Application of Voltage Stability Index for Congestion Management

2016 ◽  
pp. 253-264
Author(s):  
Madhvi Gupta ◽  
Vivek Kumar ◽  
N. K. Sharma ◽  
G. K. Banerjee
Keyword(s):  
Voltage Stability ◽  
Stability Index ◽  
Congestion Management ◽  
Voltage Stability Index

scholarly journals Effect of SVC installation on loss and voltage in power system congestion management

2019 ◽  
Vol 14 (1) ◽  
pp. 428 ◽  
Author(s):  
Nur Zahirah Mohd Ali ◽  
Ismail Musirin ◽  
Hasmaini Mohamad
Keyword(s):  
Power System ◽  
Voltage Stability ◽  
Optimization Technique ◽  
Stability Index ◽  
Evolutionary Programming ◽  
Congestion Management ◽  
Optimal Operation ◽  
Voltage Profile ◽  
Voltage Stability Index ◽  
Ac Transmission

<span>In this paper, a new hybrid optimization technique is proposed namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). This idea comes from the combination part of the clone in an Artificial Immune System (AIS) and then combined with Evolutionary Programming (EP). This technique was implemented to determine the optimal sizing of Flexible AC Transmission Systems (FACTS) devices. This study focused on the ability of Static Var Compensator (SVC) is used for the optimal operation of the power system as well as in reducing congestion in power system. In order to determine the location of SVC, the previous study has been done using pre-developed voltage stability index, Fast Voltage Stability Index (FVSI). Congested lines or buses will be identified based on the highest FVSI value for the purpose of SVC placement. The optimizations were conducted for the SVC sizing under single contingency, where SVC was modeled in steady state analysis. The objective function of this study is to minimize the power loss and improve the voltage profile along with the reduction of congestion with the SVC installation in the system. Validation on the IEEE 30 Bus RTS and IEEE 118 Bus RTS revealed that the proposed technique managed to reduce congestion in power system.</span>

Fast Voltage Stability Index (FVSI) Based Technique for Congestion Management Assessment

2015 ◽  
Vol 793 ◽  
pp. 49-53
Author(s):  
Nur Zahirah Mohd Ali ◽  
Ismail Musirin ◽  
H. Mohamad
Keyword(s):  
Voltage Stability ◽  
Optimization Technique ◽  
Stability Index ◽  
Congestion Management ◽  
Optimal Location ◽  
Stability Assessment ◽  
Voltage Stability Index ◽  
Facts Devices ◽  
Line Identification ◽  
Particle Swarm Optimization Technique

This paper presents a voltage stability assessment based approach to determine the congested line with optimal sizing and location. FVSI, a voltage stability index is chosen as the indicator for congested line identification, while particle swarm optimization technique (PSO) is used for optimal location and sizing of FACTs devices installation. Congested line is identified by increasing the reactive load at chosen load buses until they reach the maximum loadability level. PSO is applied for identifying the optimal location and sizing of FACTs devices as the compensating device. Results obtained from the implementation on IEEE 30 Bus RTS revealed that the proposed technique can manage the congestion subject to various disturbances.

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.

Optimization of Real Power Loss and Voltage Stability Index for Distribution Systems with Distributed Generation

2017 ◽  
Vol 33 ◽  
pp. 100-114 ◽  
Author(s):  
Mostafa Elshahed ◽  
Mahmoud Dawod ◽  
Zeinab H. Osman
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Reactive Power ◽  
Optimization Problems ◽  
Stability Index ◽  
Mixed Integer ◽  
Voltage Profile ◽  
Voltage Stability Index

Integrating Distributed Generation (DG) units into distribution systems can have an impact on the voltage profile, power flow, power losses, and voltage stability. In this paper, a new methodology for DG location and sizing are developed to minimize system losses and maximize voltage stability index (VSI). A proper allocation of DG has to be determined using the fuzzy ranking method to verify best compromised solutions and achieve maximum benefits. Synchronous machines are utilized and its power factor is optimally determined via genetic optimization to inject reactive power to decrease system losses and improve voltage profile and VSI. The Augmented Lagrangian Genetic Algorithm with nonlinear mixed-integer variables and Non-dominated Sorting Genetic Algorithm have been implemented to solve both single/multi-objective function optimization problems. For proposed methodology effectiveness verification, it is tested on 33-bus and 69-bus radial distribution systems then compared with previous works.

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