A geometrical approach for network reconfiguration based loss minimization in distribution systems

“…The DORM has been applied on 33 and 69 node distribution systems [20,21]. The 33 node network, operating at 12.66 kV with net loads of 3715 kW and 2300 kVar, contains 5 normally opened switches and 32 normally closed switches.…”

Section: Numerical Resultsmentioning

confidence: 99%

Dragonfly Optimization based Reconfiguration for Voltage Profile Enhancement in Distribution Systems

Abhiraj¹,

Aravindhababu²

2017

IJCA

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Dragonfly Optimization (DO) is a nature inspired optimization technique that imitates the static and dynamic swarming activities of dragonflies. The static swarm possessing smaller number of dragonflies hunts for preys in a small area, while the dynamic swarm with more number of dragonflies travels over long distances; and they represent the exploration and exploitation phases of the DO. This paper applies DO in solving reconfiguration problem of distribution systems with an objective of enhancing the voltage profile. It presents the results of 33 and 69-node distribution systems for illustrating the superiority of the proposed method.

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“…The second test network is a 12.66 kV, 69 node network comprising of 5 tie-loops. The network data of the initial configuration is available in [20]. The total active and reactive network loads are 3802.19 kW and 2694.60 kVar, respectively.…”

Section: Numerical Resultsmentioning

confidence: 99%

New Reconfiguration Method for Improving Voltage Profile of Distribution Networks

Vizhiy¹,

Santhi²

2016

IJCA

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Network reconfiguration aims to minimize network real power loss through rearranging the status of open switches. The consumers of the distribution networks need a better voltage profile for efficient operation of various gadgets. This paper thus attempts to develop a new reconfiguration algorithm with an objective of improving the voltage profile of the distribution network without incurring any additional cost for installation of capacitors and tap-changing transformers. The algorithm uses a nature-inspired biogeography based optimization (BBO) that searches for optimal solution through the migration and mutation operators. Test results on a 33 and 69-node distribution networks reveal the superiority of the developed method. General TermsOptimization, evolutionary algorithms

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A geometrical approach for network reconfiguration based loss minimization in distribution systems

Cited by 70 publications

References 12 publications

Sensitivity based Load Shedding Strategy for Avoiding Voltage Instability

Sensitivity based Load Shedding Strategy for Avoiding Voltage Instability

Dragonfly Optimization based Reconfiguration for Voltage Profile Enhancement in Distribution Systems

New Reconfiguration Method for Improving Voltage Profile of Distribution Networks

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