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# Distribution system efficiency improvement by reconfiguration and capacitor placement using a modified particle swarm optimization algorithm

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Rezaei, P
; Sharif University of Technology
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2010

915
Viewed

- Type of Document: Article
- DOI: 10.1109/EPEC.2010.5697205
- Publisher: 2010
- Abstract:
- Capacitor placement/setting is one of the main means for loss reduction and voltage profile improvement in distribution systems. If capacitor placement is meant, the objective function will be the cost of energy losses besides the capacitors costs in a specified period of time. Here, reconfiguration can be used as a strategy to reform the base configuration of the distribution network in order to place the capacitors more efficiently with lower costs. On the other hand, if capacitors are already available in a network, optimum capacitors setting and network reconfiguration should be performed for power loss minimization. In this paper both power loss minimization and capacitor placement cost minimization are implemented using a modified particle swarm optimization algorithm. PSO is a robust optimization algorithm inspired by social behavior. Several simulations are performed on two conventional sample distribution networks and compared against the results of existing methods which demonstrated the advantage of this method
- Keywords:
- Capacitor placement ; Cost minimization ; Distribution network ; Distribution system efficiency ; Distribution system reconfiguration ; Distribution systems ; Energy loss ; Existing method ; Loss reduction ; Lower cost ; Modified particle swarm optimization ; Network re-configuration ; Objective functions ; Power-losses ; Robust optimization algorithm ; Sample distributions ; Social behavior ; Voltage profile improvement ; Algorithms ; Capacitors ; Computer simulation ; Costs ; Electric power supplies to apparatus ; Energy conservation ; Energy dissipation ; Local area networks ; Smart power grids ; Particle swarm optimization (PSO)
- Source: EPEC 2010 - IEEE Electrical Power and Energy Conference: "Sustainable Energy for an Intelligent Grid", 25 August 2010 through 27 August 2010 ; August , 2010 ; 9781424481880 (ISBN)
- URL: http://ieeexplore.ieee.org/document/5697205