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Methods of Numerical Integration

Wide-area monitoring, protection, and control (WAMPAC) involves the use of system-wide information and the communication of selected local information to a remote location to counteract the propagation of large disturbances. Synchronized measurement technology (SMT) is an important element and enabler of WAMPAC. It is expected that WAMPAC systems will in the future reduce the number of catastrophic blackouts and generally improve the reliability and security of energy production, transmission, and distribution, particularly in power networks with a high level of operational uncertainties. In this paper, the technological and application issues are addressed. Several key monitoring, protection, and control applications are described and discussed. A strategy for developing a WAMPAC system in the United Kingdom is given as well.

Wide-Area Monitoring, Protection, and Control of Future Electric Power Networks

Electric load forecasting methods: Tools for decision making

With the increasing use of real-time synchronized phasor measurement units, it is necessary to consider applications of these measurements in greater detail. One of the most natural applications of these measurements is in the area of state estimation. A straightforward application of state estimation theory treats phasor measurements of currents and voltages as additional measurements to be appended to traditional measurements now being used in most energy management system (EMS) state estimators. The resulting state estimator is once again nonlinear and requires significant modifications to existing EMS software. This paper proposes an alternative approach, which leaves the traditional state estimation software in place, and discusses a novel method of incorporating the phasor measurements and the results of the traditional state estimator in a postprocessing linear estimator. This paper presents the underlying theory and provides verification through simulations of the two alternative strategies. It is shown that the new technique provides the same results as the nonlinear state estimator and does not require modification of the existing EMS software

An Alternative for Including Phasor Measurements in State Estimators

As the phasor measurement units (PMUs) start populating the substations, their benefits for different power system application functions are being debated. One of these functions is the bad data processing that is commonly integrated into the state estimation. Bad data detection is closely related to the measurement redundancy in that bad data appearing in critical measurements cannot be detected. Such measurements, however, can be transformed into redundant measurements by adding few PMUs at strategic locations. In this paper, it will be shown that with few extra PMUs, the bad data detection and identification capability of a given system can be drastically improved. Description of the placement algorithm is given, and case studies carried out on different size test systems are presented

Placement of PMUs to Enable Bad Data Detection in State Estimation

This paper presents different aspects of implementation of phasor measurement unit (PMU) technology in power system static state estimation. Various options in the use of PMU measurements in power system state estimation are presented and tested. From the simulation study performed on the IEEE 14-bus test system, it is found that PMU measurements can increase the confidence in the state estimation result. This paper also investigates the possibility of using a new linear state estimation algorithm in parallel with existing the nonlinear estimator. It is shown that this linear estimator has certain advantages. The problem with different angle references of the estimator and angle measurements is investigated and possible solutions are presented.

Implementation of PMU technology in state estimation: an overview

The increased connection of distributed generation (DG), such as photovoltaic (PV) and wind turbine (WT), has shifted the current distribution networks from being passive (consuming energy) into active (consuming/producing energy). However, there is still no consensus about how to determine the maximum amount of DGs that are allowed to be connected, i.e., how to quantify a so-called “hosting capacity” (HC). Therefore, this paper proposes a novel risk assessment tool for estimating network HC by considering uncertainties associated with PV, WT, and loads. This evaluation is performed using the likelihood approximation approach. The paper, also, proposes a utilization of clearness index for localized solar irradiance prediction of PV. In addition, we propose the use of sparse grid technique as an effective means for uncertainty computation while the use of Monte Carlo technique is taken for a comparison purpose. Two actual distribution networks (11-buses and South Australian large feeder) are considered as case studies to demonstrate the usefulness of the proposed tool.

Probabilistic Hosting Capacity for Active Distribution Networks

On-line diagnostics of induction machine faults such as broken rotor bars and shorted stator windings can be accomplished by analysing the anomalies of machine stator current. Defective rotor bars result in twice slip frequency sidebands around the fundamental frequency in the stator current, while stator winding short circuits cause changes in stator current amplitude and the occurrence of negative sequence current. This paper presents an induction machine model based on the Coupled Circuit Approach to simulate both the rotor and stator faults in an induction machine and to test fault diagnostic techniques. This model is realized in Matlab/Simulink and its construction in Simulink is explained with sufficient details. Simulation results of both the rotor and stator fault conditions are presented. A novel high-resolution spectral analysis approach and a technique based on Discrete Fourier Transform (DFT) for the detection of broken rotor bars are tested using the simulated data. The results confirm that the high-resolution method overcomes drawbacks of DFT such as the requirement for long data windows. Copyright © 2009 John Wiley & Sons, Ltd.

Modelling and simulation of stator and rotor fault conditions in induction machines for testing fault diagnostic techniques

Abrupt change detection in power system fault analysis using adaptive whitening filter and wavelet transform

During a fault, protection relays of the faulty line as well as adjacent lines react and record measurement data. The records of an adjacent healthy line can be used for line parameter identification. The special feature of the proposed method is the consideration of unsymmetrical transmission lines and the application of a high-accuracy signal modeling technique. Derived from a π line model, an estimation equation for determining the different impedances is developed. This equation contains the signal models of measurements as well as their time derivatives, which can be estimated very precisely compared to the classical approach based on filtering. By means of a simple simulation model, the accuracy of the proposed algorithm is compared to an approach previously proposed which is based on deconvolution and filtering methods as well as on the representation of a transmission line using time-varying phasors.

Rastko Zivanovic

Papers

Implementation of PMU technology in state estimation: an overview

Probabilistic Hosting Capacity for Active Distribution Networks

Modelling and simulation of stator and rotor fault conditions in induction machines for testing fault diagnostic techniques

Abrupt change detection in power system fault analysis using adaptive whitening filter and wavelet transform

Parameter Identification of Unsymmetrical Transmission Lines Using Fault Records Obtained From Protective Relays