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This paper presents a method for processing real-time data error in generalized state estimation (GSE). Attention is focused on the two main types of error: network topology errors and bad data on analog measurements. The proposed approach is able to handle both errors without making any previous assumption regarding the nature of those errors. The degrading effects of topology errors over bad data processing when both topology and measurement errors occur at the same time are evaluated and new strategy is proposed to overcome it. GSE is treated as a constrained optimization problem where measurements and circuit-breaker status are modeled as equality constraints. Geometric tests based on the geometric interpretation of the Lagrange multiplier vector are then utilized to determine the source of the error. The proposed strategy is tested on two model power networks represented at the bus-section level which is derived from the IEEE 30-bus and 118-bus systems. [ABSTRACT FROM PUBLISHER]

This paper proposes a generalized approach of the per unit normalization, named complex per unit normalization (cpu), to improve the performance of fast decoupled power flow methods applied to emerging distribution networks. The proposed approach takes into account the changes envisaged and also already faced by distribution systems, such as high penetration of generation sources and more interconnection between feeders, while considering the typical characteristics of distribution systems, as the high R/X ratios. These characteristics impose difficulties on the performance of both backward-forward sweep and decoupled-based power flow methods. The cpu concept is centred on the use of a complex volt-ampere base, which overcomes the numerical problems raised by the high R/X ratios of distribution feeders. As a consequence, decoupled power flow methods can be efficiently applied to distribution system analysis. The performance of the proposed technique and the simplicity of adapting it to existing power flow programs are addressed in the paper. Different distribution network configurations and load conditions have been used to illustrate and evaluate the use of cpu. [ABSTRACT FROM PUBLISHER]

The ferroresonance phenomena in electrical power systems can cause very important quality and security problems. Although it has been extensively analyzed with different approaches since the birth of electrical systems, it still remains a challenge due the complexity of factors that can lead to the phenomenon. In this paper, a scalar Jiles-Atherton (JA) hysteresis model is applied to model a nonlinear ferromagnetic core allowing to analyze magnetic circuits, which can be in ferroresonant mode. It is used an inverse JA approach, which had originally the magnetic induction as its independent variable. The analysis here proposed applies a flux-current methodology to obtain a hysteresis behavior of a nonlinear inductor. [ABSTRACT FROM AUTHOR]

Presents a study that extended graph theoretic observability algorithms to make them capable of processing switching branches. Background on the classical topological observability theory; Changes in the conventional network observability algorithms; Simulation results and practical applications.