Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output （MIMO） random vibration test. During the control process with the difference control algorithm （DCA）, a lower tri...Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output （MIMO） random vibration test. During the control process with the difference control algorithm （DCA）, a lower triangular matrix is derived from Cholesky decomposition of a reference spectrum matrix. The diagonal elements of the lower triangular matrix （DELTM） may become negative. These negative values have no meaning in physical significance and can cause divergence of auto-power spectrum control. A proportional root mean square control algorithm （PRMSCA） provides another method to avoid the divergence caused by negative values of DELTM, but PRMSCA cannot control the cross-power spectrum. A new control algorithm named matrix power control algorithm （MPCA） is proposed in the paper. MPCA can guarantee that DELTM is always positive in the auto-power spectrum control. MPCA can also control the cross-power spectrum. After these three control algorithms are analyzed, three-input three-output random vibration control tests are implemented on a three-axis vibration shaker. The results show the validity of the proposed MPCA.展开更多
随着电力系统对灵活性资源需求的增加,核电作为一种稳定、可控的清洁能源未来在电力系统中不可避免要承担调峰的任务。在调度需求下,主蒸汽阀门开度的频繁变化对一回路冷却剂平均温度等参数产生了一定程度的扰动,而反应堆冷却剂平均温...随着电力系统对灵活性资源需求的增加,核电作为一种稳定、可控的清洁能源未来在电力系统中不可避免要承担调峰的任务。在调度需求下,主蒸汽阀门开度的频繁变化对一回路冷却剂平均温度等参数产生了一定程度的扰动,而反应堆冷却剂平均温度控制系统中的功率失配通道难以满足快速控制的要求。为了提高堆机协调中反应堆调节的快速响应能力,降低主蒸汽阀门开度变化对一回路冷却剂平均温度等参数的扰动,依据大型压水堆(Pressurized Water Reactor,PWR)核电机组的模型,在传统的R棒控制系统的基础上引入以汽轮机负荷为输入信号的前馈环节。一方面,采用理论推导方法,在合理简化R棒控制系统的基础上,借助梅逊公式精确计算前馈环节传递函数;另一方面,采用粒子群算法,依托MATLAB与Simulink之间数据交互,直接对前馈环节传递函数中的待定参数进行寻优。最后,在80%工况下引入±5%、±10%和±20%的负荷阶跃,仿真结果表明:6种负荷阶跃工况下,理论推导的前馈环节让一回路冷却剂温度和主蒸汽压力调节时间缩短53.7%⁓89.6%,波动降22.8%⁓100%;粒子群优化算法计算的前馈环节使调节时间优化64.4%⁓95.3%,波动降23.4%⁓100%。由两种方法得出的前馈环节引入到R棒控制系统中均能有效大幅提升一回路平均温度与主蒸汽压力的调节速度,降低其波动性。所提出的理论计算方法与粒子群优化算法的结果相近,且具有计算成本低、操作简便的优势,在工程中更具应用价值。展开更多
The objective of this work is the coordinated design of controllers that can enhance damping of power system swings. With presence of flexible AC transmission system （FACTS） device as unified power flow controller ...The objective of this work is the coordinated design of controllers that can enhance damping of power system swings. With presence of flexible AC transmission system （FACTS） device as unified power flow controller （UPFC）, three specific classes of the power system stabilizers （PSSs） have been investigated. The first one is a conventional power system stabilizer （CPSS）; the second one is a dual-input power system stabilizer （dual-input PSS）; and the third one is an accelerating power PSS model （PSS2B）. Dual-input PSS and PSS2B are introduced to maintain the robustness of control performance in a wide range of swing frequency. Uncoordinated PSS and UPFC damping controller may cause unwanted interactions; therefore, the simultaneous coordinated tuning of the controller parameters is needed. The problem of coordi- nated design is formulated as an optimization problem, and particle swarm optimization （PSO） algorithm is employed to search for optimal parameters of controllers. Finally, in a system having a UPFC, comparative analysis of the results obtained from application of the dual-input PSS, PSS2B, and CPSS is presented. The eigenvalue analysis and the time-domain simulation results show that the dual-input PSS ＆ UPFC and the PSS2B ＆ UPFC coordination provide a better performance than the conventional single-input PSS ＆ UPFC coordination. Also, the PSS2B ＆ UPFC coordination has the best performance.展开更多
基金National Natural Science Foundation of China （10972104） The Fundamental Research Funds for NUAA（NS2010007）
文摘Both auto-power spectrum and cross-power spectrum need to be controlled in multi-input multi-output （MIMO） random vibration test. During the control process with the difference control algorithm （DCA）, a lower triangular matrix is derived from Cholesky decomposition of a reference spectrum matrix. The diagonal elements of the lower triangular matrix （DELTM） may become negative. These negative values have no meaning in physical significance and can cause divergence of auto-power spectrum control. A proportional root mean square control algorithm （PRMSCA） provides another method to avoid the divergence caused by negative values of DELTM, but PRMSCA cannot control the cross-power spectrum. A new control algorithm named matrix power control algorithm （MPCA） is proposed in the paper. MPCA can guarantee that DELTM is always positive in the auto-power spectrum control. MPCA can also control the cross-power spectrum. After these three control algorithms are analyzed, three-input three-output random vibration control tests are implemented on a three-axis vibration shaker. The results show the validity of the proposed MPCA.
文摘随着电力系统对灵活性资源需求的增加,核电作为一种稳定、可控的清洁能源未来在电力系统中不可避免要承担调峰的任务。在调度需求下,主蒸汽阀门开度的频繁变化对一回路冷却剂平均温度等参数产生了一定程度的扰动,而反应堆冷却剂平均温度控制系统中的功率失配通道难以满足快速控制的要求。为了提高堆机协调中反应堆调节的快速响应能力,降低主蒸汽阀门开度变化对一回路冷却剂平均温度等参数的扰动,依据大型压水堆(Pressurized Water Reactor,PWR)核电机组的模型,在传统的R棒控制系统的基础上引入以汽轮机负荷为输入信号的前馈环节。一方面,采用理论推导方法,在合理简化R棒控制系统的基础上,借助梅逊公式精确计算前馈环节传递函数;另一方面,采用粒子群算法,依托MATLAB与Simulink之间数据交互,直接对前馈环节传递函数中的待定参数进行寻优。最后,在80%工况下引入±5%、±10%和±20%的负荷阶跃,仿真结果表明:6种负荷阶跃工况下,理论推导的前馈环节让一回路冷却剂温度和主蒸汽压力调节时间缩短53.7%⁓89.6%,波动降22.8%⁓100%;粒子群优化算法计算的前馈环节使调节时间优化64.4%⁓95.3%,波动降23.4%⁓100%。由两种方法得出的前馈环节引入到R棒控制系统中均能有效大幅提升一回路平均温度与主蒸汽压力的调节速度,降低其波动性。所提出的理论计算方法与粒子群优化算法的结果相近,且具有计算成本低、操作简便的优势,在工程中更具应用价值。
文摘The objective of this work is the coordinated design of controllers that can enhance damping of power system swings. With presence of flexible AC transmission system （FACTS） device as unified power flow controller （UPFC）, three specific classes of the power system stabilizers （PSSs） have been investigated. The first one is a conventional power system stabilizer （CPSS）; the second one is a dual-input power system stabilizer （dual-input PSS）; and the third one is an accelerating power PSS model （PSS2B）. Dual-input PSS and PSS2B are introduced to maintain the robustness of control performance in a wide range of swing frequency. Uncoordinated PSS and UPFC damping controller may cause unwanted interactions; therefore, the simultaneous coordinated tuning of the controller parameters is needed. The problem of coordi- nated design is formulated as an optimization problem, and particle swarm optimization （PSO） algorithm is employed to search for optimal parameters of controllers. Finally, in a system having a UPFC, comparative analysis of the results obtained from application of the dual-input PSS, PSS2B, and CPSS is presented. The eigenvalue analysis and the time-domain simulation results show that the dual-input PSS ＆ UPFC and the PSS2B ＆ UPFC coordination provide a better performance than the conventional single-input PSS ＆ UPFC coordination. Also, the PSS2B ＆ UPFC coordination has the best performance.
