A Genetic–Based Tabu Search Algorithm for Optimal DG Allocation in Distribution Networks

By M. Gandomkar, M. Vakilian, Mehdi Ehsan. 2005

215 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8b5438c615e428baafe5121d82ff752b8ef624a4

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. M. E. El-Hawary
2. Mohamad F. AlHajri
3. Mohammed R. AlRashidi
4. Hadi Nasiri-Rad
5. Nima Amjady

In Electrical and Electronic Engineering

1. C. Das
2. M. E. El-Hawary
3. Daryoush Habibi
4. Mohamad F. AlHajri
5. Mohammed R. AlRashidi
6. Ganesh Kothapalli
7. Thair Mahmoud
8. Octavian Bass

Citations in the corpus

• Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II (2015, methodology): “Among the research about optimization methods, multiobjective models of DG planning were optimized by various methods, such as the simulated annealing technique, Tabu search method integrated with the genetic algorithm (GA) [4], and Fuzzy optimization method [5].”
• Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality (2018, methodology): “To evade the major shortcomings of the classical simple GA, a new hybrid algorithm combining GA and TS is proposed in [263].”
• Hybrid Particle Swarm Optimization Approach for Optimal Distribution Generation Sizing and Allocation in Distribution Systems (2007, background): “[13] investigated only the location aspects of DG with respect to network real power losses.”