Data-driven control of a Pendulum Wave Energy Converter: A Gaussian Process Regression approach

Gioia, Daniele Giovanni; Pasta, Edoardo; Brandimarte, Paolo; Mattiazzo, Giuliana

doi:10.1016/j.oceaneng.2022.111191

Cited by 32 publications

(8 citation statements)

References 40 publications

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“…Any continuous function can be approximated when the number of RBFs is large enough. This is expressed as [16]:…”

Section: Gaussian-process-based Modeling Methodsmentioning

confidence: 99%

“…The work in [15] presented a model-free deep reinforcement learning controller for WEC that outperforms the model-based control in terms of wave energy production, but it is rather computationally expensive. The authors of [16] presented a novel data-driven approach for updating reactive control parameters based on a Multifidelity Gaussian process model for a WEC device. The machine learning applications for WEC control are focused on wave force forecasting [14], wave excitation force estimation [17], complex wave hydrodynamic approximation [18], direct controller optimization using a reinforcement learning algorithm [15,19], etc.…”

Section: Introductionmentioning

confidence: 99%

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Data-Driven Model Predictive Control for Wave Energy Converters Using Gaussian Process

Liu

Shi²,

Zhang

et al. 2022

Symmetry

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The energy harvested by an ocean wave energy converter (WEC) can be enhanced by a well-designed wave-by-wave control strategy. One of such superior control methods is model predictive control (MPC), which is a nonlinear constrained optimization control strategy. A limitation of the classical MPC algorithm is its requirement of an accurate WEC dynamic model for real-time implementation. This article overcomes this challenge by proposing a data-driven MPC scheme for wave energy converters. The data-based WEC model is developed by a Gaussian process (encompassing mean predictions and symmetric uncertainties) for a more accurate description of nonlinear and unmodeled system dynamics. A cross-entropy solver for data-driven MPC is employed for rapid, high-performance results, which samples trajectories from Gaussian distributions based on the concept of the symmetry principle. The proposed strategy is verified numerically by simulations which demonstrate its superior performance over a classical complex-conjugate controller.

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“…Any continuous function can be approximated when the number of RBFs is large enough. This is expressed as [16]:…”

Section: Gaussian-process-based Modeling Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data-Driven Model Predictive Control for Wave Energy Converters Using Gaussian Process

Liu

Shi²,

Zhang

et al. 2022

Symmetry

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“…Otros estudios desarrollados por Gioia et al [38] y Cai et al [39], han presentado dispositivos WEC en forma de péndulo, que podrían ser adaptados a los OWSC, pero en este caso articulados en la parte superior, evitando así tener el sistema PTO sumergido al tener la bisagra en la parte superior de la paleta, como lo muestra Ogai et al [40].…”

Section: Wec Oscilantes Sumergidosunclassified

Selección de un convertidor de energía de las olas de tipo oscilante y un sistema de toma de fuerza para el aprovechamiento de la energía undimotriz de Colombia

Castaño-Serna

Chica

2023

Rev UIS ing

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Los dispositivos de generación undimotriz son dispositivos que se encargan de transformar la energía proveniente de las olas del mar en energía eléctrica. Los sistemas de toma de fuerza se caracterizan por tomar la energía mecánica obtenida mediante el dispositivo undimotriz y facilitar su conversión a energía eléctrica. En este trabajo, inicialmente se realizó una búsqueda y evaluación de los dispositivos tipo oscilantes convertidores de energía de las olas y sistemas de toma de fuerza disponibles en la literatura para identificar su ventajas y desventajas con el fin de seleccionar los sistemas más indicados para el aprovechamiento del recurso undimotriz de Colombia. Los sistemas seleccionados corresponden a dispositivos undimotriz acoplados a estructuras fijas a la costa y sistemas de toma mecánica directa debido a que, estos presentan mayores ventajas en cuanto a su proceso de fabricación, puesta a punto, operación y mantenimiento. Finalmente se presenta un diagrama de flujo del proceso de diseño de estos sistemas.

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“…WEC represents the Wave Energy Converters, modeled with reference to the Pendulum Wave Energy Converter (PeWEC) device [44], using potential flow theory [45] and energy maximization control strategies [46]. The rated power of each device is 115 kWp, and its productivity was estimated from its power matrix and hourly sea state values off the coast of San Pietro, whose parameters were taken from the ERA5 database.…”

Section: Scenario Settingsmentioning

confidence: 99%

An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

et al. 2022

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The need for a clean and affordable energy supply is a major challenge of the current century. The tough shift toward a sustainable energy mix becomes even more problematic when facing realities that lack infrastructures and financing, such as small islands. Energy modeling and planning is crucial at this early stage of the ecological transition. For this reason, this article aims to improve an established long-run energy model framework, known as “OSeMOSYS,” with an add-on tool able to estimate different types of Levelized Cost Of Electricity (LCOE): a real and theoretical LCOE of each technology and a real and theoretical system LCOE. This tool fills a gap in most modeling frameworks characterized by a lack of information when evaluating energy costs and aims at guiding policymakers to the most appropriate solution. The model is then used to predict future energy scenarios for the island of San Pietro, in Sardinia, which was chosen as a case study. Four energy scenarios with a time horizon from 2020 to 2050—the Business-As-Usual (BAU) scenario, the Current Policy Projection (CPP) scenario, the Sustainable Growth (SG) scenario, and the Self-Sufficient-Renewable (SSR) scenario—are explored and ranked according to the efforts made in them to achieve an energy transition. Results demonstrates the validity of the tool, showing that, in the long run, the average LCOE of the system benefits from the installation of RES plants, passing from 49.1 €/MWh in 2050 in the BAU scenario to 48.8 €/MWh in the ambitious SG scenario. On the other hand, achieving carbon neutrality and the island’s energy independence brings the LCOE to 531.5 €/MWh, questioning the convenience of large storage infrastructures in San Pietro and opening up future work on the exploration of different storage systems.

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Data-driven control of a Pendulum Wave Energy Converter: A Gaussian Process Regression approach

Cited by 32 publications

References 40 publications

Data-Driven Model Predictive Control for Wave Energy Converters Using Gaussian Process

Data-Driven Model Predictive Control for Wave Energy Converters Using Gaussian Process

Selección de un convertidor de energía de las olas de tipo oscilante y un sistema de toma de fuerza para el aprovechamiento de la energía undimotriz de Colombia

An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

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