5,283 research outputs found

    Maximum power extraction from wind turbines using a fault-tolerant fractional-order nonsingular terminal sliding mode controller

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    This work presents a nonlinear control approach to maximise the power extraction of wind energy conversion systems (WECSs) operating below their rated wind speeds. Due to nonlinearities associated with the dynamics of WECSs, the stochastic nature of wind, and the inevitable presence of faults in practice, developing reliable fault-tolerant control strategies to guarantee maximum power production of WECSs has always been considered important. A fault-tolerant fractional-order nonsingular terminal sliding mode control (FNTSMC) strategy to maximize the captured power of wind turbines (WT) subjected to actuator faults is developed. A nonsingular terminal sliding surface is proposed to ensure fast finite-time convergence, whereas the incorporation of fractional calculus in the controller enhances the convergence speed of system states and simultaneously suppresses chattering, resulting in extracted power maximisation by precisely tracking the optimum rotor speed. Closed-loop stability is analysed and validated through the Lyapunov stability criterion. Comparative numerical simulation analysis is carried out on a two-mass WT, and superior power production performance of the proposed method over other methods is demonstrated, both in fault-free and faulty situations

    An Efficient and Robust Current Control for Polymer Electrolyte Membrane Fuel Cell Power System

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    Taking into account the restricted ability of polymer electrolyte membrane fuel cell (PEMFC) to generate energy, it is compulsory to present techniques, in which an efficient operating power can be achieved. In many applications, the PEMFC is usually coupled with a high step-up DC-DC power converter which not only provides efficient power conversion, but also offers highly regulated output voltage. Due to the no-linearity of the PEMFC power systems, the application of conventional linear controllers such as proportional-integral (PI) did not succeed to drive the system to operate precisely in an adequate power point. Therefore, this paper proposes a robust non-linear integral fast terminal sliding mode control (IFTSMC) aiming to improve the power quality generated by the PEMFC; besides, a digital filter is designed and implemented to smooth the signals from the chattering effect of the IFTSMC. The stability proof of the IFTSMC is demonstrated via Lyapunov analysis. The proposed control scheme is designed for an experimental closed-loop system which consisted of a Heliocentric hy-Expert™ FC-50W, MicroLabBox dSPACE DS1202, step-up DC-DC power converter and programmable DC power supplies. Comparative results with the PI controller indicate that a reduction of 96% in the response time could be achieved using the suggested algorithm; where, up to more than 91% of the chattering phenomenon could be eliminated via the application of the digital filter.The authors wish to express their gratitude to the Basque Government through the project SMAR3NAK (ELKARTEK KK-2019/00051), to the Diputación Foral de Álava (DFA) through the project CONAVAUTIN 2 and to the UPV/EHU for supporting this work

    Control of Proton Exchange Membrane Fuel Cell System

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    265 p.In the era of sustainable development, proton exchange membrane (PEM) fuel cell technology has shown significant potential as a renewable energy source. This thesis focuses on improving the performance of the PEM fuel cell system through the use of appropriate algorithms for controlling the power interface. The main objective is to find an effective and optimal algorithm or control law for keeping the stack operating at an adequate power point. Add to this, it is intended to apply the artificial intelligence approach for studying the effect of temperature and humidity on the stack performance. The main points addressed in this study are : modeling of a PEM fuel cell system, studying the effect of temperature and humidity on the PEM fuel cell stack, studying the most common used power converters in renewable energy systems, studying the most common algorithms applied on fuel cell systems, design and implementation of a new MPPT control method for the PEM fuel cell system

    A New Sliding Mode Control Strategy for Variable-Speed Wind Turbine Power Maximization

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    This is the peer reviewed version of the following article: Khalfallah Tahir, Cheikh Belfedal, Tayeb Allaoui, Mouloud Denai, and M’hamed Doumi, ‘A new sliding mode control strategy for variable‐speed wind turbine power maximization’, International Transactions on Electrical Energy Systems, Vol. 28 (4): e2513, April 2018, which has been published in final form at https://doi.org/10.1002/etep.2513. Under embargo until 10 January 2019. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The paper proposes a new sliding mode power control strategy for a wound-field synchronous generator-based variable speed wind energy conversion systems to maximize the power extracted from the wind turbine. The proposed controller can handle the inherent nonlinearities in wind energy conversion systems and the randomness of the wind speed as well as the uncertainties of the model and external disturbances. To reduce the chattering phenomenon that characterizes conventional sliding mode control, a sigmoid function with a variable boundary layer is proposed. The adaptive switching gains are adjusted on-line by using a fuzzy logic-based technique. Several simulation scenarios were performed to evaluate the performance of the proposed control scheme. The results demonstrate that this controller provides excellent response characteristics, is robust against parameter variations, and free from chattering phenomenon as compared with the conventional sliding mode control.Peer reviewedFinal Accepted Versio

    A survey on fractional order control techniques for unmanned aerial and ground vehicles

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    In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

    Investigations on performance enhancement measures of the bidirectional converter in PV–wind interconnected microgrid system

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    This is the final version. Available from MDPI via the DOI in this record. In this work, a hybrid microgrid framework was created with the assistance of a photovoltaic (PV) and wind turbine (WT) generator. Additionally, bidirectional control mechanisms were implemented where an AC system was integrated with permanent magnet synchronous generator (PMSG)-based WT and a DC system was integrated with a sliding mode algorithm controlled maximum power point tracker (MPPT)-integrated PV system. The wind and PV interconnected microgrid system was mathematically modeled for steady-state conditions. This hybrid microgrid model was simulated using the MATLAB/SIMULINK platform. Optimal load management strategy was performed on a chosen hybrid microgrid system. Various case studies pertaining to connection and disconnection of sources and loads were performed on the test system. The outcomes establish that the system can be kept up in a steady-state condition under the recommended control plans when the network is changed, starting with one working condition then onto the next

    Effects of POD control on a DFIG wind turbine structural system

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    This paper investigates the effects power oscillation damping (POD) controller could have on a wind turbine structural system. Most of the published work in this area has been done using relatively simple aerodynamic and structural models of a wind turbine which cannot be used to investigate the detailed interactions between electrical and mechanical components of the wind turbine. Therefore, a detailed model that combines electrical, structural and aerodynamic characteristics of a grid-connected Doubly Fed Induction Generator (DFIG) based wind turbine has been developed by adapting the NREL (National Renewable Energy Laboratory) 5MW wind turbine model within FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code. This detailed model is used to evaluate the effects of POD controller on the wind turbine system. The results appear to indicate that the effects of POD control on the WT structural system are comparable or less significant as those caused by wind speed variations. Furthermore, the results also reveal that the effects of a transient three-phase short circuit fault on the WT structural system are much larger than those caused by the POD controller

    Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

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    In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control.  This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

    A map-based model predictive control approach for train operation

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    Trains are a corner stone of public transport and play an important role in daily life. A challenging task in train operation is to avoid skidding and sliding during fast changes of traction conditions, which can, for example, occur due to changing weather conditions, crossings, tunnels or forest entries. The latter depends on local track conditions and can be recorded in a map together with other location-dependent information like speed limits and inclination. In this paper, a model predictive control (MPC) approach is developed. Thanks to the knowledge of future changes of traction conditions, the approach is able to avoid short-term skidding and sliding even under fast changes of traction conditions. In a first step, an optimal reference trajectory is determined by a multiple-shooting approach. In a second step, the reference trajectory is tracked by an MPC setup. The developed method is simulated along a track with fast-changing traction conditions for different scenarios, like changing weather conditions and unexpected delays. In all cases, skidding and sliding is avoided.Comment: 6 pages, 7 figures, accepted at ECC 202
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