基于特征灵敏度的兆瓦重调度,利用DE增强电压安全性

Pushpendra Singh, L. S. Titare, L. Arya
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引用次数: 1

摘要

本文提出了一种基于特征灵敏度计算稳定性约束的基于DE技术的兆瓦级发电重调度提高电压稳定裕度的方法。如果无功功率控制变量耗尽,则使用有功功率控制变量来提高静态电压稳定极限。在强应力条件下,有功功率控制变量与电压幅值耦合,避免了系统出现电压崩溃问题。选取潮流雅可比矩阵的最小特征值作为接近指标。采用连续潮流法求出潮流雅可比矩阵的最小特征值。利用差分进化方法对负荷流雅可比矩阵的最小特征值进行了优化。该算法不仅考虑了当前运行条件下(有功发电重调度后)的不等式约束,而且考虑了预测的下一个区间发电(有功发电重调度后)的不等式约束。该方法已在ieee6总线测试系统上实现。并与遗传算法(GA)和基于统计推理的梯度搜索(GS)技术进行了性能比较。仿真结果表明,该方法对有功发电重调度具有较好的缓解作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MW-rescheduling based on eigen sensitivities to enhance voltage security using DE
This paper proposes a methodology for enhancement of voltage stability margin by rescheduling of MW generation based on eigen sensitivity accounting stability constraints using DE technique. If the reactive power controls variables are exhausted, then active power controls variables are used to enhance static voltage stability limits. Under heavily stressed condition active power control variables are coupled with the voltage magnitude and system is protected from voltage collapse problem. Minimum eigen value of load flow Jacobian is selected as a proximity indicator. Minimum eigen value of load flow Jacobian is obtained using continuation power flow method. Minimum eigen value of load flow Jacobian has been optimized using Differential Evolution (DE). Developed algorithm accounts inequality constraints not only in present operating conditions (after active power generation rescheduling) but also for predicted next interval generation (with active power generation rescheduling). Proposed methodology has been implemented on IEEE 6-bus test system. Performance of the DE has been compared with Genetic Algorithm (GA) and Gradient Search (GS) technique based on statistical inference. Simulation results have been obtained which confirm that the proposed methodology provide considerable mitigation in the active power generation rescheduling.
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