基于最小控制综合算法的多机电力系统分散自适应稳定器

P. Doraraju, R. K. Nondy
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引用次数: 4

摘要

本文提出了一种基于最小控制综合算法的多机电力系统分散自适应镇定新方法。该控制器采用比例加积分型自适应来满足系统参数变化的超稳定条件。在每台机器的激励输入处合成稳定信号,以满足参考模型规定的期望系统性能。选择参考模型参数以获得定义良好的闭环性能。最后给出了系统稳定性的保证。提出的自适应控制方案避免了满足Erzberger模型匹配条件的困难和实现在线参数估计器的负担。总之,超稳定性保证了机器在扰动作用下的渐近稳定性。给出了多机电力系统的仿真结果,结果表明该控制器在系统参数变化和不同干扰下都能很好地工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A decentralized adaptive stabilizer based on minimal control synthesis algorithm for a multi-machine power system
In this paper, a new approach to decentralized adaptive stabilization using a minimal control synthesis algorithm for a multimachine power system is proposed. This controller uses proportional plus integral type adaptation to satisfy the hyperstability conditions for taking care of parameter changes of the system. The stabilization signals are synthesized at the excitation input of each machine such that desired system performance as specified in terms of reference model are satisfied. The reference model parameters are chosen to elicit a well defined closed loop performance. A guarantee of stability to the overall system is also presented. The proposed adaptive control scheme avoids the difficulty of satisfying the Erzberger's model matching conditions and the burden of implementing an online parameter estimator. Above all, the hyperstability guarantees asymptotical stability of the machines under a disturbance. Simulation results of a multi-machine power system are presented which show that the controller works well under system parameter changes and with different disturbances.
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