Preventive control approach for voltage stability improvement using voltage stability constrained optimal power flow based on static line voltage stability indices

Preventive control approach for voltage stability improvement using voltage stability constrained optimal power flow based on static line voltage stability indices

Preventive control approach for voltage stability improvement using voltage stability constrained optimal power flow based on static line voltage stability indices

Abstract:

Voltage stability improvement is a challenging issue in planning and security assessment of power systems. As modern systems are being operated under heavily stressed conditions with reduced stability margins, incorporation of voltage stability criteria in the operation of power systems began receiving great attention. This study presents a novel voltage stability constrained optimal power flow (VSC-OPF) approach based on static line voltage stability indices to simultaneously improve voltage stability and minimise power system losses under stressed and contingency conditions. The proposed methodology uses a voltage collapse proximity indicator (VCPI) to provide important information about the proximity of the system to voltage instability. The VCPI index is incorporated into the optimal power flow (OPF) formulation in two ways; first it can be added as a new voltage stability constraint in the OPF constraints, or used as a voltage stability objective function. The proposed approach has been evaluated on the standard IEEE 30-bus and 57-bus test systems under different cases and compared with two well proved VSC-OPF approaches based on the bus voltage indicator Lindex and the minimum singular value. The simulation results are promising and demonstrate the effectiveness of the proposed VSC-OPF based on the line voltage stability index.
Published in: IET Generation, Transmission & Distribution ( Volume: 8, Issue: 5, May 2014 )
Date of Publication: 12 May 2014
ISSN Information:
INSPEC Accession Number: 14256193
Publisher: IET

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Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation

Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation

Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation

Abstract:

Recently, integration of distributed generation (DG) in distribution systems has increased to high penetration levels. The impact of DG units on the voltage stability margins has become significant. Optimization techniques are tools which can be used to locate and size the DG units in the system, so as to utilize these units optimally within certain limits and constraints. Thus, the impacts of DG units issues, such as voltage stability and voltage profile, can be analyzed effectively. The ultimate goal of this paper is to propose a method of locating and sizing DG units so as to improve the voltage stability margin. The load and renewable DG generation probabilistic nature are considered in this study. The proposed method starts by selecting candidate buses into which to install the DG units on the system, prioritizing buses which are sensitive to voltage profile and thus improve the voltage stability margin. The DG units’ placement and sizing is formulated using mixed-integer nonlinear programming, with an objective function of improving the stability margin; the constraints are the system voltage limits, feeders’ capacity, and the DG penetration level.
Published in: IEEE Transactions on Power Systems ( Volume: 28, Issue: 1, Feb. 2013 )
Date of Publication: 14 June 2012
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INSPEC Accession Number: 13244941
Publisher: IEEE

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Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm

Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm

Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm

Abstract:- People have paid more attention to enhancing voltage stability margin since voltage collapses happened in some power systems recently. This paper proposes an optimal reactive power flow (ORPF) incorporating static voltage stability based on a multi-objective adaptive immune algorithm (MOAIA). The main idea of the proposed algorithm is to add two parts to an existing immune algorithm. The first part defines both partial affinity and global affinity to evaluate the antibody affinity to the multi-objective functions. The second part uses adaptive crossover, mutation and clone rates for antibodies to maintain the antibodies diversity. Hence, the proposed algorithm can achieve a dynamic balance between individual diversity and population convergence. The paper describes ORPF’s multi-objective functional mathematical model and the constraint conditions. The problems associated with the antibody are also discussed in detail. The proposed method has been tested in the IEEE-30 system and compared with IGA (immune genetic algorithm). The results show that the proposed algorithm has improved performance over the IGA.

Publisher: ELSEVIER


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Optimal placement of FACTS devices for multi-objective voltage stability problem

Optimal placement of FACTS devices for multi-objective voltage stability problem

Optimal placement of FACTS devices for multi-objective voltage stability problem

Abstract:

In this paper, a new method for optimal locating multi-type FACTS devices in order to optimize multi-objective voltage stability problem is presented. The proposed methodology is based on a new variant of Particle Swarm Optimization (PSO) specialized in multi-objective optimization problem known as Non-dominated Sorting Particle Swarm Optimization (NSPSO). The crowding distance technique is used to maintain the Pareto front size at the chosen limit, without destroying its characteristics. To aid the decision maker choosing the best compromise solution from the Pareto front, the fuzzy-based mechanism is employed for this task. NSPSO is used to find the optimal location and setting of two types of FACTS namely: Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) that maximize Static Voltage Stability Margin (SVSM), reduce Real Power Losses (RPL), and Load Voltage Deviation (LVD). The optimization is carried out on two and three objective functions for various FACTS combinations. The thermal limits of lines and voltage limits of load buses are considered as security constraints. The simulation results show the effectiveness of the proposed NSPSO to solve the multiobjective optimization problem considered and capture Pareto optimal solutions with satisfactory diversity characteristics.
Date of Conference: 15-18 March 2009
Date Added to IEEE Xplore: 24 April 2009
INSPEC Accession Number: 10588700
Publisher: IEEE

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Multi-objective VAr Planning with SVC for a Large Power System Using PSO and GA

Multi-objective VAr Planning with SVC for a Large Power System Using PSO and GA

Multi-objective VAr Planning with SVC for a Large Power System Using PSO and GA

Abstract: Particle swarm optimization (PSO) algorithm is used for planning the static VAr compensator (SVC) in a large-scale power system. The primary function of an SVC is to improve transmission system voltage, thereby enhancing the maximum power transfer limit. To enhance voltage stability, the planning problem is formulated as a multiobjective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem in a large-scale power system is solved by the fuzzy PSO with very encouraging results, and the results are compared with those obtained by the genetic algorithm (GA)
Date of Conference: 29 Oct.-1 Nov. 2006
Date Added to IEEE Xplore: 05 February 2007
INSPEC Accession Number: 9462837

Publisher: IEEE


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Multi-objective Optimization of Power System Performance with TCSC Using the MOPSO Algorithm

Multi-objective Optimization of Power System Performance with TCSC Using the MOPSO Algorithm

Multi-objective Optimization of Power System Performance with TCSC Using the MOPSO Algorithm

Abstract: 
In this paper, multi-objective particle swarm optimization (MOPSO) algorithm is used to find the optimal location of thyristor controlled series compensator (TCSC) and its parameter in order to increase total transfer capability (TTC), reduce total transmission losses and reduce voltage deviation. This multi-objective optimization problem is solved by using the MOPSO with sigma method and encouraging results are obtained.
Date of Conference: 24-28 June 2007
Date Added to IEEE Xplore: 23 July 2007
Print ISSN: 1932-5517
INSPEC Accession Number: 10300808

Publisher: IEEE


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On-line voltage stability based contingency ranking using fast voltage stability index (FVSI)

On-line voltage stability based contingency ranking using fast voltage stability index (FVSI)

On-line voltage stability based contingency ranking using fast voltage stability index (FVSI)

Abstract:

Voltage instability is one phenomenon that could happen in a power system due to its stressed condition. The result would be the occurrence of voltage collapse which leads to total blackout to the whole system. Therefore voltage collapse prediction is important in power system planning and operation so that the occurrence of voltage collapse due to voltage instability could be avoided. Line outage in a power system could also lead to the event of voltage collapse which implies the contingency in the system. Line outage contingencies are ranked so that the line which highly affects voltage stability of the system when there is an outage occurs in this line could be identified. The contingency ranking process can be conducted by computing the line stability index of each line for a particular line outage and sort them in descending order. The contingency which is ranked highest implies that it contributes to system instability. This paper presents a new voltage stability index refers to a line namely fast voltage stability index (FVSI). The values of the line indices indicate the voltage stability condition in the system and it is used to rank the line outage contingency. The information from the contingency ranking denotes the severity of the voltage stability condition in a power system due to line outage. The proposed contingency ranking technique was tested on an IEEE reliability test system.
Date of Conference: 6-10 Oct. 2002
Date Added to IEEE Xplore: 19 February 2003
Print ISBN: 0-7803-7525-4
INSPEC Accession Number: 7664557
Publisher: IEEE


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Technique for contingency monitoring and voltage collapse prediction

Technique for contingency monitoring and voltage collapse prediction

Technique for contingency monitoring and voltage collapse prediction

Abstract:

Investigation and online monitoring of power system stability have become vital factors to electric utility suppliers. At present power system utilities operate very close to the limit of system stability owing to an increasing number of new economic and environmental restrictions. Researchers have been trying to find out the most effective way for online system status monitoring, so that necessary precautions can be taken prior to voltage collapse. Several methods have been proposed for analysing voltage collapse phenomena. An effective method for online system status monitoring and thus voltage collapse prediction is described. The basic methodology implied in this technique is the investigation of each line of the system through calculating line stability indices. The proposed method was tested on the IEEE 24-bus reliability test system and has been found to be accurate and precise in voltage collapse prediction. A comparative study with other methods has also been carried out indicating that the proposed method has some advantages over the others.
Date of Publication: 06 August 2002
Print ISSN: 1350-2360
INSPEC Accession Number: 6129904
Publisher: IET
Sponsored by: IET

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A Comparison of Voltage Stability Indices for Placing Shunt FACTS Controllers

A Comparison of Voltage Stability Indices for Placing Shunt FACTS Controllers

A Comparison of Voltage Stability Indices for Placing Shunt FACTS Controllers

Abstract:

Location of shunt compensation devices is important for the enhancement of the voltage stability for practical power systems. This paper presents a comparison of several voltage stability indices in electric power system to identify the weakest bus/ area of the system. Shunt FACTS controller is introduced at the weakest bus in IEEE 14-bus test system and its effectiveness is assessed by comparing voltage profile and loading margin enhancement. Various line stability indices are also compared with and without shunt FACTS controller. It is shown that the best location for reactive power compensation for improving static voltage stability margin is the “weakest bus” of the system.
Date of Conference: 16-18 July 2008
Date Added to IEEE Xplore: 29 July 2008

Publisher: IEEE


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Estimating the Voltage Stability Margin Using PMU Measurements

Estimating the Voltage Stability Margin Using PMU Measurements

Estimating the Voltage Stability Margin Using PMU Measurements

Abstract:- This paper presents a new method based on phasor measurement units (PMUs) for the estimation of voltage stability margin in a power system to increase operator’s situational awareness. The method assumes a PMU measurement preprocessing technique as a priori in order to eliminate data inconsistency and uncertainty caused by random load disturbances. The measurements are then used in the computation of voltage stability margin based on the coupled single-port Thevenin equivalent model and the cubic spline extrapolation technique. Moreover, some practical operating constraints such as the generator reactive power limits are taken into account for practical assessment of the method’s performance. Extensive case studies conducted on several standard IEEE test systems are used to demonstrate the effectiveness of the proposed method.
Published in: IEEE Transactions on Power Systems ( Volume: 31, Issue: 4, July 2016 )
Date of Publication: 30 September 2015
INSPEC Accession Number: 15985795
Publisher: IEEE

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