The art of estimating future values of a random process, based upon previously observed or
estimated values, is usually known as a priori estimation, prediction, or forecasting. Power …

A new method for topology identification, bad data detection and state estimation (SE) is
proposed in this paper. The method utilizes fuzzy clustering and pattern matching for this …

This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow
(OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units …

The correct assessment of network topology and system operating state in the presence of
corrupted data is one of the most challenging problems during real-time power system …

This article proposes a new algorithm for forecasting‐aided state estimation based on the
cubature Kalman filter (CKF) and new methods for detecting and identifying data anomalies …

This paper presents a new method for solving bad data acquisition problems in power
system state estimation. The normalized innovations, available in the pre-filtering stage of a …

The paper deals with power system topology verification. The correct model of a power
system topology is essential for different power system applications. There are different …

Systematic approach for pre-filter for state estimation based on wavelet analysis to detect
and eliminate bad data, is developed in this work. Unbiased (random/Gaussian) bad data …

Bad data identification is one of the most important and complex problems to be addressed
during power system state estimation, particularly when both analogical and topological …

Accurate dynamic load models allow more precise calculations of power system controls
and stability limits. System identification methods can be applied to estimate load models …