The Accuracy Evaluation of State Estimation in Smart Power Grids

State estimation (SE) is the main function of energy management system (EMS) in smart grids (SG) integrated with renewable resources. Therefore, it is very important to evaluate the accuracy of SE results for efficient EMS. The SE problem of power system can be formulated by several techniques. The most common technique is the weighted least squares (WLS). The introduction of synchronized phasor measurement units (PMU) to SGs has greatly enhanced the SE of the system state variables. In this paper, four accuracy indexes are addressed, namely, mean absolute estimated error (MAE), mean squares error (MSE), longest common sequence (LCS) and Gaussian kernel (Correntropy (COE)). These indexes are used to evaluate the accuracy of two types of estimator; conventional WLS based estimator and a hybrid state estimator consists of WLS and PMU.