Hybrid Neural Fuzzy Design-Based Rotational Speed Control of a Tidal Stream Generator Plant

Artificial Intelligence techniques have shown outstanding results for solving many tasks in a wide variety of research areas. Its excellent capabilities for the purpose of robust pattern recognition which make them suitable for many complex renewable energy systems. In this context, the Simulation of Tidal Turbine in a Digital Environment seeks to make the tidal turbines competitive by driving up the extracted power associated with an adequate control. An increment in power extraction can only be archived by improved understanding of the behaviors of key components of the turbine power-train (blades, pitch-control, bearings, seals, gearboxes, generators and power-electronics). Whilst many of these components are used in wind turbines, the loading regime for a tidal turbine is quite different. This article presents a novel hybrid Neural Fuzzy design to control turbine power-trains with the objective of accurately deriving and improving the generated power. In addition, the proposed control scheme constitutes a basis for optimizing the turbine control approaches to maximize the output power production. Two study cases based on two realistic tidal sites are presented to test these control strategies. The simulation results prove the effectiveness of the investigated schemes, which present an improved power extraction capability and an effective reference tracking against disturbance.This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE). The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS-Campus of International Excellence

Fuzzy logic control of an artificial neural network-based floating offshore wind turbine model integrated with four oscillating water columns

Renewable energy induced by wind and wave sources is playing an indispensable role in electricity production. The innovative hybrid renewable offshore platform concept, which combines Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs), has proven to be a promising solution to harvest clean energy. The hybrid platform can increase the total energy absorption, reduce the unwanted dynamic response of the platform, mitigate the load in critical situations, and improve the system's cost efficiency. However, the nonlinear dynamical behavior of the hybrid offshore wind system presents an opportunity for stabilization via challenging control applications. Wind and wave loads lead to stress on the FOWT tower structure, increasing the risk of damage and failure, and raising maintenance costs while lowering its performance and lifespan. Moreover, the dynamics of the tower and the platform are extremely sensitive to wind speed and wave elevation, which causes substantial destabilization in extreme conditions, particularly to the tower top displacement and the platform pitch angle. Therefore, this article focuses on two main novel targets: (i) regressive modeling of the hybrid aero-hydro-servo-elastic-mooring coupled numerical system and (ii) an ad-hoc fuzzy-based control implementation for the stabilization of the platform. In order to analyze the performance of the hybrid FOWT-OWCs, this article first employs computational Machine Learning (ML) techniques, i.e., Artificial Neural Networks (ANNs), to match the behavior of the detailed FOWT-OWCs numerical model. Then, a Fuzzy Logic Control (FLC) is developed and applied to establish a structural controller mitigating the undesired structural vibrations. Both modeling and control schemes are successfully implemented, showing a superior performance compared to the FOWT system without OWCs. Experimental results demonstrate that the proposed ANN-based modeling is a promising alternative to other intricate nonlinear NREL 5 MW FOWT dynamical models. Meanwhile, the proposed FLC improves the platform's dynamic behavior, increasing its stability under a wide range of wind and wave conditions.This work was supported in part by the Basque Government through project IT1555-22 and through the projects RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE), PID2021-123543OB-C21 and C22 funded by MCIN/AEI/10.13039/501100011033. The authors would also like to thank the UPV/EHU for the financial support through the Maria Zambrano grant MAZAM22/15 funded by the European Union-Next Generation EU and through grant PIF20/299

A regressive machine-learning approach to the non-linear complex FAST model for hybrid floating offshore wind turbines with integrated oscillating water columns

Offshore wind energy is getting increasing attention as a clean alternative to the currently scarce fossil fuels mainly used in Europe's electricity supply. The further development and implementation of this kind of technology will help fighting global warming, allowing a more sustainable and decarbonized power generation. In this sense, the integration of Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs) devices arise as a promising solution for hybrid renewable energy production. In these systems, OWC modules are employed not only for wave energy generation but also for FOWTs stabilization and cost-efficiency. Nevertheless, analyzing and understanding the aero-hydro-servo-elastic floating structure control performance composes an intricate and challenging task. Even more, given the dynamical complexity increase that involves the incorporation of OWCs within the FOWT platform. In this regard, although some time and frequency domain models have been developed, they are complex, computationally inefficient and not suitable for neither real-time nor feedback control. In this context, this work presents a novel control-oriented regressive model for hybrid FOWT-OWCs platforms. The main objective is to take advantage of the predictive and forecasting capabilities of the deep-layered artificial neural networks (ANNs), jointly with their computational simplicity, to develop a feasible control-oriented and lightweight model compared to the aforementioned complex dynamical models. In order to achieve this objective, a deep-layered ANN model has been designed and trained to match the hybrid platform's structural performance. Then, the obtained scheme has been benchmarked against standard Multisurf-Wamit-FAST 5MW FOWT output data for different challenging scenarios in order to validate the model. The results demonstrate the adequate performance and accuracy of the proposed ANN control-oriented model, providing a great alternative for complex non-linear models traditionally used and allowing the implementation of advanced control schemes in a computationally convenient, straightforward, and easy way.This work was supported in part by the Basque Government through project IT1555-22 and through the projects PID2021-123543OB-C21 and PID2021-123543OB-C22 (MCIN/AEI/10.13039/501100011033/FEDER, UE). The authors would also like to thank the UPV/EHU for the financial support through the María Zambrano grant MAZAM22/15 and Margarita Salas grant MARSA22/09 (UPV-EHU/MIU/Next Generation, EU) and through grant PIF20/299 (UPV/EHU)

Fuzzy Supervision Based-Pitch Angle Control of a Tidal Stream Generator for a Disturbed Tidal Input

Energy originating in tidal and ocean currents appears to be more intense and predictable than other renewables. In this area of research, the Tidal Stream Generator (TSG) power plant is one of the most recent forms of renewable energy to be developed. The main feature of this energy converter is related to the input resource which is the tidal current speed. Since its behaviour is variable and with disturbances, these systems must be able to maintain performance despite the input variations. This article deals with the design and control of a tidal stream converter system. The Fuzzy Gain Scheduling (FGS) technique is used to control the blade pitch angle of the turbine, in order to protect the plant in the case of a strong tidal range. Rotational speed control is investigated by means of the back-to-back power converters. The optimal speed is provided using the Maximum Power Point Tracking (MPPT) strategy to harness maximum power from the tidal speed. To verify the robustness of the developed methods, two scenarios of a disturbed tidal resource with regular and irregular conditions are considered. The performed results prove the output power optimization and adaptive change of the pitch angle control to maintain the plant within the tolerable limits.This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE) and in part by the University of the Basque Country (UPV/EHU) through PPG17/33. The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS - Campus of international Excellence

A Comparative Analysis of Self-Rectifying Turbines for the Mutriku Oscillating Water Column Energy Plant

Oscillating Water Column (OWC) based devices are arising as one of the most promising technologies for wave energy harnessing. However, the most widely used turbine comprising its power take-off (PTO) module, the Wells turbine, presents some drawbacks that require special attention. Notwithstanding different control strategies are being followed to overcome these issues; the use of other self-rectifying turbines could directly achieve this goal at the expense of some extra construction, maintenance, and operation costs. However, these newly developed turbines in turn show diverse behaviours that should be compared for each case. This paper aims to analyse this comparison for the Mutriku wave energy power plant.This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE) and in part by the University of the Basque Country (UPV/EHU) through PPG17/33. The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190, and EUSKAMPUSCampus of International Excellence

Analysis of electrical drive speed control limitations of a power take-off system for wave energy converters

The active control of wave energy converters with oil-hydraulic power take-off systems presents important demands on the electrical drives attached to their pumps, in particular on the required drive accelerations and rotational speeds. This work analyzes these demands on the drives and designs reliable control approaches for such drives by simulating a wave-to-wire model in a hardware in-the-loop simulation test rig. The model is based on a point absorber wave energy converter, being the wave, hydrodynamic and oil-hydraulic part simulated in a computer that sends and receives signals from the real embedded components, such as the drive generator, controller and back-to-back converter. Three different control strategies are developed and tested in this test rig and the results revealed that despite the drive limitations to acceleration levels, well above 1 × 104 rpm/s, these do not significantly affect the power take-off efficiency, because the required acceleration peaks rarely achieve these values. Moreover this drive is much more economical than an oil-hydraulic and equivalent one that is able to operate at those peaks of acceleration.This work was performed within the Strategic Research Plan of the Center for Marine Technology and Ocean Engineering, which is financed by Portuguese Foundation for Science and Technology (Fundacao para a Ciencia e Tecnologia-FCT) and the project "Generic hydraulic power take-off system for wave energy converters" funded by the Portuguese Foundation for Science and Technology (FCT) under contract PTDC/EMS-SIS-1145/2014. The testing has received support from MARINET, a European Community - Research Infrastructure Action under the FP7 "Capacities" Specific Programme, grant agreement nr. 262552. The research leading to these results is also part of the OceaNET project, which has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement nr. 607656

An Iterative Refining Approach to Design the Control of Wave Energy Converters with Numerical Modeling and Scaled HIL Testing

The aim of this work is to show that a significant increase of the e_ciency of aWave Energy Converter (WEC) can be achieved already at an early design stage, through the choice of a turbine and control regulation, by means of an accurate Wave-to-Wire (W2W) modeling that couples the hydrodynamic response calibrated in a wave flume to a Hardware-In-the-Loop (HIL) test bench with sizes and rates not matching those of the system under development. Information on this procedure is relevant to save time, because the acquisition, the installation, and the setup of a test rig are not quick and easy. Moreover, power electronics and electric machines to emulate turbines and electric generators matching the real systems are not low-cost equipment. The use of HIL is important in the development of WECs also because it allows the carrying out of tests in a controlled environment, and this is again time- and money-saving if compared to tests done on a real system installed at the sea. Furthermore, W2W modeling can be applied to several Power Take-O_ (PTO) configurations to experiment di_erent control strategies. The method here proposed, concerning a specific HIL for testing power electronics and control laws for a specific WECs, may have a more general validity.This work was supported by MARINET, a European Community—Research Infrastructure Action under the FP7 “Capacities” Specific Programme, grant agreement n. 262552

A Practical Model and an Optimal Controller for Variable Speed Wind Turbine Permanent Magnet Synchronous Generator

The aim of this paper is the complete modeling and simulation of an optimal control system using practical setup parameters for a wind energy conversion system (WECS) through a direct driven permanent magnet synchronous generator (D-PMSG) feeding ac power to the utility grid. The generator is connected to the grid through a back-to-back PWM converter with a switching frequency of 10 KHz. A maximum power point tracking (MPPT) control is proposed to ensure the maximum power capture from wind turbine, and a PI controller designed for the wind turbine to generate optimum speed for the generator via an aerodynamic model. MATLAB/Simulink results demonstrate the accuracy of the developed control scheme