论文标题
具有太阳能农场和动态负载的多机电源网络的强大动态状态估计
Robust Dynamic State Estimation of Multi-Machine Power Networks with Solar Farms and Dynamics Loads
论文作者
论文摘要
电网的常规状态估计惯例主要依赖于化石燃料资源的动态模型。这些模型通常包含描述同步发电机模型和代数方程建模功率流/平衡方程的微分方程。因此，由无惯性的可再生能源驱动的无燃料电源系统将需要新的型号和升级的估计例程。为此，在本文中，我们为由全面的第九阶同步发电机模型，高级电力电子设备组成的电力网络的互连模型提出了一个可靠的估计器，用于光伏电厂（PV）发电厂，恒定功率载荷，恒定的障碍物载荷和电动机负载。提出的状态估计器设计基于非线性差分代数方程（DAE）模型的Lyapunov稳定性标准，并作为凸半定义优化问题提出。已经对IEEE-39总线测试系统进行了彻底的仿真研究，以展示拟议估计量的鲁棒性，以防止负载需求和太阳辐照度不确定的不确定性。
Conventional state estimation routines of electrical grids are mainly reliant on dynamic models of fossil fuel-based resources. These models commonly contain differential equations describing synchronous generator models and algebraic equations modeling power flow/balance equations. Fuel-free power systems that are driven by inertia-less renewable energy resources will hence require new models and upgraded estimation routines. To that end, in this paper we propose a robust estimator for an interconnected model of power networks comprised of a comprehensive ninth order synchronous generator model, advanced power electronics-based models for photovoltaic (PV) power plants, constant power loads, constant impedance loads, and motor loads. The presented state estimator design is based on Lyapunov stability criteria for nonlinear differential algebraic equation (DAE) models and is posed as a convex semi-definite optimization problem. Thorough simulations studies have been carried out on IEEE-39 bus test system to showcase the robustness of the proposed estimator against unknown uncertainty from load demand and solar irradiance.
