Reactive Power Optimization with SVC & TCSC using Genetic Algorithm
In this paper Genetic Algorithm (GA) is used as an evolutionary tecthniques for the optimal placement of flexible AC transmission systems (FACTS) devices in an interconnected power system. Here two types of FACTS devices has been discussed nemely, Thyristor Controlled Series Capacitor (TCSC) and Sta...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
VSB-Technical University of Ostrava
2014-01-01
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| Series: | Advances in Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://advances.utc.sk/index.php/AEEE/article/view/778 |
| _version_ | 1797827063331160064 |
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| author | Biplab Bhattacharyya Vikash Kumar Gupta Sanjay Kumar |
| author_facet | Biplab Bhattacharyya Vikash Kumar Gupta Sanjay Kumar |
| author_sort | Biplab Bhattacharyya |
| collection | DOAJ |
| description | In this paper Genetic Algorithm (GA) is used as an evolutionary tecthniques for the optimal placement of flexible AC transmission systems (FACTS) devices in an interconnected power system. Here two types of FACTS devices has been discussed nemely, Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) for the economic operation and to reduce the transmission loss. Reactively loading of the system is taken from base to 200% of base loading and the system performance is observed without and with FACTS devices. Optimal placement of FACTS devices in the system is determined by calculating active and reactive power flow in lines. FACTS devices along with reactive generation of generators and transformer tap setting are used for the power transfer capacity using GA. The proposed approach is applied on IEEE 14 and IEEE 30-bus test systems. Finally the effectiveness of the proposed GA based method of placement of FACTS devices is established by comparing the results with another standard method of optimization like Particle Swarm Optimization (PSO) technique. |
| first_indexed | 2024-04-09T12:42:15Z |
| format | Article |
| id | doaj.art-c896596449cb40dbba7c25b3b59a09e2 |
| institution | Directory Open Access Journal |
| issn | 1336-1376 1804-3119 |
| language | English |
| last_indexed | 2024-04-09T12:42:15Z |
| publishDate | 2014-01-01 |
| publisher | VSB-Technical University of Ostrava |
| record_format | Article |
| series | Advances in Electrical and Electronic Engineering |
| spelling | doaj.art-c896596449cb40dbba7c25b3b59a09e22023-05-14T20:50:09ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192014-01-0112111210.15598/aeee.v12i1.778645Reactive Power Optimization with SVC & TCSC using Genetic AlgorithmBiplab BhattacharyyaVikash Kumar GuptaSanjay KumarIn this paper Genetic Algorithm (GA) is used as an evolutionary tecthniques for the optimal placement of flexible AC transmission systems (FACTS) devices in an interconnected power system. Here two types of FACTS devices has been discussed nemely, Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) for the economic operation and to reduce the transmission loss. Reactively loading of the system is taken from base to 200% of base loading and the system performance is observed without and with FACTS devices. Optimal placement of FACTS devices in the system is determined by calculating active and reactive power flow in lines. FACTS devices along with reactive generation of generators and transformer tap setting are used for the power transfer capacity using GA. The proposed approach is applied on IEEE 14 and IEEE 30-bus test systems. Finally the effectiveness of the proposed GA based method of placement of FACTS devices is established by comparing the results with another standard method of optimization like Particle Swarm Optimization (PSO) technique.http://advances.utc.sk/index.php/AEEE/article/view/778facts devicesgenetic algorithmline power flowoptimal location of facts devicesparticle swarm optimization. |
| spellingShingle | Biplab Bhattacharyya Vikash Kumar Gupta Sanjay Kumar Reactive Power Optimization with SVC & TCSC using Genetic Algorithm Advances in Electrical and Electronic Engineering facts devices genetic algorithm line power flow optimal location of facts devices particle swarm optimization. |
| title | Reactive Power Optimization with SVC & TCSC using Genetic Algorithm |
| title_full | Reactive Power Optimization with SVC & TCSC using Genetic Algorithm |
| title_fullStr | Reactive Power Optimization with SVC & TCSC using Genetic Algorithm |
| title_full_unstemmed | Reactive Power Optimization with SVC & TCSC using Genetic Algorithm |
| title_short | Reactive Power Optimization with SVC & TCSC using Genetic Algorithm |
| title_sort | reactive power optimization with svc tcsc using genetic algorithm |
| topic | facts devices genetic algorithm line power flow optimal location of facts devices particle swarm optimization. |
| url | http://advances.utc.sk/index.php/AEEE/article/view/778 |
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