A Flexible DSTATCOM Operating in Voltage or Current Control Mode

The topology and control are discussed of a distribution static compensator (DSTATCOM) that can be operated flexibly in the voltage or current control mode. In the voltage control mode, the DSTATCOM can force the voltage of a distribution bus to be balanced sinusoids. In the current control mode, it can cancel distortion caused by the load, such that current drawn by the compensated load is pure balanced sinusoid. Both these objectives are achieved, irrespective of unbalance and harmonic distortions in load currents or source voltages. The chosen DSTATCOM topology includes three single-phase voltage source inverters connected in parallel to a filter-capacitor, which allows the high-frequency component of the current to pass. A switching control scheme is proposed, and its suitability is proved for this problem. The proposed scheme is verified using computer simulation studie

Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System

Abstract—This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN. Keywor ds —Dynamic voltage collapse, prediction, artificial neural network, support vector machines

A Study on Wide-area Measurement-based Approaches for Power System Voltage Stability

With the development of wide-area monitoring system (WAMS) enabled by the synchrophasor technology, measurement-based approaches for power system voltage stability and control have been widely discussed in recent years. Based on high-frequency synchronized measurement signals collected from phasor measurement units (PMUs), these approaches have great potentials to significantly improve the situational awareness and to effectively guide the controls of interconnected modern power systems. If compared with conventional model-based voltage stability assessment (VSA) and control methods, the measurement-based methods are relatively new. Although their simplicity and independence of system models make them suitable for online deployment, the applications of these measurement-based methods are not as well explored as their model-based counterparts, which have been improved and matured over several decades. Therefore, the motivation of this dissertation is to explore new applications of measurement-based voltage stability assessment and control. In this dissertation, first, a comparative study on existing measurement-based approaches is provided; second, a hybrid VSA approach for N-1 contingency is proposed; third, measurement-based wide-area loading margin sensitivity suitable for voltage stability control is presented with a sample control study; fourth, mitigation approaches for overestimation of voltage stability margin when using coupled single-port circuit are proposed; and fifth, voltage dependent load model is integrated into measurement-based voltage stability analysis to provide a practical and accurate assessment of voltage stability margin

On the Exploitation of Admittance Measurements for Wired Network Topology Derivation

The knowledge of the topology of a wired network is often of fundamental importance. For instance, in the context of Power Line Communications (PLC) networks it is helpful to implement data routing strategies, while in power distribution networks and Smart Micro Grids (SMG) it is required for grid monitoring and for power flow management. In this paper, we use the transmission line theory to shed new light and to show how the topological properties of a wired network can be found exploiting admittance measurements at the nodes. An analytic proof is reported to show that the derivation of the topology can be done in complex networks under certain assumptions. We also analyze the effect of the network background noise on admittance measurements. In this respect, we propose a topology derivation algorithm that works in the presence of noise. We finally analyze the performance of the algorithm using values that are typical of power line distribution networks.Comment: A version of this manuscript has been submitted to the IEEE Transactions on Instrumentation and Measurement for possible publication. The paper consists of 8 pages, 11 figures, 1 tabl