Introduction to State Estimation in Power System

Introduction to State Estimation in Power System:

Introduction to State Estimation in Power System plays a very important role in the monitoring and control of modem power systems. As in case of load flow analysis, the aim of State Estimation in Power System is to obtain the best possible values of the bus voltage magnitudes and angles by processing the available network data.

Two modifications are, however, introduced now in order to achieve a higher degree of accuracy of the solution at the cost of some additional computations. First, it is recognized that the numerical values of the data to be processed for the state estimation are generally noisy due to the errors present. Second, it is noted that there are a larger number of variables in the system (e.g. P, Q line flows) which can be measured but are not utilized in the load flow analysis. Thus, the process involves imperfect measurements that are redundant and the process of estimating the system states is based on a statistical criterion that estimates the true value of the state variables to minimize or maximize the selected criterion.

A well known and commonly used criterion is that of minimizing the sum of the squares of the differences between the estimated and “true” (i.e. measured) values of a function.

Most State Estimation in Power System programs in practical use are formulated as over determined systems of non-linear equations and solved as weighted least-squares (WLS) problems.

State estimators may be both static and dynamic. Both have been developed for power systems. This chapter will introduce the basic principles of a static-state estimator.

In a power system, the state variables are the voltage magnitudes and phase angles at the buses. The inputs to an estimator are imperfect (noisy) power system measurements. The estimator is designed to give the “best estimate” of the system voltage and phase angles keeping in mind that there are errors in the measured quantities and that there may be redundant measurements. The output data are then used at the energy control centres for carrying out several real-time or on-line system studies such as economic dispatch, security analysis.

Updated: March 29, 2020 — 12:48 pm