Simultaneous distributed generation and capacitor placement and sizing in radial distribution system considering reactive power market
In this paper, Teaching-Learning-Based Optimization (TLBO) algorithm is used to determine the location and size of capacitor banks and Distributed Generation (DG) units simultaneously, in order to maximize the Benefit in regards to Cost (BRC). The benefits which are considered for DG units and capac...
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| Published in | Journal of renewable and sustainable energy Vol. 6; no. 4 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Melville
American Institute of Physics
01.07.2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1941-7012 1941-7012 |
| DOI | 10.1063/1.4893431 |
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| Abstract | In this paper, Teaching-Learning-Based Optimization (TLBO) algorithm is used to determine the location and size of capacitor banks and Distributed Generation (DG) units simultaneously, in order to maximize the Benefit in regards to Cost (BRC). The benefits which are considered for DG units and capacitor banks are based on economic aspects. Therefore, for the DG units, the benefits are loss reduction, active power selling in the active power market, and energy not supplied reduction. On the other side, capacitor placement is performed to decrease the active power loss of networks, and reactive power selling (i.e., not purchasing reactive power as ancillary service from reactive power market). The DG units and capacitor banks are owned by distribution utility; consequently, their operation is controlled by the utility. The costs of DG units and capacitor banks include investment, operation, and maintenance costs. In addition, the cost of reactive power purchased for DGs is taken into account for non-unity power factor DG's (i.e., induction generator). The maximization process of BRC is performed using TLBO algorithm which has been selected from two alternative algorithms, i.e., particle swarm optimization and shuffled frog leaping algorithm. The study looked at a 69-bus radial distribution system. The results were reviewed, concluding that simultaneous DG and capacitor placement, considering the reactive power market, is a profitable way for loss reduction. Moreover, the strong performance of TLBO is shown. |
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| AbstractList | In this paper, Teaching-Learning-Based Optimization (TLBO) algorithm is used to determine the location and size of capacitor banks and Distributed Generation (DG) units simultaneously, in order to maximize the Benefit in regards to Cost (BRC). The benefits which are considered for DG units and capacitor banks are based on economic aspects. Therefore, for the DG units, the benefits are loss reduction, active power selling in the active power market, and energy not supplied reduction. On the other side, capacitor placement is performed to decrease the active power loss of networks, and reactive power selling (i.e., not purchasing reactive power as ancillary service from reactive power market). The DG units and capacitor banks are owned by distribution utility; consequently, their operation is controlled by the utility. The costs of DG units and capacitor banks include investment, operation, and maintenance costs. In addition, the cost of reactive power purchased for DGs is taken into account for non-unity power factor DG's (i.e., induction generator). The maximization process of BRC is performed using TLBO algorithm which has been selected from two alternative algorithms, i.e., particle swarm optimization and shuffled frog leaping algorithm. The study looked at a 69-bus radial distribution system. The results were reviewed, concluding that simultaneous DG and capacitor placement, considering the reactive power market, is a profitable way for loss reduction. Moreover, the strong performance of TLBO is shown. |
| Author | Aranizadeh, A. Rahiminejad, A. Vahidi, B. |
| Author_xml | – sequence: 1 givenname: A. surname: Rahiminejad fullname: Rahiminejad, A. – sequence: 2 givenname: A. surname: Aranizadeh fullname: Aranizadeh, A. – sequence: 3 givenname: B. surname: Vahidi fullname: Vahidi, B. |
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| CitedBy_id | crossref_primary_10_1155_2022_6833488 crossref_primary_10_1063_1_4989828 crossref_primary_10_1109_ACCESS_2020_2981406 crossref_primary_10_3390_en15218258 crossref_primary_10_3390_app11094156 crossref_primary_10_1016_j_ijepes_2016_04_002 crossref_primary_10_3233_JIFS_181990 crossref_primary_10_1063_1_5043403 crossref_primary_10_1080_15325008_2016_1183729 crossref_primary_10_1063_1_4966230 |
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| SubjectTerms | Algorithms Capacitor banks Capacitors Distributed generation Electric power distribution Energy management Induction generators Loss reduction Machine learning Maintenance costs Markets Particle swarm optimization Placement Power factor Power loss Radial distribution Reactive power |
| Title | Simultaneous distributed generation and capacitor placement and sizing in radial distribution system considering reactive power market |
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