After the 2015 United Nations Climate Change Conference (COP21) the interest for clean and renewable energy is high priority in global energy policy. In this sense, the ocean offers a great potential for energy harnessing. However, in the path to commercialization, conversion systems still lack maturity. Oscillating water column (OWC) power plants are among the most promising cost-effective and ecologically compatible technologies. The NEREIDA MOWC wave power plant, located on the Basque coast of Mutriku, is a clear example of this principle. In addition, the maximum power point tracking (MPPT) strategy, which has already been used successfully in other renewable energy systems, stands out as one of the most useful schemes. In this context, this paper focuses on the implementation of a novel MPPT control approach for the OWC systems in order to optimize the power delivered to the grid. For this purpose, a full wave-to-wire plant model is introduced, and a new MPPT-based control scheme is presented. The controller continuously adjusts the energy conversion of the doubly fed induction generator according to an established MPPT curve so as to optimize the power generated. In order to demonstrate the goodness and feasibility of the proposed control scheme, its behavior is tested and compared in two representative case studies of both uncontrolled and controlled plants. In the first case, an air valve control is employed, and in the second case, an MPPT-based control strategy has been implemented. Results show that the proposed MPPT-based control successfully matches the optimum rotational speed, allowing maximum active power generation.

Oscillating Water Column (OWC)-based power take-off systems are one of the potential solutions to the current energy problems arising from the use of nuclear fission and the consumption of fossil fuels. This kind of energy converter turns wave energy into electric power by means of three different stages: firstly wave energy is transformed into pneumatic energy in the OWC chamber, and then a turbine turns it into mechanical energy and finally the turbogenerator module attached to the turbine creates electric power from the rotational mechanical energy. To date, capture chambers have been the least studied part. In this context, this paper presents an analytical model describing the dynamic behavior of the capture chamber, encompassing the wave motion and its interaction with the OWC structure and turbogenerator module. The model is tested for the case of the Mutriku wave power plant by means of experimental results. For this purpose, representative case studies are selected from wave and pressure drop input-output data. The results show an excellent matching rate between the values predicted by the model and the experimental measured data with a small bounded error in all cases, so that the validity of the proposed model is proven.

Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness.

In comparison to wind farms , the relative scarcity of actual operational data from wave power plants has contributed to a significant research gap in the areas of wave farm forecasting and cost reduction. In this context, this manuscript presents a new Machine Learning-based Power Take-Off (PTO) diagnosis for wave energy generation farms which has the potential to serve as an extensive reference for other wave energy farms and offer substantial benefits to both investors and policymakers involved in the advancement of the emerging wave technologies. The suggested method has been employed at the Mutriku Wave Power Plant (WWP) to facilitate the implementation of predictive maintenance strategies and reduce the Levelized Cost of Energy (LCoE). Hence, the research study considers two main extraction methods, namely, Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), used to select the most relevant features for OWC diagnosis. In addition, two classification methods have been considered: Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN). The obtained data show that, although both methods allow to achieve an effective performance with an excellent degree of accuracy, the ANN-based method presents better results with 98% accuracy against 81% for the SVM when using PCA extraction method. Then, the developed classification-based OWC diagnosis has been used for the development of a predictive maintenance strategy at the Mutriku WPP, analyzing its impact on the economic indicators. The results indicate that, using the proposed predictive maintenance strategy, the OpEx may be decreased down to 17%, downtime may be decreased down to 55% and plant availability may be better up to 95%, leading to a 5% LCoE reduction.

Las centrales de aprovechamiento de la energía proveniente de las olas, y particularmente los dispositivos de columna de agua oscilante, resultan una alternativa factible para reducir la dependencia de los combustibles fósiles y frenar el creciente problema del calentamiento global. Así, los nuevos esquemas de control pueden jugar un papel importante a la hora de aportar mejoras de rendimiento y competir de igual a igual desde un punto de vista comercial con las fuentes de energía tradicionales. En este sentido, el presente artículo propone un nuevo método de control basado en el seguimiento de la curva de máxima potencia, mediante el establecimiento de los valores óptimos de los coeficientes de flujo y de par que permiten maximizar la potencia generada en cada instante. El esquema de control ha sido implementado sobre un modelo completo desde la ola hasta la red de potencia a fin de demostrar la viabilidad del método propuesto y la bondad de sus resultados.