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Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability
Abstract 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 Teaching–Learning-Based Optimization (TLBO), particle swarm optimization (PSO) and its variant.
Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability
Abstract 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 Teaching–Learning-Based Optimization (TLBO), particle swarm optimization (PSO) and its variant.
Genetic Algorithm Used for Load Shedding Based on Sensitivity to Enhance Voltage Stability
Titare, L. S. (author) / Singh, P. (author) / Arya, L. D. (author)
Journal of The Institution of Engineers (India): Series B ; 95 ; 337-343
2014-07-09
7 pages
Article (Journal)
Electronic Resource
English
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