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A Pricing-based Game Theoretic Framework for Distributed-MPC in Voltage Stabilization

机译:基于定价的分布式MPC的游戏理论框架,电压稳定

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A pricing based game theoretic approach of distributed model predictive control (MPC), suitable for controlling voltage instability in power systems, is devloped and presented. MPC is a promising technique in power system control, but its centralized implementation is computationally expensive for real-time application. A non-cooperative distributed-MPC framework is a computationally viable alternative. However in such framework, distributed agents acting selfishly optimize own utility functions, attaining a Nash equilibrium, which in general is less efficient with respect to the global cost/utility function of a dynamically coupled system. A cooperative alternative to this scheme distributively optimizes the global cost, but with an increase in computational complexity by a factor equal to the number of buses. In this paper, we introduce a pricing scheme to incentivize agents’ individual utility functions in an iterative manner, improving the efficiency of non-cooperative Nash-equilibrium and attaining results comparable to global optimal of the centralized case. Additionally, to design the distributed-MPC framework, a distributed time domain simulation as well as trajectory sensitivity estimation framework, considering bus level decomposition, is developed and provided. Trajectory sensitivity supports linearization around a trajectory, attaining an accurate approximation of nonlinear dynamics. Finally, the efficacy of the proposed scheme is validated using the WECC 9 bus test system.
机译:一种基于定价的分布式模型预测控制(MPC)的游戏理论方法,适用于控制电力系统中的电压不稳定,具有揭示和呈现。 MPC是电力系统控制中有希望的技术,但其集中实施是对实时应用的计算昂贵。非合作分布式MPC框架是计算上可行的替代方案。然而,在这种框架中,作用自私优化自己的实用功能的分布式代理,达到了纳什均衡,这通常对动态耦合系统的全球成本/实用功能效率较低。该方案的合作替代方案分布地优化了全局成本,但随着等于总线数量的因素,计算复杂性增加。在本文中,我们介绍了一种定价方案,以迭代方式激励代理的个人实用功能,提高非合作纳什平衡的效率,并获得与集中案件的全局最优相当的结果。另外,为了设计分布式MPC框架,开发并提供了考虑总线分解的分布式时域仿真以及轨迹敏感性估计框架。轨迹敏感性支持轨迹周围的线性化,达到非线性动力学的准确近似。最后,使用WECC 9总线测试系统验证了所提出的方案的功效。

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