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Nonlinear Model Predictive Control of a Variable-Speed Pumped-Storage Power Plant

机译:变速泵送电厂的非线性模型预测控制

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摘要

Optimal operation and control of (variable-speed) pumped-storage power plants (PSPPs) is essential to meet the growing demands on the dynamics for the stabilization of power distribution grids with an increasing amount of renewable energy sources. Existing work on the control of PSPPs is typically based on rather simplified system models, in particular of the (long) pipeline system. In this article, a nonlinear model predictive control (NMPC) strategy is proposed, which enables fast closed-loop dynamics while keeping all system constraints, including the pressure constraints along the pipeline system. The control strategy is based on a physics-based model, which enables easy parameterization and application to other plant sizes or topologies. To ensure real-time capability of the model predictive control (MPC) strategy, a number of measures are outlined in this article. Finally, the feasibility of the proposed control strategy is demonstrated by detailed simulation studies. An accurate tracking for fast changing desired grid powers as well as a high robustness with respect to parameter uncertainties is demonstrated.
机译:(可变速度)泵送存储发电厂(PSPP)的最佳运行和控制对于满足对动力量的需求不断增长,以越来越多的可再生能源。对PSPP的控制的现有工作通常基于相当简化的系统模型,特别是(长)管​​道系统。在本文中,提出了一种非线性模型预测控制(NMPC)策略,其在保持所有系统约束的同时实现快速闭环动态,包括沿着管道系统的压力约束。控制策略基于基于物理的模型,它可以轻松地参数化和应用于其他植物尺寸或拓扑。为确保模型预测控制(MPC)策略的实时能力,本文概述了许多措施。最后,通过详细的仿真研究证明了所提出的控制策略的可行性。对快速改变所需的电网功率以及相对于参数不确定性的高稳健性进行准确跟踪。

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