Optimal reconfiguration of electrical distribution network using the refined genetic algorithm

By Jizhong Zhu. 2002

473 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/01669dbf5812b176c2ae5d77d8ca3ba3f0d6ec18

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Antonio Padilha-Feltrin
2. Khaleequr Rehman Niazi
3. R. Rao
4. Rubén R. Romero
5. Anil Swarnkar
6. S. Narasimham
7. A. Rao
8. Nikhil Gupta

In Electrical and Electronic Engineering

1. Antonio Padilha-Feltrin
2. Khaleequr Rehman Niazi
3. R. Rao
4. Rubén R. Romero
5. Anil Swarnkar
6. S. Narasimham
7. A. Rao
8. Nikhil Gupta

Citations in the corpus

• Reconfiguration of Distribution Systems for Real Power Loss Minimization Using Adaptive Particle Swarm Optimization (2011, background): “[ 9 ] and Zhu [ 10 ] proposed refined GAs for feeder reconfiguration.”
• Path-based distribution network modeling: application to reconfiguration for loss reduction (2005, background): “Finally, a third category comprises those contributions using artificial intelligence, like simulated annealing [15], fuzzy logic [16], genetic algorithms (GAs) [17], or artificial neural networks [18].”
• An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem (2008, background): “can be formulated as follows [10], [18]:”
• Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm (2011, methodology): “It can be observed that 24.85% of average loss reduction is achieved by HSA comparing with 18.01% by the GA, 18.65% by the RGA, and 19.34% by the ITS as shown in Table III.”