论文标题
动力网络和同步发电机的移动型状态估计
Moving-Horizon State Estimation for Power Networks and Synchronous Generators
论文作者
论文摘要
电力网络和发电机状态估计通常被视为单独的问题。我们提出了一个动态方案，以同时估计网络和发电机状态。该估计是在过去观测值的移动马上提出的优化问题。该框架是静态状态估计的概括。它可以处理不完整的模型知识，并且不需要PMU的静态网络可观察性。与静态状态估计相比，数值结果表明估计精度提高了。此外，可以实现对发电机内部状态的准确估计，而无需在其终端上进行PMU。最后，我们强调了所提出的估计器检测和识别不良数据的能力。
Power network and generators state estimation are usually tackled as separate problems. We propose a dynamic scheme for the simultaneous estimation of the network and the generator states. The estimation is formulated as an optimization problem on a moving-horizon of past observations. The framework is a generalization of static state estimation; it can handle incomplete model knowledge and does not require static network observability by PMUs. The numerical results show an improved estimation accuracy compared to static state estimation. Moreover, accurate estimation of the internal states of generators without PMUs on their terminals can be achieved. Finally, we highlight the capability of the proposed estimator to detect and identify bad data.
