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Modeling of a Hydrogen Storage Wind Plant for Model Predictive Control Management Strategies

机译:用于模型预测控制管理策略的储氢风电厂模型

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The intermittent nature of wind energy combined with the penalty deviations adopted in several electricity regulation markets explains the difficulty of this clean energy in playing a major role in the energy system. Coupling the wind farm with advanced energy storage systems represents, in principle, a good solution for these problems. To date, several researches have been conducted on storage technology, but the problem of finding the best ESS solution is still open. Indeed, every storage technology has its own constraints and limitations in terms of capital cost, response time, operational, maintenance and degradation issues. This highlights the importance of advanced control algorithms for energy storage management systems to mitigate the problems outlined. In this paper, we model a hydrogen-based energy storage system in terms of operating constraints and cost/degradation features. Via a MPC based controller and mixed-integer linear constraints and dynamics, we address the problem of satisfying a forecasted power demand. The paper collects the preliminary ideas for the EU-FCH 2 JU (European Union Fuel Cells and Hydrogen 2 Joint Undertaking) founded project HAEOLUS aiming at building and integrating advanced control strategies for a hydrogen based ESS within a wind farm fence. Numerical simulations corroborate the feasibility and the effectiveness of the proposed approach.
机译:风能的间歇性加上几个电力监管市场所采用的罚款偏差,说明了这种清洁能源难以在能源系统中发挥重要作用。原则上,将风电场与先进的储能系统耦合在一起,可以很好地解决这些问题。迄今为止,已经对存储技术进行了一些研究,但是寻找最佳ESS解决方案的问题仍然悬而未决。实际上,每种存储技术在资金成本,响应时间,操作,维护和降级问题方面都有其自身的约束和限制。这凸显了先进的控制算法对储能管理系统缓解所概述问题的重要性。在本文中,我们根据操作约束和成本/降解特性对基于氢的储能系统进行建模。通过基于MPC的控制器以及混合整数线性约束和动力学,我们解决了满足预测的功率需求的问题。本文收集了EU-FCH 2 JU(欧盟燃料电池和氢2联合事业)成立的项目HAEOLUS的初步构想,该项目旨在建立和整合风电场围网中基于氢的ESS的高级控制策略。数值模拟证实了该方法的可行性和有效性。

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