70 research outputs found
Optimal design of wind turbine blades equipped with flaps
No full textAs a result of the significant growth of wind turbines in size, blade load control has become the main challenge for large wind turbines. Many advanced techniques have been investigated aiming at developing control devices to ease blade loading. Amongst them, trailing edge flaps have been proven as effective devices for load alleviation. The present study aims at investigating the potential benefits of flaps in enhancing the energy capture capabilities rather than blade load alleviation. A software tool is especially developed for the aerodynamic simulation of wind turbines utilising blades equipped with flaps. As part of the aerodynamic simulation of these wind turbines, the control system must be also simulated. The simulation of the control system is carried out via solving an optimisation problem which gives the best value for the controlling parameter at each wind turbine run condition. Developing a genetic algorithm optimisation tool which is especially designed for wind turbine blades and integrating it with the aerodynamic performance evaluator, a design optimisation tool for blades equipped with flaps is constructed. The design optimisation tool is employed to carry out design case studies. The results of design case studies on wind turbine AWT-27 (Aerodynamic Wind Turbine-27) reveal that, as expected, the location of flap is a key parameter influencing the amount of improvement in the power extraction. The best location for placing a flap is at about 70% of the blade span from the root of the blade. The size of the flap has also significant effect on the amount of enhancement in the average power. This effect, however, reduces dramatically as the size increases. For constant speed rotors, adding flaps without re-designing the topology of the blade can improve the power extraction capability as high as of about 5%. However, with re-designing the blade pretwist the overall improvement can be reached as high as 12%
A critical evaluation of deterministic methods in size optimisation of reliable and cost effective standalone Hybrid renewable energy systems
No full textReliability of a hybrid renewable energy system (HRES) strongly depends on various uncertainties affecting the amount of power produced by the system. In the design of systems subject to uncertainties, both deterministic and nondeterministic design approaches can be adopted. In a deterministic design approach, the designer considers the presence of uncertainties and incorporates them indirectly into the design by applying safety factors. It is assumed that, by employing suitable safety factors and considering worst-case-scenarios, reliable systems can be designed. In fact, the multi-objective optimisation problem with two objectives of reliability and cost is reduced to a single-objective optimisation problem with the objective of cost only. In this paper the competence of deterministic design methods in size optimisation of reliable standalone wind-PV-battery, wind-PV-diesel and wind-PV-battery-diesel configurations is examined. For each configuration, first, using different values of safety factors, the optimal size of the system components which minimises the system cost is found deterministically. Then, for each case, using a Monte Carlo simulation, the effect of safety factors on the reliability and the cost are investigated. In performing reliability analysis, several reliability measures, namely, unmet load, blackout durations (total, maximum and average) and mean time between failures are considered. It is shown that the traditional methods of considering the effect of uncertainties in deterministic designs such as design for an autonomy period and employing safety factors have either little or unpredictable impact on the actual reliability of the designed wind-PV-battery configuration. In the case of wind-PV-diesel and wind-PV-battery-diesel configurations it is shown that, while using a high-enough margin of safety in sizing diesel generator leads to reliable systems, the optimum value for this margin of safety leading to a cost-effective system cannot be quantified without employing probabilistic methods of analysis. It is also shown that deterministic cost analysis yields inaccurate results for all of the investigated configurations
Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties
No full textOptimal design of a standalone wind-PV-diesel hybrid system is a multi-objective optimisation problem with conflicting objectives of cost and reliability. Uncertainties in renewable resources, demand load and power modelling make deterministic methods of multi-objective optimisation fall short in optimal design of standalone hybrid renewable energy systems (HRES). Firstly, deterministic methods of analysis, even in the absence of uncertainties in cost modelling, do not predict the levelised cost of energy accurately. Secondly, since these methods ignore the random variations in parameters, they cannot be used to quantify the second objective, reliability of the system in supplying power. It is shown that for a given site and uncertainties profile, there exist an optimum margin of safety, applicable to the peak load, which can be used to size the diesel generator towards designing a cost-effective and reliable system. However, this optimum value is problem dependent and cannot be obtained deterministically. For two design scenarios, namely, finding the most reliable system subject to a constraint on the cost and finding the most cost-effective system subject to constraints on reliability measures, two algorithms are proposed to find the optimum margin of safety. The robustness of the proposed design methodology is shown through carrying out two design case studies
EFEKTIVITAS STRATEGI PROBLEM SOLVING TERHADAP KEMAMPUAN MENGANALISIS PADA MATA PELAJARAN MATEMATIKA KELAS V SDIT SALSABILA AL MUTHI’IN YOGYAKARTA
No full textRina Tri Maheri, "Efektivitas Strategi Problem Solving Terhadap Kemampuan Menganalisis Pada Mata Pelajaran Matematika Kelas V SDIT Salsabila Al Muthi’in Yogyakarta". Skripsi. Yogyakarta: Fakultas Ilmu Tarbiyah dan Keguruan UIN Sunan Kalijaga, 2018. Proses pembelajaran di SDIT Salsabila Al Muthi’in masih menggunakan strategi konvensional sehingga kurang bisa mencapai tujuan pembelajaran. Siswa hanya diarahkan untuk menghafal informasi sedangkan kemampuan menganalisis siswa masih rendah. Untuk mengatasi masalah tersebut diterapkan strategi pembelajaran problem solving. Adapun tujuan dari penelitian ini adalah: (1) Mengetahui perbedaan kemampuan menganalisis matematika dengan strategi problem solving dibandingkan dengan kemampuan menganalisis matematika menggunakan strategi konvesional, (2) Mengetahui efektivitas kemampuan menganalisis matematika dengan strategi problem solving. Desain penelitian menggunakan jenis eksperimen semu. Populasi dalam penelitian berjumlah 42 dan menggunakan sampel jenuh dimana seluruh populasi dijadikan sampel. Teknik dan instrumen pengumpulan data menggunakan wawancara, dokumentasi, dan tes. Teknik analisis data yang digunakan adalah statistik parametrik yaitu uji t dan uji Normalized Gain (N-Gain). Hasil penelitian antara lain: (1) Terdapat perbedaan kemampuan menganalisis matematika menggunakan strategi problem solving dibandingkan dengan pembelajaran kovensional, hal ini dibuktikan dengan uji t diperoleh nilai sig 0,000 yang artinya Ha diterima sehingga terdapat perbedaan antara rata-rata kemampuan menganalisis matematika siswa kelas eksperimen dengan kelas kontrol (2) Efektivitas strategi problem solving terhadap kemampuan menganalisis matematika siswa sebesar 0,861 atau setara dengan 86,1% sehingga strategi ini cukup efektif dibandingkan dengan strategi kovensional
An accurate method for the PV Model identification based on a genetic algorithm and the interior-point method
No full textDue to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% and 31% depending on the PV technology
Standalone DC microgrids as complementarity dynamical systems: Modeling and applications
No full textIt is well known that, due to bimodal operation as well as existent discontinuous differential states of batteries, standalone microgrids belong to the class of hybrid dynamical systems of non-Filippov type. In this work, however, standalone microgrids are presented as complementarity systems (CSs) of the Filippov type which is then used to develop a multivariable nonlinear model predictive control (NMPC)-based load tracking strategy as well as Modelica models for long-term simulation purposes. The developed load tracker strategy is a multi-source maximum power point tracker (MPPT) that also regulates the DC bus voltage at its nominal value with the maximum of ±2.0% error despite substantial demand and supply variations
A multivariable optimal energy management strategy for standalone DC microgrids
No full textDue to substantial generation and demand fluctuations in standalone green microgrids, energy management strategies are becoming essential for the power sharing and voltage regulation purposes. The classical energy management strategies employ the maximum power point tracking (MPPT) algorithms and rely on batteries in case of possible excess or deficit of energy. However, in order to realize constant current-constant voltage (IU) charging regime and increase the life span of batteries, energy management strategies require being more flexible with the power curtailment feature. In this paper, a coordinated and multivariable energy management strategy is proposed that employs a wind turbine and a photovoltaic array of a standalone DC microgrid as controllable generators by adjusting the pitch angle and the switching duty cycles. The proposed strategy is developed as an online nonlinear model predictive control (NMPC) algorithm. Applying to a sample standalone dc microgrid, the developed controller realizes the IU regime for charging the battery bank. The variable load demands are also shared accurately between generators in proportion to their ratings. Moreover, the DC bus voltage is regulated within a predefined range, as a design parameter
The double-tree method : An O(n) unsteady aerodynamic lifting surface method
No full textOpen Access via Wiley agreement. Acknowledgements Some results in this work were obtained using the Maxwell High Performance Computing Cluster of the University of Aberdeen IT Service (www.abdn.ac.uk/staffnet/research/hpc.php), provided by Dell Inc. and supported by Alces Software. The lead author would also like to thank the University of Aberdeen for their research scholarship funding.Peer reviewe
Propagation characteristics of millimeter waves in the H guide loaded with yttrium iron garnet films
No full textAerodynamic Design of Wind Turbine Blades Utilising Nonconventional Control Systems
No full textAs a result of the significant growth of wind turbines in size, blade load control has become the main challenge for large wind turbines. Many advanced techniques have been investigated aiming at developing control devices to ease blade loading. Individual pitch control system, adaptive blades, trailing edge microtabs, morphing aerofoils, ailerons, trailing edge flaps, and telescopic blades are among these techniques. Most of the above advanced technologies are currently implemented in, or are under investigation to be utilised, for blade load alleviation. The present study aims at investigating the potential benefits of these advanced techniques in enhancing the energy capture capabilities rather than blade load alleviation. To achieve this goal the research is carried out in three directions: (i) development of a simulation software tool suitable for wind turbines utilising nonconventional control systems, (ii) development of a blade design optimisation tool capable of optimising the topology of blades equipped with nonconventional control systems, and (iii) carrying out design optimisation case studies with the objective of power extraction enhancement towards investigating the feasibility of advanced technologies, initially developed for load alleviation of large blades, for power extraction enhancement. Three nonconventional control systems, namely, microtab, trailing edge flap and telescopic blades are investigated. A software tool, AWTSim, is especially developed for aerodynamic simulation of wind turbines utilising blades equipped with microtabs and trailing edge flap as well as telescopic blades. As part of the aerodynamic simulation of these wind turbines, the control system must be also simulated. The simulation of the control system is carried out via solving an optimisation problem which gives the best value for the controlling parameter at each wind turbine run condition. Developing a genetic algorithm optimisation tool which is especially designed for wind turbine blades and integrating it with AWTSim, a design optimisation tool for blades equipped with nonconventional control system is constructed. The design optimisation tool, AWTSimD, is employed to carry out design case studies. The results of design case studies reveal that for constant speed rotors, optimised telescopic blades are more effective than flaps and microtabs in power enhancement. However, in comparison with flap and microtabs, telescopic blades have two disadvantages: (i) complexity in telescopic mechanism and the added weight and (ii) increased blade loading. It is also shown that flaps are more efficient than microtabs, and that the location and the size of flaps are key parameters in design. It is also shown that optimisation of the blade pretwist has a significant influence on the energy extraction enhancement. That is, to gain the maximum benefit of installing flaps and microtabs on blades, the baseline blades must be redesigned
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