1,720,968 research outputs found
A novel Economic Nonlinear Model Predictive Controller for power maximisation on wind turbines
No full textReducing the Levelized Cost of Energy (LCoE) is one of the main objectives of the wind turbine industry. There are several ways to achieve this goal: reducing construction and installation costs, reducing Operating&Maintenance costs, or increasing the power output. In this work, an Economic Nonlinear Model Predictive Control strategy is developed to maximise the power production of wind turbines. A novel three-states, non-linear Reduced Order Model is developed to predict aerodynamic power, rotor thrust and generator temperature with suitable accuracy. The control action is obtained from a constrained optimisation problem that uses the developed model, where the objective is the maximisation of the integral of the aerodynamic power. A set of constraints (including a bound on the generator temperature and the rotor thrust) are imposed. First, the turbine model is validated against high-fidelity simulations, then the controller performance and robustness are assessed in the entire wind range of operation, obtaining a significant increase of average power. Apart from the assessment of the controller performance in OpenFAST, the controller robustness is verified, introducing errors in the estimation of incoming wind, up to the case of a complete lack of information. The controller (freely downloadable from a dedicated repository) is effective in all the operating regions without the need for logical switches. Moreover, thanks to the optimised numerical solver adopted, it can be applied to actual wind turbines (which require real-time algorithmic performance)
Robustness of an Economic Nonlinear Model Predictive Control for Wind Turbines Under Changing Environmental and Wear Conditions
No full textIn this letter, the authors have assessed the robustness of an Economic Nonlinear Model-Predictive Controller (ENMPC) aimed at maximizing the power production of wind turbines. The scope of this letter is to quantify the sensitivity of this type of controller concerning wind conditions, climate, wind speed prediction unavailability, and aerodynamic performance degradation. A power production controller's robustness is crucial for the wind turbine industry due to the extreme variability of external conditions and the wear caused by long-term continuous operativity. Model-Predictive controllers are, in principle, more prone to robustness issues concerning standard controllers, a fact that limits their adoption on actual wind turbines. The analysis is performed with the fully-aeroelastic solver OpenFAST considering a wide set of realistic load cases. It is demonstrated that the ENMPC previously developed is robust to wind prediction unavailability and change in wind turbulence intensity. Conversely, it is not robust to the modelling error due to aerodynamic degradation. Indeed, a reduction in generated power concerning the reference controller is observed, especially for operating region two and end-life blades. Finally, a significant increase in power production is achieved considering the external temperature variation thanks to the ENMPC's direct handling of the generator temperature constraint
Advanced multidisciplinary design of next-generation green aircraft
No full textThis study presents an advanced Multidisciplinary Design Optimization (MDO) tailored for the design of next-
generation green aircraft, integrating innovative propulsion systems and advanced materials. The MDO is
based on an advanced Class III weight estimation method. Traditional Class I and II methods were inadequate
for contemporary green aircraft, necessitating a sophisticated approach to accommodate new concentrated
masses and materials. The Asymmetric Subspace Optimization (ASO) method was employed to balance
computational loads effectively across disciplines such as aerodynamics, structures, and propulsion systems.
Preliminary results for a hybrid electric/traditional regional aircraft have shown significant performance improve-
ments, including a notable reduction in fuel mass and an increase in lift-to-drag ratio
STRUCTURAL DESIGN OF NEXT-GENERATION REGIONAL GREEN AIRCRAFT
No full textThe aviation industry is increasingly focused on developing next-generation green aircraft to mitigate environ-
mental impacts. This study addresses the limitations of traditional weight estimation methods (Class I & II) in
the context of innovative aircraft designs, particularly focusing on the wing-box structure.
The conceptual design of three distinct aircraft configurations, a reference regional aircraft, a hybrid-electric
aircraft, and a full-electric aircraft, utilizes HEAD (Hybrid-Electric Aircraft Design), an internally developed
software at the University of Naples Federico II.
This study introduces a novel Class III weight estimation approach, developed at Sapienza University of Rome,
integrating Finite Element Analysis (FEA) capabilities. This method facilitates rapid generation of detailed FEM
models, crucial for Multidisciplinary Design Optimization (MDO) loops. Automated aeroelastostatic and buck-
ling analyses are conducted to ensure structural integrity under varied flight conditions, while accurate modeling
of composite materials like Carbon Fiber Reinforced Plastic (CFRP) enhances realistic weight predictions.
Utilizing the developed Class III approach, this study optimizes the wing-box structure of the concepts devel-
oped with HEAD and emphasizes the differences in terms of structural weight.
Results demonstrate significant weight reductions in optimized wing-box structures while maintaining structural
integrity compared to the initial guess oversized FEM. Key optimization strategies include exploring design
variables (e.g., ply thickness, spar cap width, stringer dimensions) using a genetic algorithm. Notably, tapering
thickness along the wing-box’s spanwise direction is crucial in achieving these weight reductions.
Comparison with HEAD software’s structural mass estimations reveals good correlation for the wing-box, with
differences noted in lighter (ICE and ICE+BAT) and heavier (PEMFC+BAT) configurations. Larger discrepan-
cies are evident in unoptimized components like the fuselage and tail, highlighting areas for future refinement
Control of power generated by a floating offshore wind turbine perturbed by sea waves
No full textOffshore wind energy is expected to provide a significant contribution to the achievement of the European Renewable Energy targets. One of the main technological issues affecting floating offshore wind turbines concerns generated power fluctuations and structural fatigue caused by sea-wave/platform interactions. This paper presents a fully-coupled aero/hydro/servo-mechanic model for response and control of floating offshore wind turbines in waves, suitable for preliminary design. The wind-turbine is described by a multibody model consisting of rigid bodies (blades and tower) connected by hinges equipped with springs and dampers (for realistic low-frequency simulation). The aerodynamic loads are evaluated through a sectional aerodynamic approach coupled with a wake inflow model. A spar buoy floating structure supports the wind turbine. The hydrodynamic forces are evaluated through a linear frequency-domain potential solver, with the free surface deformation effects included through a reduced-order, state-space model. An optimal controller is identified and applied for rejection of annoying fluctuations of extracted power and structural loads. The developed comprehensive model has been successfully applied to a floating version of the NREL 5 MW wind turbine for stability analysis, as well as for the analysis of uncontrolled and controlled responses to regular and irregular short-crested sea waves. The proposed controller, based on the combined use of blade pitch and generator torque as control variables and the application of an observer for non-measurable aerodynamic and hydrodynamic states estimation, has been demonstrated to be effective in a wide frequency range for alleviation of both generated power fluctuations and vibratory loads
Adaptation of maximum power point tracking controller for damaged wind turbines
No full textWind energy is essential for sustainable energy production, but its growth faces challenges. Wind turbines endure harsh conditions, such as rain, ice, dust, and sea spray, causing erosion and degrading aerodynamics. In this study, we address the relevant issue of leading-edge blade erosion. Initially, the power loss due to erosion will be quantified, considering three severity levels. Subsequently, a controller tuning strategy will be implemented to mitigate these losses during operation. Numerous design load cases (DLCs), each with different seeds, are necessary to achieve statistical significance. Therefore, it was decided to integrate the OpenFAST medium-fidelity software with high-fidelity CFD simulations to characterize erosion and quantify its effects. An initial evaluation of the aerodynamic coefficient maps was performed for the different levels of erosion. Subsequently, the potential gain was quantified by tuning the control strategy. Two sites were selected for the calculation of the Annual Energy Production (AEP) with medium-low wind speeds. Furthermore, a gain scheduling strategy that varies according to erosion and wind speed was considered, achieving positive results and an increase in AEP of up to 0.7% in the most severe case. This was achieved without any modifications to the turbine, but exclusively by acting on the existing controller
Individual blade pitch control for alleviation of vibratory loads on Floating Offshore Wind Turbines
No full textAmong the renewable energy technologies, offshore wind energy is expected to provide a significant contribution for the achievement of the European Renewable Energy (RE) targets for the next future. In this framework, the increase of generated power combined with the alleviation of vibratory loads achieved by application of suitable advanced control systems can lead to a beneficial LCOE (Levelized Cost Of Energy) reduction. This paper defines a control strategy for increasing floating offshore wind turbine lifetime through the reduction of vibratory blade and hub loads. To this purpose a Proportional-Integral (PI) controller based on measured blade-root bending moment feedback provides the blade cyclic pitch to be actuated. The proportional and integral gain matrices are determined by an optimization procedure whose objective is the alleviation of the vibratory loads due to a wind distributed linearly on the rotor disc. This control synthesis process relies on a linear, state-space, reduced-order model of the floating offshore wind turbine derived from aerohydroelastic simulations provided by the open-source tool OpenFAST. In addition to the validation of the proposed controller, the numerical investigation based on OpenFAST predictions examines also the corresponding control effort, influence on platform dynamics and expected blade lifetime extension. The outcomes show that, as a by-product of the alleviation of the vibratory out-of-plane bending moment at the blade root, significant reductions of both cumulative blade lifetime damage and sway and roll platform motion are achieved, as well. The maximum required control power is less than 1% of the generated power
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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