonlinear systems. The simulation results demonstrate a significant reduction in computations and control efforts compared to LMI‐based MPC, kω2 approach, and (proportional–integral) PI controllers. It is also demonstrated that the system response to a sudden wind speed variation contains less overshoot and settles in a shorter time.

Perils of an open Arctic

Perils of an open Arctic

Feasibility and optimal operation of micro energy hybrid system (hydro/wind) in the rural valley region

Abstract With the increase in the global and local demand for electrical energy, which is necessary for the functioning of several fields such as the economy and agriculture, this study introduces a micro-hydro–wind hybrid system in order to obtain an economic feasibility of the off-grid isolated and renewable energy system. The main objective of this research is to determine the optimum design size for a hydro–wind hybrid energy system that is supposed to meet the demand for the electric load in front of a valley in Algeria called Yesser with variable water flow and wind speeds in three positions. Batteries are supplied to increase the reliability of the system when the performance of the wind turbine energy and the flow rate of the hydro system are evaluated. This system is proposed to reduce financial costs in addition to the possibility of providing interchangeable energy and operating reserves with short start times. The Homer Pro software is used to model the hybrid renewable energy system and to perform the required analysis of the economic side of the system in terms of the valley's flow rate and the wind speed. The average speed of the water flow in Yesser valley is varied between 10 and 24.6 m3/s, and three cases of the valley's flow rate were studied with the maximum and minimum wind speeds: the passage (the transit) with 10 m3/s, the downstream (the estuary) with 19 m3/s and the valley's upstream (the source) with 24.6 m3/s. From the results, it appears that the hydro power was not enough to meet the load demand in the first area (the transit); however, the hydro/wind hybrid system was capable to feed the required load. For the second area (the estuary) the wind power was needed just in summer season, and for the third area (the source) the hydro generator was sufficient to feed the load all the year as the hydro power generated exceeds the load demand. The Homer Pro software calculations prove that the financial cost of the system is inversely proportional with the wind speed, such that the higher the wind speed the lower the cost of the system, the same relationship is for the flow rate speed as we consider the third case the most cost-effective with 61 330.46 USD.

Analyzing a Decade of Wind Turbine Accident News with Topic Modeling

Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is scarce. The research presented here, upon construction of a text corpus of 721 selected wind turbine accident and failure news reports, develops and applies a custom-developed data analytics framework that integrates tabular analysis, visualization, text mining, and machine learning. Topic modeling was applied for the first time to identify and classify recurring themes in wind turbine accident news, and association mining was applied to identify contextual terms associated with death and injury. The tabular and visual analyses relate accidents to location (offshore vs. onshore), wind turbine life cycle phases (transportation, construction, operation, and maintenance), and the incidence of death and injury. As one of the insights, more incidents were found to occur during operation and transportation. Through topic modeling, topics associated most with deaths and injuries were revealed. The results could benefit wind turbine manufacturers, service providers, energy companies, insurance companies, government bodies, non-profit organizations, researchers, and other stakeholders in the wind energy sector.

A Hybrid Neuro-Fuzzy &amp; Bootstrap Prediction System for Wind Power Generation

Increasing integration of wind turbines in the electrical grid creates more challenges daily because of the unstable power of these units because they rely mainly on the wind. One of the solutions used to deal with these challenges is to predict the power produced from the wind turbine for a short or long term. Prediction of the power to be produced from the wind turbines gives a future vision of how to deal with these sources. Many techniques are used to improve the prediction of wind turbine energy. In this paper, a bootstrap hybrid neuro-fuzzy short-term prediction system for wind turbine power is presented. The bootstrap technique is used to increase the accuracy of the predicted value by creating multiple small datasets with the same features of the main dataset. A neuro-fuzzy model is created for each dataset using the hybrid optimization agent in MATLAB. The output of each neuro-fuzzy model is a prediction of wind turbine power. Therefore, the output of all models is combined using the combination model to calculate the final predicted wind turbine power. The system is simulated using MATLAB and the result show that the bootstrap hybrid neuro-fuzzy system predicts the wind turbine power for the next 24 h with accuracy 94.3%. The relative percentage error and average error for the system outputs are calculated and showed that the error is minimized to ±5.7%. Therefore, this prediction system could be useful for the challenges of integration wind turbine in electrical grid