Journal of Intelligent Learning Systems and Applications

Journal of Intelligent Learning Systems and Applications

ISSN Print: 2150-8402
ISSN Online: 2150-8410
www.scirp.org/journal/jilsa
E-mail: jilsa@scirp.org
"A Novel Stochastic Framework for the Optimal Placement and Sizing of Distribution Static Compensator"
written by Reza Khorram-Nia, Aliasghar Baziar, Abdollah Kavousi-Fard,
published by Journal of Intelligent Learning Systems and Applications, Vol.5 No.2, 2013
has been cited by the following article(s):
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[1] A new approach to optimal location and sizing of DSTATCOM in radial distribution networks using bio-inspired cuckoo search algorithm
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[2] Optimal Allocation of Multiple D-STATCOM in Distribution System Using PSO
2020
[3] Optimal Placement of D-STATCOM for Reduction of Power Loss and Improvement of Voltage Profile using Power Stability and Power Loss Indices in a Radial …
2019
[4] Sizing and Location Optimization of DSTATCOM in Radial Distribution System
2019
[5] A review on distributed generation planning
Renewable and Sustainable Energy Reviews, 2017
[6] The Imperialist Competitive Algorithm for Optimal Multi-Objective Location and Sizing of DSTATCOM in Distribution Systems Considering Loads Uncertainty
INAE Letters, 2017
[7] A Taxonomical Review on Distributed Generation Planning
2016
[8] Optimal D-STATCOM placement in radial distribution system based on power loss index approach
2015
[9] Optimal placement of D-STATCOM in distribution network using new sensitivity index with probabilistic load models
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[10] Short term load forecasting in power systems using a hybrid approach based on SVR technique
Journal of Intelligent and Fuzzy Systems, 2015
[11] A new intelligent method for optimal allocation of D-STATCOM with uncertainty
Journal of Intelligent & Fuzzy Systems, 2015
[12] Stochastic allocation and sizing of fuel cells using MFA and 2m-PEM
Journal of Intelligent & Fuzzy Systems, 2015
[13] Using Wireless Communications To Enable Decentralized Analysis And Control of Smart Distribution Systems
2014
[14] Loss reduction and voltage profile improvement by optimal placement and sizing of distributed generation (DG) using a hybrid of genetic algorithm (GA) and improved particle swarm optimization (IPSO)
Thesis, 2014
[15] Loss reduction and voltage profile improvement by optimal placement and sizing of distributed generation (DG) using a hybrid of genetic algorithm (GA) and improved …
2014
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