Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market
This paper presents a genetic algorithm (GA) to maximize total system social welfare and alleviate congestion by best placement and sizing of TCSC device, in a double-sided auction market. To introduce more accurate modeling, the valve loading effects is incorporated to the conventional quadratic s...
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| Format: | Article |
| Language: | English |
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Stefan cel Mare University of Suceava
2011-05-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2011.02016 |
| _version_ | 1811280772845273088 |
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| author | MASOUM, M. A. S. NABAVI, S. M. H. KAZEMI, A. |
| author_facet | MASOUM, M. A. S. NABAVI, S. M. H. KAZEMI, A. |
| author_sort | MASOUM, M. A. S. |
| collection | DOAJ |
| description | This paper presents a genetic algorithm (GA) to maximize total system social welfare and alleviate congestion by best placement and sizing of TCSC device, in a double-sided auction market. To introduce more accurate modeling, the valve loading effects is incorporated to the conventional quadratic smooth generator cost curves. By adding the valve point effect, the model presents nondifferentiable and nonconvex regions that challenge most gradient-based optimization algorithms. In addition, quadratic consumer benefit functions integrated in the objective function to guarantee that locational marginal prices charged at the demand buses is less than or equal to DisCos benefit, earned by selling that power to retail customers. The proposed approach makes use of the genetic algorithm to optimal schedule GenCos, DisCos and TCSC location and size, while the Newton-Raphson algorithm minimizes the mismatch of the power flow equations. Simulation results on the modified IEEE 14-bus and 30-bus test systems (with/without line flow constraints, before and after the compensation) are used to examine the impact of TCSC on the total system social welfare improvement. Several cases are considered to test and validate the consistency of detecting best solutions. Simulation results are compared to solutions obtained by sequential quadratic programming (SQP) approaches. |
| first_indexed | 2024-04-13T01:20:50Z |
| format | Article |
| id | doaj.art-44f4c64c0b75426ebf0754e1afc76cd2 |
| institution | Directory Open Access Journal |
| issn | 1582-7445 1844-7600 |
| language | English |
| last_indexed | 2024-04-13T01:20:50Z |
| publishDate | 2011-05-01 |
| publisher | Stefan cel Mare University of Suceava |
| record_format | Article |
| series | Advances in Electrical and Computer Engineering |
| spelling | doaj.art-44f4c64c0b75426ebf0754e1afc76cd22022-12-22T03:08:46ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002011-05-011129910610.4316/AECE.2011.02016Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction MarketMASOUM, M. A. S.NABAVI, S. M. H.KAZEMI, A.This paper presents a genetic algorithm (GA) to maximize total system social welfare and alleviate congestion by best placement and sizing of TCSC device, in a double-sided auction market. To introduce more accurate modeling, the valve loading effects is incorporated to the conventional quadratic smooth generator cost curves. By adding the valve point effect, the model presents nondifferentiable and nonconvex regions that challenge most gradient-based optimization algorithms. In addition, quadratic consumer benefit functions integrated in the objective function to guarantee that locational marginal prices charged at the demand buses is less than or equal to DisCos benefit, earned by selling that power to retail customers. The proposed approach makes use of the genetic algorithm to optimal schedule GenCos, DisCos and TCSC location and size, while the Newton-Raphson algorithm minimizes the mismatch of the power flow equations. Simulation results on the modified IEEE 14-bus and 30-bus test systems (with/without line flow constraints, before and after the compensation) are used to examine the impact of TCSC on the total system social welfare improvement. Several cases are considered to test and validate the consistency of detecting best solutions. Simulation results are compared to solutions obtained by sequential quadratic programming (SQP) approaches.http://dx.doi.org/10.4316/AECE.2011.02016congestion managementreal code based-GAreschedulingsocial welfare maximizationTCSC |
| spellingShingle | MASOUM, M. A. S. NABAVI, S. M. H. KAZEMI, A. Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market Advances in Electrical and Computer Engineering congestion management real code based-GA rescheduling social welfare maximization TCSC |
| title | Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market |
| title_full | Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market |
| title_fullStr | Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market |
| title_full_unstemmed | Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market |
| title_short | Social Welfare Improvement by TCSC using Real Code Based Genetic Algorithm in Double-Sided Auction Market |
| title_sort | social welfare improvement by tcsc using real code based genetic algorithm in double sided auction market |
| topic | congestion management real code based-GA rescheduling social welfare maximization TCSC |
| url | http://dx.doi.org/10.4316/AECE.2011.02016 |
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