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 inJournal of renewable and sustainable energy Vol. 6; no. 4
Main Authors Rahiminejad, A., Aranizadeh, A., Vahidi, B.
Format Journal Article
LanguageEnglish
Published Melville American Institute of Physics 01.07.2014
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ISSN1941-7012
1941-7012
DOI10.1063/1.4893431

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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.
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.
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Snippet In this paper, Teaching-Learning-Based Optimization (TLBO) algorithm is used to determine the location and size of capacitor banks and Distributed Generation...
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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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