scholarly journals Voltage Stability Index Calculation by Hybrid State Estimation based on Multi Objective Optimal Phasor Measurement Unit Placement

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2688
Author(s):  
Matsukawa ◽  
Watanabe ◽  
Wahab ◽  
Othman
Keyword(s):  
Power System ◽  
State Estimation ◽  
Voltage Stability ◽  
Stability Index ◽  
Phasor Measurement Unit ◽  
Measurement Unit ◽  
Voltage Collapse ◽  
Hybrid State ◽  
Voltage Stability Index ◽  
Critical Boundary

Operation of a power system close to the voltage stability limit due to increasing of load demand and limited power sources may result in disastrous economic loss with voltage collapse of the entire power system. A system operator has to understand how far the system is from the critical boundary of the voltage collapse. This paper investigated the influence of State Estimation (SE) in the calculation of the Critical Boundary Index (CBI) as a voltage stability index. For SE, Hybrid State Estimation (HSE), including the measurement set of both Remote Terminal Unit (RTU) in Supervisory Control and Data Acquisition (SCADA) and Phasor Measurement Unit (PMU), is employed. Concurrently, the CBI is estimated using voltage phasor estimated by HSE based on optimal PMU location, which is selected from a Pareto optimal front obtained by the Non-dominated Sorting Genetic Algorithm II (NSGA-II). As a result of CBI estimation, HSE using PMU is relatively accurate in voltage stability index estimation compared to SCADA SE, which uses the RTU alone. However, when a mixed measurement condition in some lines affects the CBI estimation, it is suggested that it may be necessary to discard PMU measurements in some cases.

Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)

2012 ◽  
Vol 61 (2) ◽  
pp. 239-250 ◽  
Author(s):  
M. Kumar ◽  
P. Renuga
Keyword(s):  
Power System ◽  
Voltage Stability ◽  
Reactive Power ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Stability Index ◽  
Test System ◽  
Unified Power Flow Controller ◽  
Voltage Profile ◽  
Voltage Stability Index

Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)Transmission line loss minimization in a power system is an important research issue and it can be achieved by means of reactive power compensation. The unscheduled increment of load in a power system has driven the system to experience stressed conditions. This phenomenon has also led to voltage profile depreciation below the acceptable secure limit. The significance and use of Flexible AC Transmission System (FACTS) devices and capacitor placement is in order to alleviate the voltage profile decay problem. The optimal value of compensating devices requires proper optimization technique, able to search the optimal solution with less computational burden. This paper presents a technique to provide simultaneous or individual controls of basic system parameter like transmission voltage, impedance and phase angle, thereby controlling the transmitted power using Unified Power Flow Controller (UPFC) based on Bacterial Foraging (BF) algorithm. Voltage stability level of the system is defined on the Fast Voltage Stability Index (FVSI) of the lines. The IEEE 14-bus system is used as the test system to demonstrate the applicability and efficiency of the proposed system. The test result showed that the location of UPFC improves the voltage profile and also minimize the real power loss.

scholarly journals Fast Load Voltage Stability Index constrained PMU Placement for Complete Observability

2018 ◽  
Vol 7 (4.24) ◽  
pp. 20
Author(s):  
P.Lakshmi Narayana ◽  
M. Venkatesan ◽  
S. Ravindra
Keyword(s):  
Voltage Stability ◽  
Stability Index ◽  
Measurement Unit ◽  
Binary Integer Programming ◽  
Load Voltage ◽  
Voltage Stability Index ◽  
Pmu Placement ◽  
Bus Networks ◽  
Matlab Programming ◽  
Redundancy Index

This paper proposes a Fast Load Voltage Stability Index (FLVSI) constrained Binary Integer Programming (BIP) method for Phasor Measurement Unit placement at optimal locations in network to obtain complete observability. Every load bus of network is considered to sort out weak load bus from proposed FLVSI approach. PMUs are constrained to place at weak load buses using BIP approach for observability of network. Zero Injection (ZI) modeling is suggested to reduce PMU placement locations in network. Single line outage or PMU loss constraints are formulated for placement of PMUs. Bus Redundancy Index (BRI) is formulated and considered for every bus of network. With and without ZI modeling under normal and line outage cases is compared to present effectiveness of approach. IEEE –14- 30-and 57- bus networks are tested with MATLAB Programming and compared with other methods to show its effectiveness.

Voltage Stability Index of Radial Distribution Networks by Considering Distributed Generator for Different Types of Loads

2016 ◽  
Vol 5 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Tapan Kumar Chattopadhyay ◽  
Sumit Banerjee ◽  
Chandan Kumar Chanda
Keyword(s):  
Stability Analysis ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Stability Index ◽  
Distribution Networks ◽  
Voltage Collapse ◽  
Distributed Generator ◽  
Voltage Stability Index ◽  
Different Types

The paper presents an approach on voltage stability analysis of distribution networks for loads of different types. A voltage stability index is proposed for identifying the node, which is most sensitive to voltage collapse. It is shown that the node, at which the value of voltage stability index is maximum, is more sensitive to voltage collapse. For the purpose of voltage stability analysis, constant power, constant current, constant impedance and composite load modeling are considered. Distributed generation can be integrated into distribution systems to meet the increasing load demand. It is seen that with the insertion of distributed generator (DG), load capability limit of the feeder has increased for all types of loads. By using this voltage stability index, one can measure the level of voltage stability of radial distribution systems and thereby appropriate action may be taken if the index indicates a poor level of stability. The effectiveness of the proposed method is demonstrated through two examples.

scholarly journals Voltage collapse prediction using artificial neural network

2021 ◽  
Vol 11 (1) ◽  
pp. 124
Author(s):  
Samuel Isaac ◽  
Soyemi Adebola ◽  
Awelewa Ayokunle ◽  
Katende James ◽  
Awosope Claudius
Keyword(s):  
Neural Network ◽  
Voltage Stability ◽  
Stability Index ◽  
Voltage Collapse ◽  
Feed Forward Neural Network ◽  
Voltage Stability Index ◽  
Voltage Instability ◽  
Collapse Prediction ◽  
R Value ◽  
Bus System

Unalleviated voltage instability frequently results in voltage collapse; which is a cause of concern in power system networks across the globe but particularly in developing countries. This study proposed an online voltage collapse prediction model through the application of a machine learning technique and a voltage stability index called the new line stability index (NLSI_1). The approach proposed is based on a multilayer feed-forward neural network whose inputs are the variables of the NLSI_1. The efficacy of the method was validated using the testing on the IEEE 14-bus system and the Nigeria 330-kV, 28-bus National Grid (NNG). The results of the simulations indicate that the proposed approach accurately predicted the voltage stability index with an R-value of 0.9975 with a mean square error (MSE) of 2.182415x10<sup>−5</sup> for the IEEE 14-bus system and an R-value of 0.9989 with an MSE of 1.2527x10<sup>−7</sup> for the NNG 28 bus system. The results presented in this paper agree with those found in the literature.

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