Wide-Area Damping Control Using Multiple DFIG-Based Wind Farms Under Stochastic Data Packet Dropouts
Wide-Area Damping Control Using Multiple DFIG-Based Wind Farms Under Stochastic Data Packet Dropouts
复制标题
DOI：
10.1109/tsg.2016.2631448
复制
发表时间：
2018-07
影响因子：
9.6
通讯作者：
Amirthagunaraj Yogarathinam;N. Chaudhuri
中科院分区：
文献类型：
--
作者：
Amirthagunaraj Yogarathinam;N. Chaudhuri
在大规模部署分布式和网络化相量测量单元和风能资源的智能电网中，通信网络中的数据丢失会对广域振荡阻尼控制产生重大影响。通过通信信道发送的远程反馈信号会遇到数据丢失，这由Gilbert-Elliott模型表示。提出了一种基于降维驱动的降维拷贝（ORC）方法，该方法利用数据丢失时系统标称动态特性的知识来改善传统反馈会受到影响的阻尼性能。还推导了由于数据丢失引起的网络系统和由于操作条件变化引起的物理系统中的不确定性的实际和估计状态之间的误差范数上的界的期望的表达式。关键的贡献来自网络和物理层之间的耦合对ORC性能的影响的分析推导。通过蒙特卡罗模拟计算了误差界的离散度。非线性时域仿真表明，ORC产生显着更好的性能相比，传统的反馈在较高的数据丢失的情况下。
Data dropouts in communication network can have a significant impact on wide-area oscillation damping control of a smart power grid with large-scale deployment of distributed and networked phasor measurement units and wind energy resources. Remote feedback signals sent through communication channels encounter data dropout, which is represented by the Gilbert-Elliott model. An observer-driven reduced copy (ORC) approach is presented, which uses the knowledge of the nominal system dynamics during data dropouts to improve the damping performance where conventional feedback would suffer. An expression for the expectation of the bound on the error norm between the actual and the estimated states relating uncertainties in the cyber system due to data dropout and physical system due to change in operating conditions is also derived. The key contribution comes from the analytical derivation of the impact of coupling between the cyber and the physical layer on ORC performance. Monte Carlo simulation is performed to calculate the dispersion of the error bound. Nonlinear time-domain simulations demonstrate that the ORC produces significantly better performance compared to conventional feedback under higher data drop situations.