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Sea trial results of a predictive algorithm at the Mutriku Wave power plant and controllers assessment based on a detailed plant model

机译:Mutriku Wave电厂预测算法的海试结果和基于详细电厂模型的控制器评估

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Improving the power production in wave energy plants is essential to lower the cost of energy production from this type of installations. Oscillating Water Column is among the most studied technologies to convert the wave energy into a useful electrical one. In this paper, three control algorithms are developed to control the biradial turbine installed in the Mutriku Wave Power Plant. The work presents a comparison of their main advantages and drawbacks first from numerical simulation results and then with practical implementation in the real plant, analysing both performance and power integration into the grid. The wave-to-wire model used to develop and assess the controllers is based on linear wave theory and adjusted with operational data measured at the plant. Three different controllers which use the generator torque as manipulated variable are considered. Two of them are adaptive controllers and the other one is a nonlinear Model Predictive Control (MPC) algorithm which uses information about the future waves to compute the control actions. The best adaptive controller and the predictive one are then tested experimentally in the real power plant of Mutriku, and the performance analysis is completed with operational results. A real time sensor installed in front of the plant gives information on the incoming waves used by the predictive algorithm. Operational data are collected during a two-week testing period, enabling a thorough comparison. An overall increase over 30% in the electrical power production is obtained with the predictive control law in comparison with the reference adaptive controller. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
机译:改善波浪能发电厂的电力生产对于降低此类装置的能源生产成本至关重要。振荡水柱是研究最多的技术之一,可将波能转换为有用的电波。在本文中,开发了三种控制算法来控制安装在Mutriku Wave Power Plant中的双径向涡轮机。这项工作首先从数值模拟结果中提出了它们的主要优缺点,然后在实际工厂中进行了实际实施,对性能和向电网的功率集成进行了分析。用于开发和评估控制器的波线模型基于线性波理论,并根据工厂测得的运行数据进行了调整。考虑了使用发电机转矩作为调节变量的三种不同的控制器。其中两个是自适应控制器,另一个是非线性模型预测控制(MPC)算法,该算法使用有关未来波浪的信息来计算控制动作。然后,在Mutriku的实际发电厂中对最佳自适应控制器和预测控制器进行实验测试,并通过运行结果完成性能分析。安装在工厂前部的实时传感器可提供有关预测算法使用的入射波的信息。在为期两周的测试期间内收集了运行数据,从而可以进行全面比较。与参考自适应控制器相比,通过预测控制定律可实现总发电量增加30%以上。 (C)2019作者。由Elsevier Ltd.发布。这是CC BY许可下的开放访问文章(http://creativecommons.org/licenses/by/4.0/)。

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