2012
DOI: 10.1016/j.ijepes.2012.05.064
|View full text |Cite
|
Sign up to set email alerts
|

New approach for optimal UPFC placement using hybrid immune algorithm in electric power systems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

0
49
0

Year Published

2013
2013
2022
2022

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 90 publications
(53 citation statements)
references
References 50 publications
(74 reference statements)
0
49
0
Order By: Relevance
“…where ∆P gg represents power mismatch, which is obtained by Equation (14). If the voltage regulation at bus k is disabled, the Equation (15) …”
Section: Upfc Equivalent Circuit and Power Flow Modelmentioning
confidence: 99%
See 2 more Smart Citations
“…where ∆P gg represents power mismatch, which is obtained by Equation (14). If the voltage regulation at bus k is disabled, the Equation (15) …”
Section: Upfc Equivalent Circuit and Power Flow Modelmentioning
confidence: 99%
“…where ∆Pgg represents power mismatch, which is obtained by Equation (14). If the voltage regulation at bus k is disabled, the Equation (15) 3rd column is exchanged by partial derivatives of the bus and mismatch powers of UPFC with respect to the bus voltage magnitude Vk.…”
Section: Upfc Equivalent Circuit and Power Flow Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…Using UPFC based on feedback linearization technique was introduced in [3] to regulate the active power demand. The UPFC location optimization using the immune PSO is investigated in [4] to enhance power system capacity. In [5], the critical clearing time of SMIB system has increased after the occurrence of UPFC.…”
Section: Introductionmentioning
confidence: 99%
“…While in [18], an optimal strategy comprising CPF and OPF techniques to install the static model of UPFC, was proposed by minimizing the sum of the generation cost and investment. The hybrid immune algorithms (HIA) proposed in [19], with the performance validated to be better than other evolutionary methods such as GA, PSO, and IA, were utilized to increase system loadability by optimizing the locations for UPFC installation. The new indices, thermal capacity index (TCI) and contingency capacity index (CCI), proposed in [20] were used to place TCSC at appropriate location under normal and network contingency conditions respectively.…”
Section: Introductionmentioning
confidence: 99%