Application of active power sensitivity to frequency and voltage variations on load shedding

Girgis, A.A.; Mathure, Shruti

doi:10.1016/j.epsr.2009.09.013

Cited by 46 publications

(23 citation statements)

References 34 publications

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“…Load buses have been ranked based on sensitivities of Schur's inequality indicator of load flow Jacobian with respect to the load (real and reactive load). The amount of load to be shed at load bus has been optimized using developed [9] algorithm.…”

Section: Resultsmentioning

confidence: 99%

“…A methodology was presented by Wiszniewski et.al [8] which gives new criteria of voltage stability margin for the purpose of load shedding. A methodology was presented by Girgis et.al [9] that shows the rate of change of frequency can be utilized to determine the magnitude of generation-load imbalance, while the rate of change of voltage with respect to active power can be utilized to identify the sensitive bus for load shedding. A methodology to optimize the load curtailments necessary to restore the equilibrium of operating point was described by Arya et.al [10].…”

Section: Introductionmentioning

confidence: 99%

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Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability

Titare¹,

Singh²,

Arya³

2014

J. Inst. Eng. India Ser. B

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This paper presents an algorithm to calculate optimum load shedding with voltage stability consideration based on sensitivity of proximity indicator using genetic algorithm (GA). Schur's inequality based proximity indicator of load flow Jacobian has been selected, which indicates system state. Load flow Jacobian of the system is obtained using Continuation power flow method. If reactive power and active rescheduling are exhausted, load shedding is the last line of defense to maintain the operational security of the system. Load buses for load shedding have been selected on the basis of sensitivity of proximity indicator. The load bus having large sensitivity is selected for load shedding. Proposed algorithm predicts load bus rank and optimum load to be shed on load buses. The algorithm accounts inequality constraints not only in present operating conditions, but also for predicted next interval load (with load shedding). Developed algorithm has been implemented on IEEE 6-bus system. Results have been compared with those obtained using TeachingLearning-Based Optimization (TLBO), particle swarm optimization (PSO) and its variant. Keywords Schur's inequality Á Sensitivity Á Load shedding Á Genetic Algorithm Á Voltage stability List of symbols J Objective function J 0 Jacobian of load flow solution ls i Total load (real and reactive power) shed at ith load bus NG Total number of generator buses NL Number of load buses NLS Number of load buses selected for loadshedding P gk ,Q gk Lower bound on active and reactive power generation at kth bus " P gk , " Q gk Upper bound on active and reactive power generation at kth bus P gk o , Q gk o Active and reactive power generation at kth bus under current operating condition accounting load shed P gk p , Q gk p Active and reactive power generation at kth bus under predicted load condition accounting load shed V i o Load bus voltage at ith load bus under current operating condition accounting load shed V i p Load bus voltage at ith load bus under predicted load condition accounting load shed V i , " V i Lower and upper bound on ith load bus voltage k min Minimum Eigen value of load flow Jacobian s Schur's inequality proximity indicator value of load flow Jacobian s o Schur's inequality proximity indicator value of load flow Jacobian under current operating condition accounting load shed

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability

Titare¹,

Singh²,

Arya³

2014

J. Inst. Eng. India Ser. B

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“…We implemented a fuzzy controller in order to enslave the process of the gate opening, Fig. 2 [5,7,13].…”

Section: Studied Modelmentioning

confidence: 99%

Fuzzy load shedding strategy based on the anticipation of the point of voltage collapse

Jemai

Trabelsi

Ouederni

2014

Journal of Intelligent &Amp; Fuzzy Systems

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As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several strategies are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we propose a new approach of a load shedding strategy based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to voltage level at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a pre-calculated load shedding ratio in the purpose to reestablish the power balance and avoid the appearance of the collapse phenomenon.

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“…Amraee et al [14] developed an optimal load shedding algorithm which is based on the concept of the static voltage stability margin and its sensitivity at the maximum loading point. Girgis and Mathure [15] presented a methodology that shows the rate of change of frequency can be utilized to determine the magnitude of generation-load imbalance, while the rate of change of voltage with respect to active power can be utilized to identify the sensitive bus for load shedding. Fu and Wang [16] presented an algorithm for studying the load shedding problem in emergencies where an ac power flow solution cannot be found for the stressed system.…”

Section: Introductionmentioning

confidence: 99%

Differential evolution applied for anticipatory load shedding with voltage stability considerations

Arya¹,

Singh²,

Titare

2012

International Journal of Electrical Power & Energy Systems

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Application of active power sensitivity to frequency and voltage variations on load shedding

Cited by 46 publications

References 34 publications

Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability

Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability

Fuzzy load shedding strategy based on the anticipation of the point of voltage collapse

Differential evolution applied for anticipatory load shedding with voltage stability considerations

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