Variable Speed Control In Wells Turbine-Based Oscillating Water Column Devices: Optimum Rotational Speed

The effects of climate change and global warming reveal the need to find alternative sources of clean energy. In this sense, wave energy power plants, and in particular Oscillating Water Column (OWC) devices, offer a huge potential of energy harnessing. Nevertheless, the conversion systems have not reached a commercially mature stage yet so as to compete with conventional power plants. At this point, the use of new control methods over the existing technology arises as a doable way to improve the efficiency of the system. Due to the nonuniform response that the turbine shows to the rotational speed variation, the speed control of the turbo-generator may offer a feasible solution for efficiency improvement during the energy conversion. In this context, a novel speed control approach for OWC systems is presented in this paper, demonstrating its goodness and affording promising results when particularized to the Mutriku's wave power plant.This work was supported in part by the University of the Basque Country (Universidad del Pais Vasco UPV/Euskal Herriko Unibertsitatea EHU) through Project PPG17/33 and by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, EU), as well as to the Basque Government through Ph.D. Grant PIF PRE_2016_2_0193. 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. They would also like to thank Yago Torre-Enciso and Olatz Ajuria from EVE for their collaboration and help

Performance Analysis on the Use of Oscillating Water Column in Barge-Based Floating Offshore Wind Turbines

Undesired motions in Floating Offshore Wind Turbines (FOWT) lead to reduction of system efficiency, the system’s lifespan, wind and wave energy mitigation and increment of stress on the system and maintenance costs. In this article, a new barge platform structure for a FOWT has been proposed with the objective of reducing these undesired platform motions. The newly proposed barge structure aims to reduce the tower displacements and platform’s oscillations, particularly in rotational movements. This is achieved by installing Oscillating Water Columns (OWC) within the barge to oppose the oscillatory motion of the waves. Response Amplitude Operator (RAO) is used to predict the motions of the system exposed to different wave frequencies. From the RAOs analysis, the system’s performance has been evaluated for representative regular wave periods. Simulations using numerical tools show the positive impact of the added OWCs on the system’s stability. The results prove that the proposed platform presents better performance by decreasing the oscillations for the given range of wave frequencies, compared to the traditional barge platform.This work was supported in part by the Basque Government, through project IT1207-19 and by the MCIU/MINECO through the projects RTI2018-094902-B-C21 and RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE)

A control technique for hybrid floating offshore wind turbines using oscillating water columns for generated power fluctuation reduction

The inherent oscillating dynamics of floating offshore wind turbines (FOWTs) might result in undesirable oscillatory behavior in both the system states and the generated power outputs, leading to unwanted effects on critical, extreme, and fatigue loads, and finally to a premature failure of the facility. Therefore, this kind of system should be capable of lessening such undesired effects. In this article, four oscillating water columns (OWC) have been installed within a FOWT barge-type platform. A novel switching control technique has been developed in order to reduce oscillations of the system created by both wind and wave, as well as the fluctuations in the generated power, by adequately regulating the airflow control valves. While the impact of the coupled wind-wave loads has been considered, a set of representative case studies have been taken into account for a range of regular waves and wind speeds. The study relies on the use of response amplitude operators (RAO) that have been pre-processed and evaluated in order to apply the switching control technique. In this sense, the starting time of the switching for below-rated, rated, and above-rated wind speeds have been calculated using the platform’s corresponding pitch RAO. Additionally, the blades’ pitch and generator torque have also been regulated by means of a constant torque variable speed controller to capture maximum energy for below-rated wind speed conditions and to match the rated generator power for rated and above-rated wind speed conditions, respectively. In order to peruse the feasibility and performance of the proposed strategy, a comparison has been carried out between the uncontrolled traditional barge-type platform and the controlled OWCs-based barge FOWT. The results demonstrate that the proposed control approach can effectively and successfully decrease both the oscillations in the system’s modes and the fluctuations in the generated power.This work was supported in part by the projects PID2021-123543OB-C21 and PID2021-123543OB-C22 (MCIN/AEI/10.13039/501100011033), Basque Government Groups IT1555-22 and Margarita Salas MARSA22/09 (UPV-EHU/MIU/Next Generation, EU)

Complementary Power Control for Doubly Fed Induction Generator-Based Tidal Stream Turbine Generation Plants

The latest forecasts on the upcoming effects of climate change are leading to a change in the worldwide power production model, with governments promoting clean and renewable energies, as is the case of tidal energy. Nevertheless, it is still necessary to improve the efficiency and lower the costs of the involved processes in order to achieve a Levelized Cost of Energy (LCoE) that allows these devices to be commercially competitive. In this context, this paper presents a novel complementary control strategy aimed to maximize the output power of a Tidal Stream Turbine (TST) composed of a hydrodynamic turbine, a Doubly-Fed Induction Generator (DFIG) and a back-to-back power converter. In particular, a global control scheme that supervises the switching between the two operation modes is developed and implemented. When the tidal speed is low enough, the plant operates in variable speed mode, where the system is regulated so that the turbo-generator module works in maximum power extraction mode for each given tidal velocity. For this purpose, the proposed back-to-back converter makes use of the field-oriented control in both the rotor side and grid side converters, so that a maximum power point tracking-based rotational speed control is applied in the Rotor Side Converter (RSC) to obtain the maximum power output. Analogously, when the system operates in power limitation mode, a pitch angle control is used to limit the power captured in the case of high tidal speeds. Both control schemes are then coordinated within a novel complementary control strategy. The results show an excellent performance of the system, affording maximum power extraction regardless of the tidal stream input.This work was supported in part by the University of the Basque Country (Universidad del Pais Vasco UPV/ Euskal Herriko Unibertsitatea EHU) through Project PPG17/33 and by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, EU). (Ministerio de Economa, Industria y Competitividad/Fondo Europeo de Desarrollo Regional, European Union). The authors would like also to thank the anonymous reviewers for the useful comments that have helped to improve the initial version of this manuscript

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 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

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

Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements

This paper presents an ANN-based rotational speed control to avoid the stalling behavior in Oscillating Water Columns composed of a Doubly Fed Induction Generator driven by a Wells turbine. This control strategy uses rotational speed reference provided by an ANN-based Maximum Power Point Tracking. The ANN-based MPPT predicts the optimal rotational speed reference from wave amplitude and period. The neural network has been trained and uses wave surface elevation measurements gathered by an acoustic Doppler current profiler. The implemented ANN-based rotational speed control has been tested with two different wave conditions and results prove the effectiveness of avoiding the stall effect which improved the power generation.This work was supported in part by the Basque Government, through project IT1207-19 and by the MCIU/MINECO through RTI2018-094902-B-C21/RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE)

Fuzzy Airflow-Based Active Structural Control of Integrated Oscillating Water Columns for the Enhancement of Floating Offshore Wind Turbine Stabilization

This paper presents the modeling and stabilization of a floating offshore wind turbine (FOWT) using oscillating water columns (OWCs) as active structural control. The novel concept of this work is to design a new FOWT platform using the ITI Energy barge with incorporated OWCs at opposite sides of the tower, in order to alleviate the unwanted system oscillations. The OWCs provide the necessary opposing forces to the bending moment of the wind upon the tower and the waves upon the floating barge platform. However, the forces have to be synchronized with the tilting of the system which will be ensured by the proposed fuzzy airflow control strategy. Using the platform pitch angle, the fuzzy airflow control opens the valve of one side and closes the valve of the other side accordingly. Results of simulation in comparison with the standard FOWT and a PID-based airflow control show the efficiency of the fuzzy airflow control and its superiority to decrease the platform pitching and the top tower fore-aft displacement.The authors would like to thank the Basque Government for funding their research work through project IT1555-22 and the Ministry of Science and Innovation (MCIN) for funding their research work through projects PID2021-123543OB-C21 and PID2021-123543OB-C22 by MCIN/AEI/10.13039/501100011033/FEDER, UE, and the University of the Basque Country (UPV/EHU) through the María Zambrano grant MAZAM22/15 funded by UPV-EHU/MIU/Next Generation, EU

Self-Adaptive Global-Best Harmony Search Algorithm-Based Airflow Control of a Wells-Turbine-Based Oscillating-Water Column

The Harmony Search algorithm has attracted a lot of interest in the past years because of its simplicity and efficiency. This led many scientists to develop various variants for many applications. In this paper, four variants of the Harmony search algorithm were implemented and tested to optimize the control design of the Proportional-Integral-derivative (PID) controller in a proposed airflow control scheme. The airflow control strategy has been proposed to deal with the undesired stalling phenomenon of the Wells turbine in an Oscillating Water Column (OWC). To showcase the effectiveness of the Self-Adaptive Global Harmony Search (SGHS) algorithm over traditional tuning methods, a comparative study has been carried out between the optimized PID, the traditionally tuned PID and the uncontrolled OWC system. The results of optimization showed that the Self-Adaptive Global Harmony Search (SGHS) algorithm adapted the best to the problem of the airflow control within the wave energy converter. Moreover, the OWC performance is superior when using the SGHS-tuned PID.This work was supported in part by the Basque Government, through project IT1207-19 and by the MCIU/MINECO through RTI2018-094902-B-C21 / RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE)