A Distributed State Estimation Approach to Condition Monitoring of Nonlinear Electric Power Systems

作者：Rigatos G^*; Siano P; Zervos N

来源：Asian Journal of Control, 2013, 15(3): 849-860.

DOI：10.1002/asjc.562

• Extended information filter
• unscented information filter
• distributed state estimation
• condition monitoring
• nonlinear electric power systems

This paper analyzes distributed state estimation methods for condition monitoring of electric power transmission and distribution systems. When a fault occurs in such large-scale systems, it is usually difficult to detect it and to determine its exact position. Moreover, due to the cost of installation and maintenance of measurement devices and due to the excessive size of the electric power grid, the complete monitoring of the associated infrastructure is impractical. Therefore, to monitor the condition of the power grid, some form of estimation is required. As suitable approaches for distributed state estimation this paper proposes the extended information filter (EIF) and the unscented information filter (UIF). The Extended Information Filter is actually an implementation of distributed extended Kalman filtering while the unscented information filter is an implementation of distributed unscented Kalman filtering. With the use of the aforementioned filtering algorithms on processing units located at different parts of the power grid, one can produce local estimates of the system%26apos;s state vector which in turn can be fused into an aggregate state estimation. The produced global state estimate enables continuous monitoring of the condition of the electric power system and early fault diagnosis if used by a suitable fault detection and isolation algorithm.

• 出版日期2013-5