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Analysis of coupling dynamics for power systems with iterative discrete decision making architectures

机译:具有迭代离散决策架构的电力系统耦合动力学分析

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摘要

Iterative "learning" by distributed control agents has been proposed for power system decision making. Such decision making can achieve agreement among control agents while preserving privacy. The iterative decision making process may interact with power system dynamics. In such cases, coupled dynamics are expected. The objective of this paper is to propose a modeling approach that can conduct stability analysis for these hybrid systems. In the proposed approach, the discrete decision making process is approximated by continuous dynamics. As a result, the entire hybrid system can be represented by a continuous dynamic system. Conventional stability analysis tools are then used to check system stability and identify key impacting factors. An example power system with multiple control agents is used to demonstrate the proposed modeling and analysis. The analysis results are then validated by nonlinear time-domain simulation.
机译:已经提出了分布式控制代理的迭代“学习”以用于电力系统决策。这样的决策可以在控制代理之间达成协议,同时又可以保护隐私。迭代决策过程可以与电力系统动力学相互作用。在这种情况下,会产生耦合动力学。本文的目的是提出一种可以对这些混合系统进行稳定性分析的建模方法。在所提出的方法中,离散决策过程通过连续动力学来近似。结果,整个混合系统可以由连续动态系统表示。然后使用常规的稳定性分析工具来检查系统稳定性并确定关键的影响因素。具有多个控制代理的示例电源系统用于演示所提出的建模和分析。然后通过非线性时域仿真验证分析结果。

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