Wind Turbine Energy Systems Research Articles

Optimization and Validation of Model Predictive Controller (MPC) Approach for Wind Turbine Energy System in Domestic Loads

HIGHLIGHTS A novel MPC controller for Wind turbine system (WTS) is proposed to control the turbine actuation system using intelligent fuzzy logic. The controller proposed with the small actuator that defines with WTS will tackle losses associated during operation and rotation of WTS. The simulation outcomes suggest the proposed controller and further reduce ripples with various operating ranges in domestic loads holds better results compare to conventional one. Insert a highlight no longer than 85 characters.

Investigation of optimal power flow solution techniques considering stochastic renewable energy sources: Review and analysis

Increased penetration of renewable energy sources (RESs) in power system networks poses several challenges in system planning and management due to their uncertain and non-dispatchable nature. Consequently, this paper presents a thorough and precise review of recent solution methodologies for solving the optimal power flow (OPF) problems incorporated with stochastic RESs based on multiple peer-reviewed research publications in reputed journals. The Teaching Learning Based Optimization algorithm has been discussed and implemented to solve the OPF problem considering solar photovoltaic, wind turbine, and tidal energy systems. Weibull, Lognormal, and Gumbel probability density functions representing the uncertainty associated with the availability of wind speed, solar irradiance, and tidal energy systems, respectively. The results obtained from the proposed technique validate its novelty regarding OPF problems like minimization of operating cost, power loss in transmission lines, enhancement of voltage profile, and voltage stability. The proposed solution technique for OPF problems is tested on a modified IEEE 30-bus test system. Thus, this study assists in understanding the OPF problem for new researchers concerned with this domain and also gives the idea of implementing nature-inspired optimization algorithms on a defined test system to solve the OPF problem.

Techno-economic analysis and optimization of solar and wind energy systems for hydrogen production: a case study

ABSTRACT Water electrolysis can produce hydrogen by using a photovoltaic array as an electrical source to power the electrolyzer. Combining multiple energy sources has the potential to increase hydrogen production while also meeting other electrical needs. As Oman is planning to develop green hydrogen production, this study is proposed to help the private and governmental sectors to invest in the green hydrogen industry. In this study, the unique geographical location of Salalah and the meteorological data collected were utilized in the hybrid energy arrangement to generate electricity and produce a significant amount of hydrogen in Salalah using HOMER (Hybrid optimization model for electric renewables). The findings showed that the wind turbine (WT), photovoltaic (PV), fuel cell (FC), and hydrogen tank (HT) hybrid energy system is economically viable when compared to its counterparts in other systems and was chosen to meet Salalah in Oman’s electrical and hydrogen production needs. The PV-WT-FC-HT hybrid energy system is clearly the best option for the proposed hydrogen project in Salalah because it has the lowest Levelized Cost of Hydrogen (LCOH), 1.15 ($/kg), and Cost of Energy (COE), 19.0 ($/kWh).

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.

The Most Economical Design of Hybrid PV/Wind/Battery/Diesel Generator Energy System Considering Various Number of Design Parameters Based on Genetic Algorithm

The optimal sizing of a hybrid energy system may be a difficult undertaking problem, because of the huge number of structure settings and the irregular nature of solar radiation and wind power sources. This issue has a place with the classification of combinatorial enhancement, and its solution dependent on the classical technique may be a waste of time. This paper proposes a Genetic Algorithm (GA) methodology to find the optimal sizing of a hybrid Photovoltaic, Wind Turbine, Battery Storage, and Diesel Generators (PV/WT/BA/DG) energy system based on the number of PV modules, the number of wind turbines, the number of batteries, the number of diesel generators, the slope angle of PV panel and a hub height of wind turbine as the design parameters and study its effect on the Levelized Cost of Energy (LCOE). The proposed method aims to minimize the LCOE with high reliability of load supplying by increasing the design variables gradually. The proposed method will be tested at different sites with various metrological data to ensure its robustness. The results show that the LCOE decreases as the design parameters increase, also that the average wind-speed is inversely proportional to the LCOE of the site under study.

Conversion of AC wind energy system model to DC model for integration to optimization software with large scales

The work presented in this paper deals with an AC model of wind turbine system conversion to a DC model with reduced simulation time, for possible integration to optimization software with larges scales permitting a multi-objective optimization, such as the constrained optimization conjointly of the cost and power losses of the wind turbine energy system. The DC model is based on average calculation of the DC voltage recharging the battery energy accumulator used for recovering the converted wind energy and the electromagnetic torque. Indeed, classical model of wind turbine using generally electric generator associated to a PD3 rectifier to convert the alternative energy on DC energy recoverable on battery energy accumulator with need a large simulation time and thereafter it is non integrable to optimization software for multi-objective optimization problem resolution. The two models are implemented under Matlab-Simulink simulation environment. Simulation results valid entirely the wind turbine system DC model. Finally, as perspective it is interesting to use a booster chopper as an interface between the rectifier and the battery to optimize the recovered energy. An average model of the booster chopper can be integrated into the DC model for performance improvement of the conversion chain.

Economic analysis and optimal design of hydrogen/diesel backup system to improve energy hubs providing the demands of sport complexes

Energy crisis has led the communities around the world to use energy hubs. These energy hubs usually consist of photovoltics, wind turbines and batteries. Diesel generators are usually used in these systems as backup system. In this research, for the first time, an attempt is made to replace the traditional diesel only backup system with hydrogen only system and combined hydrogen and diesel backup system in hybrid photovoltaic and wind turbine energy systems. After introducing the available energy modeling tools and methods, explaining over advantages and disadvantages of each one, HOMER software was selected for this research. The simulations of this research show that using the traditional diesel generator as the backup system of the energy hub, creates a low cost system with the net present cost (NPC) of 2.5 M$ but also produces the highest amount carbon emission which is equal to 686 tons/year. The results of this study also indicate the hybrid renewable energy system which is supported by the hydrogen only backup system has the highest net present cost (NPC) and initial capital cost but reduces the maximum amount of carbon. The calculated NPC and carbon production of the energy hub using hydrogen only backup system are equal to 4.39 M$ and 55,205, respectively. On the other hand, the combined hydrogen/diesel backup system has reduced NPC compared with the hydrogen only backup system. The CO2 production of this system is also lower than the diesel only backup system. The calculations indicate that the NPC and CO2 production of the combined backup system are 3.53 M$ and 511,695 kg/yr. By comparing advantages and disadvantages of all 3 scenarios, the micro grid which uses the combined diesel/hydrogen backup system is selected as the most optimal system. The sensitivity analysis of the selected system shows that fluctuations of inflation rate along with the fluctuations of both fuel cells and electrolyzers capital cost do not affect the net present cost (NPC) considerably. On the other hand, fluctuations of capital cost of the main components like wind turbines affect the NPC much more than the others. If the inflation rate drops from 15% to 14% and wind turbine capital cost multiplier reduces from 1 to 0.8, the NPC value will drop by the value of 300,000 $.

Novel Mode Adaptive Artificial Neural Network for Dynamic Learning: Application in Renewable Energy Sources Power Generation Prediction

A reasonable dataset, which is an essential factor of renewable energy forecasting model development, sometimes is not directly available. Waiting for a substantial amount of training data creates a delay for a model to participate in the electricity market. Also, inappropriate selection of dataset size may lead to inaccurate modeling. Besides, in a multivariate environment, the impact of different variables on the output is often neglected or not adequately addressed. Therefore, in this work, a novel Mode Adaptive Artificial Neural Network (MAANN) algorithm has been proposed using Spearman’s rank-order correlation, Artificial Neural Network (ANN), and population-based algorithms for the dynamic learning of renewable energy sources power generation forecasting model. The proposed algorithm has been trained and compared with three population-based algorithms: Advanced Particle Swarm Optimization (APSO), Jaya Algorithm, and Fine-Tuning Metaheuristic Algorithm (FTMA). Also, the gradient descent algorithm is considered as a base case for comparing with the population-based algorithms. The proposed algorithm has been applied in predicting the power output of a Solar Photovoltaic (PV) and Wind Turbine Energy System (WTES). Using the proposed methodology with FTMA, the error was reduced by 71.261% and 80.514% compared to the conventional fixed-sized dataset gradient descent-based training approach for Solar PV and WTES, respectively.

Actuator and Sensor Fault Classification for Wind Turbine Systems Based on Fast Fourier Transform and Uncorrelated Multi-Linear Principal Component Analysis Techniques

In response to the high demand of the operation reliability and predictive maintenance, health monitoring and fault diagnosis and classification have been paramount for complex industrial systems (e.g., wind turbine energy systems). In this study, data-driven fault diagnosis and fault classification strategies are addressed for wind turbine energy systems under various faulty scenarios. A novel algorithm is addressed by integrating fast Fourier transform and uncorrelated multi-linear principal component analysis techniques in order to achieve effective three-dimensional space visualization for fault diagnosis and classification under a variety of actuator and sensor faulty scenarios in 4.8 MW wind turbine benchmark systems. Moreover, comparison studies are implemented by using multi-linear principal component analysis with and without fast Fourier transform, and uncorrelated multi-linear principal component analysis with and without fast Fourier transformation data pre-processing, respectively. The effectiveness of the proposed algorithm is demonstrated and validated via the wind turbine benchmark.

Review of Recent Trends in Optimization Techniques for Hybrid Renewable Energy System

Due to non-linear characteristics of renewable energy sources, a Maximum Power Point Tracking (MPPT) technique is adopted to maximize the output power. In this research article, on the basis of state of art review of renewable energy systems such as solar Photo-voltaic, Wind Turbine, Fuel Cell and Hybrid Renewable Energy System. The investigators have gone through the various MPPT techniques for different renewable energy systems out of which artificial intelligence based hybrid MPPT technique gives better performance as compared to other MPPT techniques.

Optimization and Reliability Evaluation of Hybrid Solar-Wind Energy Systems for Remote Areas

T his paper presents optimization and reliability analysis of renewable energy system for farm house electricity and irrigation load demand located at remote area. Optimum sizing of solar PV, wind turbine and battery energy system has been obtained to fully utilize the capacity of the system. The economic analysis have been carried out for different configuration of hybrid energy system in terms of net present cost (NPC), operating cost (OC), levelized cost of energy (LCOE). This paper proposes a recent evolutionary technique based on meta-heuristic optimization algorithm called grasshopper optimization algorithm (GOA), to be used for selecting optimal energy system configuration. Markov method has been employed for evaluating the reliability indices i.e. system failure rate, repair rate, availability, unavailability, mean up time (MUT), mean down time (MDT), loss of load probability (LOLP) and expected energy not supplied (EENS). Economic analysis, GOA and Markov method-based result shows that hybrid PV/wind/battery energy system is more reliable and cost effective system as compared to other configuration.Â

Order reduction of a wind turbine energy system via the methods of system balancing and singular perturbations

In this paper we study the order reduction of a wind turbine model using the methods of balancing transformation and singular perturbations. We show that the order of the considered wind turbine model can be reduced from eight to six via the balancing transformation. Further reduction via the aforementioned method results in a significant jump in the error bound. In contrast, the method of singular perturbations shows that the order of the model can be further reduced to four, or two, and still provide very good approximations to the system model, in terms of its transient step response. Moreover, we show that the reduction in model order achieved via singular perturbations is superior to that achieved via balancing, when the linear-quadratic near-optimal controllers are considered and when wind turbulence and a large-signal disturbance are applied to the system.

Feasibility of a new helical blade structure for a PV integrated wind turbine in a heat-driven swirling wind field

A controllable heat-driven swirling wind turbine system was integrated with a photovoltaics (PV) system for energy generation in a heat-collecting shed. This is a brand-new type of a wind energy generation system; and a helical three-blade structure in a vertical axis was introduced. The stationary pre-rotation vanes have a variable diameter and a helical twist angle of 225°. A numerical simulation was conducted to investigate the feasibility of a wind turbine blade structure for efficient energy output for industrial application. The computational fluid dynamics (CFD) tool OpenFOAM was used to simulate the operating conditions of the wind turbine. The findings illustrated the efficacy of the new system. The new helical blade structure is efficient for wind energy output of the turbine in a swirling wind field. The simulation under different heat source temperatures illustrated that an increase in heat source temperature could increase the output efficiency of the wind turbine energy system. The increment in output efficiency could be up to 19.07% when the temperature rises from 40 K to 80 K. The PV-swirling wind integrated system was shown to be more economical than a single solar photovoltaic system because its investment payoff period could be shortened by 2 years.

Comparative Study of Optimization Techniques for Renewable Energy System

There is a sudden fluctuations in wind speed and change of direction that affects the generator speed thus power generation of wind turbine system, so a controller like maximum power point tracking (MPPT) algorithm is essential in tracking the maximum power out of the available wind speed. MPPT algorithm can be classified into two categories such as with and without sensor as well as according to the algorithms used to find the maximum peak. A comparative analysis of different types of MPPT control methods on the basis of different speed responses and ability to obtain maximum power has been conducted. The literature based on the simulation results points out that the optimal torque control is a better MPPT control method for achieving the maximum power from wind turbine energy system against the most frequently used perturb and observe (P&O) method. The P&O method on the other hand is flexible and easy to implement but provide fluctuations about the maximum power point and is less efficient. The different types of MPPT techniques have been studied for wind turbine renewable energy system. The study points out that MPPT may also include of different dc–dc power converter and various control methods, and hybrid renewable energy system can be developed with multi-input energy systems.

Data Monitoring System for Micro-Wind Turbine Experimental Set Based on LabVIEW

The Wind Turbine Energy System (WTES) was applied to a micro-scale laboratory experimental set. Thus, there is a need to develop a data monitoring system in order to be applicable with the Wind Turbine Energy System. The aim of this study is to design and develop the data monitoring system for the Micro-Wind Turbine (MWT) experimental set, and to test the real time output and analyse the obtained results. The MWT output power is 100 watts 12 VDC with the cut-in speed is 3 m/s. The WTES consists of MWT, DC converter, and a Grid-connected inverter. This data monitoring system will be based on LabVIEW environment. The NI-9215 NI-9226, NI 9203, NI 9225, NI 9401 with chassis NI 9178 data acquisition devices were applied. The data monitoring program was developed by LabVIEW2013. The LabVIEW based data monitoring system has successfully met the objective of this study. It is capable of providing real time acquisition of the wind speed, electrical current, voltage and power of the Micro-Wind Turbine Energy System. Moreover, the software can generate a report from the MySQL data based via Microsoft office automatically.

Performance investigation of an integrated wind energy system for co-generation of power and hydrogen

In this paper, a wind turbine energy system is integrated with a hydrogen fuel cell and proton exchange membrane electrolyzer to provide electricity and heat to a community of households. Different cases for varying wind speeds are taken into consideration. Wind turbines meet the electricity demand when there is sufficient wind speed available. During high wind speeds, the excess electricity generated is supplied to the electrolyzer to produce hydrogen which is stored in a storage tank. It is later utilized in the fuel cell to provide electricity during periods of low wind speeds to overcome the shortage of electricity supply. The fuel cell operates during high demand conditions and provides electricity and heat for the residential application. The overall efficiency of the system is calculated at different wind speeds. The overall energy and exergy efficiencies at a wind speed 5 m/s are then found to be 20.2% and 21.2% respectively.

Robust fault estimation for wind turbine energy via hybrid systems

Abstract The rapid development of modern wind turbine technology has led to increasing demand for improving system reliability and practical concern for robust fault monitoring scheme. This paper presents the investigation of a 5 MW Dynamic Wind Turbine Energy System that was designed to sustain condition monitoring and fault diagnosis with the goal of improving the reliability operations of universal practical control systems. A hybrid stochastic technique is proposed based on an augmented observer combined with eigenstructure assignment for the parameterisation and the genetic algorithm (GA) optimisation to address the attenuation of uncertainty mostly generated by disturbances. Scenarios-based are employed to explore sensor and actuator faults that have direct and indirect impacts on modern wind turbine system, based on monitoring components that are prone to malfunction. The analysis is aimed to determine the effect of concerned simulated faults from uncertainty in respect to environmental disturbances mostly challenged in real-world operations. The efficiency of the proposed approach will improve the reliability performance of wind turbine system states and diagnose uncertain faults simultaneously. The simulation outcomes illustrate the robustness of the dynamic turbine systems with a diagnostic performance to advance the practical solutions for improving reliable systems.

Power Quality Enhancement for a Grid Connected Wind Turbine Energy System

A comprehensive control of a wind turbine system connected to an industrial plant is discussed in this paper, where an algorithm has been developed allowing a control structure that utilizes a four-leg inverter connected to the grid side to inject the available energy, as well as to work as an active power filter mitigating load current disturbances and enhancing power quality. A four-wire system is considered with three-phase and single-phase linear and nonlinear loads. During the connection of the wind turbine, the utility-side controller is designed to compensate the disturbances caused in presence of reactive, nonlinear, and/or unbalanced single- and intra-phase loads, in addition to providing active and reactive power as required. When there is no wind power available, the controller is intended to improve the power quality using the dc-link capacitor with the power converter attached to the grid. The main difference of the proposed methodology with respect to others in the literature is that the proposed control structure is based on the conservative power theory decompositions. This choice provides decoupled power and current references for the inverter control, offering very flexible, selective, and powerful functionalities. Real-time software benchmarking has been conducted in order to evaluate the performance of the proposed control algorithm for full real-time implementation. The control methodology is implemented and validated in hardware-in-the-loop based on the real time simulator “Opal-RT” and a TMSF28335 DSP microcontroller. The results corroborated our power quality enhancement control and allowed to exclude passive filters, contributing to a more compact, flexible, and reliable electronic implementation of a smart-grid based control.

Observer backstepping control of DFIG-Generators for wind turbines variable-speed: FPGA-based implementation

In this paper, we present a new contribution for the control of Wind-turbine energy systems, a nonlinear robust control of active and reactive power by the use of the Adaptative Backstepping approach based in double-fed asynchronous generator (DFIG-Generator).Initially, a control strategy of the MPPT for extraction of maximum power of the turbine generator is presented. Thereafter, a new control technique for wind systems is presented. This control system is based on an adaptive pole placement control approach integrated to a Backstepping control system. The stability of the system is shown using Lyapunov technique. Using the FPGA to implement the order gives us a better rapidity. A Benchmark was realized by a prototyping platform based on DFIG-generator, FPGA and wind-turbine; the experimental results obtained show the effectiveness and the benefit of our contribution.

Advanced DC\/AC Inverters: Applications in Renewable Energy (Luo, F.L. and Ye, H.; 2013) [Book News

This book presents advanced inversion technologies and provides design examples of inverters for renewable energy systems, including wind turbine and solar panel energy systems. The text systematically reviews cutting-edge inverter topologies and introduces new advanced topologies, originally developed by the authors, such as impedance source inverters (ZSI), quasi ZSI (qZSI), soft-switching inverters, and multilevel inverters up to 81 levels. Novel topologies include trinary hybrid multilevel inverters and four novel multilevel inverters: new series laddered multilevel converters, super-lift converter multilevel inverters, switched capacitor multilevel inverters, and switched inductor multilevel inverters. The authors also present modulation strategies and four methods to solve the problem of the accurate determination of the best switching angles to obtain lowest total harmonic distortion (THD) in advanced multilevel inverters. The analysis of the dc bus power injection is also presented, and methods to avoid regenerative power are also proposed. The text offers theoretical concepts, diagrams, summarizing tables, simulation and experimental results, and design examples for students, researchers, and engineers willing to learn from experts on how to design and implement inverters for renewable energy systems. Prof. Dr. Fang Lin Luo, Ph.D. (Cambridge U., U.K.), IEEE Senior Member, full professor at AnHui University, China,