Capacitor Allocation in Unbalanced Systems Using a Three-Level Optimization Framework

The optimal capacitor placement issue has a strong combinatorial nature due to the high number of possible decisions. This paper proposes a three-level method to solve this problem in unbalanced distribution systems to achieve energy losses minimization. In the first step, the Multiphase Optimal Pow...

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Bibliographic Details
Published in:Revista IEEE América Latina 2021-09, Vol.19 (9), p.1599-1607
Main Authors: Martins, Antonio Sobrinho Campolina, Costa, Fernando Rocha Moreira de Souza, De Araujo, Leandro Ramos, Penido, Debora Rosana Ribeiro
Format: Article
Language:English
Subjects:
Capacitor Placement
Capacitors
Combinatorial analysis
Constraint modelling
Energy distribution
Feeders
Genetic algorithms
IEEE transactions
Load flow
Losses Minimization
Minimization
Multiphase
Optimal Power Flow
Optimization
Power flow
Reactive power
Resource management
Switches
Topology
Unbalance
Unbalanced Distribution Systems
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Summary:The optimal capacitor placement issue has a strong combinatorial nature due to the high number of possible decisions. This paper proposes a three-level method to solve this problem in unbalanced distribution systems to achieve energy losses minimization. In the first step, the Multiphase Optimal Power Flow is solved by Interior Point Method, considering heavy-load and light-load, where the reactive power and the number of fixed and switched banks are determined, where the topology constraints are modeled using a Multiphase Power Flow Method. In the second step, the position of the capacitors is determined using Genetic Algorithms, using the light-load to allocate the fixed banks and heavy-load to allocate the switched ones. Finally, the third step aims to determine the states of the switched capacitors, using binary optimization and considering the whole daily load curve. For validation, it is tested on topologies based in IEEE 4, IEEE 13, and IEEE 123 Node Test-Feeders.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2021.9468614