电力系统多区域分布式状态估计方法

提出了一种电力系统多区域分布式状态估计方法,各区域估计器利用其数据采集与监视控制系统提供的量测数据进行本地状态估计,并通过平均一致性算法获取全局信息进行系统级状态估计。建立了基于拉格朗日乘子法的状态估计模型并设计了基于一致性的全局信息交换协议,给出了多区域分布式状态估计算法的实现流程。通过IEEE 14节点和118节点系统中的仿真算例验证了所提方法的正确性和有效性,并就估计精度和计算效率与现有状态估计方法进行了比较。仿真结果表明分布式状态估计方法可有效提高集中式状态估计系统的计算效率及可靠性,适用于结构更加复杂、量测数据体量更大电网的状态估计。

Multi-area distributed state estimation method for power system

A multi-area distributed state estimation method for power systems is proposed. Each area estimator performs local state estimation using the data provided by its supervisory control and data acquisition system, and obtains the global information through average consensus algorithm for system-level state estimation. The state estimation model based on Lagrange multiplier method is established and a global information exchange protocol based on consensus is developed. The implementation flow of multi-area distributed state estimation algorithm is presented. The correctness and effectiveness of the proposed method are verified by simulation examples in IEEE 14-bus and 118-bus systems. The estimation accuracy and computational efficiency are compared with the existing estimation methods. The simulative results show that distributed state estimation method can effectively improve the low computational efficiency and poor reliability of centralized state estimation system, and is more suitable for the state estimation of power grids with more complex structures and larger quantity of measurement data.