An effective network reconfiguration approach of radial distribution system for loss minimization and voltage profile improvement

Salkuti, Surender Reddy; Battu, Neelakanteshwar Rao

doi:10.11591/eei.v10i4.2867

Cited by 14 publications

(6 citation statements)

References 27 publications

(27 reference statements)

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“…Taking the node number in reference [13] as an example, the reconstruction results of this paper show that the disconnected branches are 10-70, 12-19, 13-14, 46-47 and 50-51. Although other algorithms [14] are different from individual disconnected branches in this paper, the network loss and the lowest node voltage are the same.…”

Section: Simulationsmentioning

confidence: 94%

A Distribution Network Reconfiguration Continuous Method Based on Efficient Solution Space Coding

Tang

Sun

Feng

et al. 2022

Frontiers in Artificial Intelligence and Applications

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This paper proposes a distribution network reconfiguration (DNR) continuous method to reduce network loss, balancing load, eliminating overload and improving power quality. When a certain coding rule reduces the dimension and reduces the radius of the variable confidence interval, the first type of non effective solution is avoided in probability through the coding rules and algorithm characteristics, and the second type of non effective solution is completely avoided compared with the expert base, so that the number of power flow calculations is greatly reduced. Through improved Crisscross optimization algorithm (CSO), the directionality is introduced into the horizontal crossing, and the fuzzy clustering idea is adopted to dynamically change the static vertical crossing factor, the simulation results show convergence speed and accuracy are improved, and verify the correctness and effectiveness of the method.

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Section: Simulationsmentioning

confidence: 94%

A Distribution Network Reconfiguration Continuous Method Based on Efficient Solution Space Coding

Tang

Sun

Feng

et al. 2022

Frontiers in Artificial Intelligence and Applications

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“…The second class can solve the challenges that the first category has been encountered effectively. The third one includes the Star algorithm (A*) and the Dijkstra algorithm, which uses a chart to draw out the pathways [24].…”

Section: Approaches Of Path Planningmentioning

confidence: 99%

Expansion of high-voltage overhead transmission lines to remote areas

Al‐Kharsan

Al-khaykan

Fakhruldeen

2022

IJPEDS

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<span>Delivering electrical energy to remote areas is one of the essential things in our modern world. Choosing the optimal route is one of the most critical factors contributing to reducing the power transmission system's cost. Other influencing factors such as the optimum alloy of the conductor wires are difficult to change, so only the aforementioned factor was adopted. In this paper, the optimized potential field algorithm is employed to determine the sub-optimum path that the transmission line should be installed. The best line for the towers is not necessarily the shortest or the cheapest one. Sometimes the best locations for the towers of the transmission lines coming according to the safety regards. It can be said that the best trajectory is a combination of several factors, including the length of the track in addition to other influencing factors depending on the work environment.</span>

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“…In this work, PSO is for attaining the optimal placement of DG for lessening power loss (𝑃 𝐿𝑜𝑠𝑠 ) and boosting voltage profile while dealing with some variables at the same time. 𝑃 𝐿𝑜𝑠𝑠 in the electrical network can be written as shown in (1) [20]:…”

Section: Problem Formulationmentioning

confidence: 99%

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

Jumaa

Neda²,

Mhawesh

2021

Bulletin EEI

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There are several profits of distributed generator (DG) units which are believed for improving the safety of the distribution power grids. However, these profits can be maximized by ensuring optimum sizing and positioning of DG units because an arbitrary location of DG units may adversely affect and jeopardize power grids which could contribute to maximising of power loss and degradation of the voltage profile. Therefore, several approaches were suggested to ensure optimum position and size of DGs. The primary aim of this article is for establishing technique for optimum scheduling and operating of DG to lessen power loss, revamp voltage profile and overall network reliability. Artificial intelligence method called particle swarm optimization (PSO) is utilized for finding the best site and size of DG to lessen power loss and boost the voltage profile. In this paper, IEEE 33 distribution system is utilized to display applicability of PSO. The results of the PSO are compared with the results gotten by other methods in the literature. Finally, the results show that the PSO is superior than the other methods.

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An effective network reconfiguration approach of radial distribution system for loss minimization and voltage profile improvement

Cited by 14 publications

References 27 publications

A Distribution Network Reconfiguration Continuous Method Based on Efficient Solution Space Coding

A Distribution Network Reconfiguration Continuous Method Based on Efficient Solution Space Coding

Expansion of high-voltage overhead transmission lines to remote areas

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

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