Adaptive power management strategies for arrays of oscillating water column wave energy converters.

适用于振荡水柱波浪能转换器阵列的自适应功率管理策略。

• 批准号: 2582473
• 金额: --
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2582473
• 关键词: Adaptive; power; management; strategies; arrays

The aim of this project is to develop a novel framework of optimal and adaptive control strategies for large arrays of oscillating water columns (OWC) that can guarantee maximum power on the one hand, and minimum power oscillation on the other. The framework will combine multi-objective optimisation with adaptive learning algorithms. First, we will analyse the response of OWC networks to different sea states and wave conditions. Second, we will build a combined individual (distributed) and central (supervisory) control architecture. Distributed optimal control strategies for the turbine and generator configurations will be integrated into a supervisory adaptive control network to address the two control objectives: (a) optimising power generation of individual OWCs while adaptively establishing a power phase shift regime for the OWC array to reduce overall power oscillation; (b) robust operation via adaptive learning algorithms to track modelling uncertainties and disturbances.

该项目的目的是开发一种新的框架的最优和自适应控制策略的大型阵列振荡水柱（OWC），一方面可以保证最大功率，另一方面最小功率振荡。该框架将联合收割机多目标优化与自适应学习算法相结合。首先，我们将分析OWC网络对不同海况和波浪条件的响应。第二，我们将建立一个组合的个人（分布式）和中央（监督）控制架构。涡轮机和发电机配置的分布式最优控制策略将被集成到一个监督自适应控制网络中，以解决两个控制目标：（a）优化单个OWC的发电，同时自适应地为OWC阵列建立功率相移机制，以减少总体功率振荡;（B）通过自适应学习算法进行鲁棒运行，以跟踪建模不确定性和干扰。