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Optimal Load Shedding Using Swarm Intelligence Based Algorithm

Optimal Load Shedding Using Swarm Intelligence Based Algorithm in Bloomington, MN

Current price: $47.00
Get it at Barnes and Noble
Optimal Load Shedding Using Swarm Intelligence Based Algorithm

Optimal Load Shedding Using Swarm Intelligence Based Algorithm in Bloomington, MN

Current price: $47.00
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Size: OS

Get it at Barnes and Noble
In this book, an Optimal Load Shedding problem is solved using a swarm-intelligence based, bio-inspired Firefly Algorithm (FA). A couple of the standard objective functions pertaining to optimal load shedding, viz. the New Voltage Stability Index (NVSI), which indicates the optimal bus location for load shedding, and the amount of load shedding is minimized using the proposed firefly algorithm to obtain the optimum values. Minimization of this index improves transmission line performance, thus improving voltage stability of the system. A standard IEEE 30-bus test system is used for implementation. The performance analysis of this optimization problem using the firefly algorithm and its comparison with the standard Particle Swarm Optimization (PSO) algorithm is carried out by checking various combinations of values of the associated parameters.
In this book, an Optimal Load Shedding problem is solved using a swarm-intelligence based, bio-inspired Firefly Algorithm (FA). A couple of the standard objective functions pertaining to optimal load shedding, viz. the New Voltage Stability Index (NVSI), which indicates the optimal bus location for load shedding, and the amount of load shedding is minimized using the proposed firefly algorithm to obtain the optimum values. Minimization of this index improves transmission line performance, thus improving voltage stability of the system. A standard IEEE 30-bus test system is used for implementation. The performance analysis of this optimization problem using the firefly algorithm and its comparison with the standard Particle Swarm Optimization (PSO) algorithm is carried out by checking various combinations of values of the associated parameters.

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