Decoupling Power System State Estimation by Means of Stochastic Collocation

This paper presents a new approach to the problem of system decoupling in a power-system state estimation problem. The complexity of power systems is growing, thus challenging the way measurements for state estimation are traditionally managed. Following a previous experience in defining a decentralized solution for state estimation, the authors here propose a decentralized dynamic state estimation method for a large-scale power system in combination with a procedure to automatically identify how and which state information to exchange for reconstructing the states starting from partial knowledge. In particular, the problem of selecting the variables that each observer has to estimate is partially solved within the framework of a stochastic approach, i.e., the so-called collocation method. An optimization algorithm based on dynamic programming is also developed to determine the optimal set of strongly coupled variables necessary for a sufficiently accurate estimation. The developed method is evaluated by applying to an IEEE test bus system.