Implementation of genetic algorithm for optimal network reconfiguration in distribution systems for load balancing

Ravibabu, P.; Venkatesh, K.; Kumar, Chitranshu

doi:10.1109/sibircon.2008.4602603

Cited by 25 publications

(12 citation statements)

References 20 publications

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“…These operators systematically create fitter off springs through successive generations. Then the new generations quickly drive the search towards optimal solution [14].…”

Section: Genetic Algorithmmentioning

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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“…These operators systematically create fitter off springs through successive generations. Then the new generations quickly drive the search towards optimal solution [14].…”

Section: Genetic Algorithmmentioning

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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“…Prim's algorithm is proposed in [17] to find the power flow path in distribution network after an outage. Metaheuristic algorithm named Genetic Algorithm was implemented in [18] to select optimal solution based on fitness algorithm function. A new algorithm which is RAY algorithm was proposed in [19] to produce a minimum weighted spanning tree of the given graph with no direction pointed.…”

Section: Introductionmentioning

confidence: 99%

Power system restoration in distribution network using minimum spanning tree - Kruskal’s algorithm

Mohamad

Zalnidzham

Salim

et al. 2019

IJEECS

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<span>Events such as natural and manmade interference, line, transformer and feeder outages that occur in electric power distribution system negatively impact the continuity of power supply, thus affecting the power demand supply as well as customer’s satisfaction. In that cases, the restoration of power needs to be carried out immediately in order to guarantee the system’s reliability. The power flow path identification is considered as a difficult task especially in a huge system due to large number of switches. Kruskal’s algorithm is presented in this paper to find the minimum power flow path in a power distribution network. The comparison of performance between presented Kruskal’s algorithm and Binary Particle Swarm Optimization (BPSO) was made in solving a problem regarding network reconfiguration. The proposed load restoration approach is tested on IEEE 33-bus single feeder radial distribution system using MATLAB software. From the results, it is found that the presented Kruskal’s algorithm was able to search for the minimal power flow path that contribute to loss reduction for power restoration after the occurrence of fault.</span>

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“…The objective function of reconfiguration optimization is defined as minimization of the resistive losses in most of the previous studies. However the optimization function can be defined as maximization of reliability [18], balancing feeder lengths and loadings [19], minimization of voltage drop or overloads [20], [21] and integration of distributed generation [22].…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration of Actual Distribution Network with Optimum Power Flow for Loss Reduction

Dursun¹,

Karaosmanoğlu²,

Umurkan³

2016

IJEEE

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This study presents loss-reduction on radial electrical distribution system by reconfiguration based on optimum power flow pattern. A real section of distribution network from Istanbul is modeled according to actual load and network data. A new configuration is sought heuristically in order to minimize the interference on the optimum flow pattern. Reconfiguration is performed by closing all switches and consecutively opening the suitable switches carrying the minimum current until the radial system is acquired. Existing configuration and the meshed configuration with all switches closed are analyzed according to load flow calculations. A new network configuration satisfying the voltage and current limitations of the system with reduced losses is proposed for the system.

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Implementation of genetic algorithm for optimal network reconfiguration in distribution systems for load balancing

Cited by 25 publications

References 20 publications

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

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

Power system restoration in distribution network using minimum spanning tree - Kruskal’s algorithm

Reconfiguration of Actual Distribution Network with Optimum Power Flow for Loss Reduction

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