State Estimation of the Nigerian 330kv Transmission Network using the Weighted Least Square Optimization Technique

The state of an electrical power system is the vector of voltage magnitudes and voltage angles at each bus across the entire power system network. The estimates of state variables are very important for online monitoring and control, which are valuable assets in power system operations. The state estimator algorithm is a computational mathematical implementation of a state space technique to process erroneous power system measurements into an estimate of the true power system state vector. It is established, through rigorous research that measurement data obtained from supervisory control and data acquistory systems or Phasor measurement unit are not fit for direct system analysis as they contain errors large enough to give a misrepresentation of the system behavior. To address the issue of erroneous data measurements, this work uses the optimized weighted least square technique to estimate the true state of the power system network. This analysis is achieved by setting up mathematical models of the system network and applying the Weighted Least Square estimation technique to different weights depending on type of measurement. A quantitative and qualitative problem of system observability and error detection in measurement is discussed in this paper. The observability and error quantification process is carried out on the IEEE 14 and the Nigerian transmission grid network through the segmentation of observable islands within the network. This work generates important state results using the MATLAB computational software and run state estimate simulations using the PSAT framework. Using the estimation technique in this work the Nigerian network state space estimation results revealed errors embedded in measurement data with a significant deviation of 1.14 of maximum voltage error in comparison with state estimate result and 16% deviation mean of voltage estimation error in comparison with raw measurement data. The deviation between the raw measurement data and the state estimation results depicts that analysis of power networks without applying that state estimation algorithm may give a misinterpretation of the state variables.           &nbsp