Implementation of Improved Genetic Algorithm in distribution system with feeder reconfiguration to minimize real power losses

Ravibabu, P.; Ramya, M.V.S.; Sandeep, Renangi; Karthik, M.; Harsha, S. P.

doi:10.1109/iccet.2010.5485563

Cited by 14 publications

(7 citation statements)

References 12 publications

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“…In [16], reconfiguration was done in order to reduce network losses and balance feeder loads. Other methods have also been employed for the optimal reconfiguration of distribution networks, including power flow based on intelligent algorithms [17], the simulated annealing algorithm [18], the hybrid differential revolution algorithm [19], particle swarm algorithm (PSO) [20], and improved GA [21], and in [22], a fuzzy multiobjective approach was presented.…”

Section: Introductionmentioning

confidence: 99%

A new multiobjective fuzzy shuffled frog-leaping algorithm for optimal reconfiguration of radial distribution systems in the presence of reactive power compensators

Dehnavi¹,

Esmaeili²

2013

Turkish Journal of Electrical Engineering and Computer Sciences

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Section: Introductionmentioning

confidence: 99%

A new multiobjective fuzzy shuffled frog-leaping algorithm for optimal reconfiguration of radial distribution systems in the presence of reactive power compensators

Dehnavi¹,

Esmaeili²

2013

Turkish Journal of Electrical Engineering and Computer Sciences

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“…More ellaborate algorithms that resorts to artificial intelligence can be found in [7], where genetic algorithm is employed, and in [8], an ant colony optimization algorithm is proposed. In [9], a hybrid method that combines evolutionary programming and ant colony optimization is proposed.…”

Section: Topological Reconfiguration In Power Distribution Systemsmentioning

confidence: 99%

Multi-agent systems applied to topological reconfiguration of smart power distribution systems

Saraiva

Asada

2014

2014 International Joint Conference on Neural Networks (IJCNN)

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One of the various features expected for a smart power distribution system -a smart grid in the power distribution level -is the possibility of the fully automated operation for certain control actions. Although this is very expected, it requires various logic, sensor and actuator technologies in a system which, historically, has a low level of automation. One of the most analyzed problems for the distribution system is the topology reconfiguration. The reconfiguration has been applied to various objectives: minimization of power losses, voltage regulation, load balancing, to name a few. The solution method in most cases is centralized and its application is not in real-time. From the new perspectives of advanced distribution systems, fast and adaptive response of the control actions are required, specially in the presence of alternative generation sources and electrical vehicles. In this context, the multi-agent system, which embeds the necessary control actions and decision making is proposed for the topology reconfiguration aiming the loss reduction. The concept of multi-agent system for distribution system is proposed and two case studies with 11-Bus and 16-Bus system are presented.

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“…It depends on the first step of analysis of the network structure to find the branches participating in each loop that is formed as each tieswitch gets closed. In [12,16] some string generation techniques have been proposed. However, the proposed switching strings were very long and it is difficult to implement in case of complicated distribution networks.…”

Section: Encoding and Decoding Of Switching Stringmentioning

confidence: 99%

Voltage sag mitigation in distribution systems by using genetically optimized switching actions

Salman

Mohamed

Shareef

2011

2011 5th International Power Engineering and Optimization Conference

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Network reconfiguration is a switching action process for altering the distribution network structure. It is an efficient method for line loss reduction in power systems and though uncommon, it can also be employed for voltage sag mitigation. In this paper, a method for improving bus voltage magnitude during voltage sag is presented. It is done by applying network reconfiguration to the exposed weak area in distribution systems. In the process of reconfiguration, genetic algorithm with a new encoding method is used to maintain the radial structure of distribution network while reaching the optimal solution. The simulation results show that the proposed method is efficient and feasible for improving the bus voltage profile during voltage sag. The proposed method may assist utility engineers in taking the right decision for network reconfiguration.Index Terms-Voltage sag, distribution system and power quality.

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Implementation of Improved Genetic Algorithm in distribution system with feeder reconfiguration to minimize real power losses

Cited by 14 publications

References 12 publications

A new multiobjective fuzzy shuffled frog-leaping algorithm for optimal reconfiguration of radial distribution systems in the presence of reactive power compensators

A new multiobjective fuzzy shuffled frog-leaping algorithm for optimal reconfiguration of radial distribution systems in the presence of reactive power compensators

Multi-agent systems applied to topological reconfiguration of smart power distribution systems

Voltage sag mitigation in distribution systems by using genetically optimized switching actions

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