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Distributed Supervisory Predictive Control of Distributed Wind and Solar Energy Systems

机译:分布式风能和太阳能系统的分布式监督预测控制

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In this work, we design a distributed supervisory model predictive control (MPC) system for optimal management and operation of distributed wind and solar energy generation systems integrated into the electrical grid to facilitate the development of the so-called “smart electrical grid”. We consider a topology in which two spatially distributed energy generation systems, a wind subsystem and a solar subsystem, are integrated in a DC power grid, providing electrical power to a local area, and each subsystem is coupled with an energy storage device. A supervisory MPC optimization problem is first formulated to take into account optimality considerations on system operation and battery maintenance; then a sequential and an iterative distributed supervisory MPC architectures are developed to coordinate the actions of the subsystems accordingly. Simulations of 24-hour system operation are carried out under the different control architectures to demonstrate the applicability and effectiveness of the distributed supervisory predictive control design.
机译:在这项工作中,我们设计了一种分布式监督模型预测控制(MPC)系统,用于优化管理和运行集成到电网中的分布式风能和太阳能发电系统,以促进所谓的“智能电网”的发展。我们考虑一种拓扑结构,其中将两个空间分布的能量生成系统(风子系统和太阳能子系统)集成到DC电网中,向局部区域提供电能,并且每个子系统都与一个储能设备耦合。首先制定监督性MPC优化问题,以考虑系统操作和电池维护的最佳化考虑;然后开发了顺序和迭代的分布式管理MPC架构,以相应地协调子系统的操作。在不同的控制架构下对24小时系统运行进行了仿真,以证明分布式监控预测控制设计的适用性和有效性。

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