A multi objective approach for placement of multiple DGs in the radial distribution system
- 5 July 2018
- journal article
- research article
- Published by Springer Nature in International Journal of Machine Learning and Cybernetics
- Vol. 10 (8) , 2027-2041
Abstract
No abstract availableKeywords
This publication has 26 references indexed in Scilit:
- Analytical approach for placement and sizing of distributed generation on distribution systemsIET Generation, Transmission & Distribution, 2014
- Multi-objective market clearing of electrical energy, spinning reserves and emission for wind-thermal power systemInternational Journal of Electrical Power & Energy Systems, 2013
- Optimal distributed generation location and size using a modified teaching–learning based optimization algorithmInternational Journal of Electrical Power & Energy Systems, 2013
- Adaptive differential evolution algorithm for solving non‐linear coordination problem of directional overcurrent relaysIET Generation, Transmission & Distribution, 2013
- A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systemsInternational Journal of Electrical Power & Energy Systems, 2012
- Sequential quadratic programming based differential evolution algorithm for optimal power flow problemIET Generation, Transmission & Distribution, 2011
- Optimal placement of multi-distributed generation units including different load models using particle swarm optimizationSwarm and Evolutionary Computation, 2011
- Modelling distributed generations in three-phase distribution load flowIET Generation, Transmission & Distribution, 2008
- A direct approach for distribution system load flow solutionsIEEE Transactions on Power Delivery, 2003
- A fast and elitist multiobjective genetic algorithm: NSGA-IIIEEE Transactions on Evolutionary Computation, 2002