Dijkstra Algorithm for Feeder Routing of Radial Distribution System

Jha, Priya

doi:10.9790/3021-03140106

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…In related research, the defined radial distribution feeder routing with Dijkstra's algorithm reduces the fixed cost, energy cost, and interruption cost (Jha and Vidyasagar, 2013). In DG allocation and sizing, Harmony Search (HS) was used to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution

Phawanaphinyo

Keeratipranon

Khemapatapan

2017

J. Rev. Global Econ.

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Electric power is the main energy source for a modern society. Good management of electric power cycle is essential for a sustainable society. The electric power cycle is composed of Generation, Transmission, Distribution, and Consumption. Smart Grid (SG) is a system that integrated traditional grids with Information and Communication Technology (ICT). In addition, SG has the ability to integrate electrical power supply from both to main power substation and Distributed Generation (DG), which compensates for the power demand during peak times. However, SG still has a similar problem to the original grid in terms of active power loss, from electric current injecting through the transmission line. This paper solves the active power loss problem by feeder routing using the Adjusting Dijkstra's Cost Method, follow by deciding the allocation position and sizing of DG by the use of Evolutionary Computing, namely Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO). The experiments evaluate the performance of the algorithm using power flow analysis, Backward / Forward Sweep Method, on the IEEE 33 bus system. From the experimental results, PSO provides the best performance. The overall active power loss in the cases of 3 DGs was reduced from 202.67 to 52.29 kW, representing a reduction of 74.20%.

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Section: Introductionmentioning

confidence: 99%

Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution

Phawanaphinyo

Keeratipranon

Khemapatapan

2017

J. Rev. Global Econ.

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“…The problem above was a provocation, causing a significant money to improve the distribution line, distribution transformer, and substation building to accommodate the active power loss [1]. In related research, the defined radial distribution feeder routing with Dijkstra's algorithm to reduces the fixed cost, energy cost, and interruption cost [2].The other proposed the feeder routing for reducing the cost of energy loss by finding the shortest path to the distribution system [3]. In DG allocation and sizing, theHSwas used to solve the problem.The objective was determined by the voltage and the capacitor.In the experiments using the IEEE33-bus and IEEE 69-bus system to compared the results with the GAand Refine Genetic Algorithm(RGA).The results showed the HSwas the best efficient in processing time [4].…”

Section: Introductionmentioning

confidence: 99%

Optimal Active Power Loss with Feeder Routing Collaborate Distributed Generation Allocation and Sizing in Smart Grid Distribution

Phawanaphinyo¹,

Keeratipranon²,

Khemapatapan³

2017

Proceedings of the 2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)

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Abstract.The Smart Grid (SG) has widely supported the electric power from the Distributed Generation (DG). It becomes a practical standard to generate the electric power from a renewable energy into the distribution system to compensate for the power demand, especially in the peak time. However, the advancement of the SG continuing with the classical problem of active power loss as the traditional grid. This research aimsto solve the active power loss problem by analyzing the elements and study to solve, in the scope of the organization that provides the electrical power. In order to solve the problem, the solutions can be achieved by feeder routing with adjusting cost Dijkstra's algorithm, afterward decided the allocation and sizing of DG by using the Evolutionary Computing (EC) which are Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO) algorithms. The experiment evaluates the performance of the algorithm usingpower flow analysis, Backward/ Forward Sweep Method, on the IEEE 33-bus system. From the experimental result, the PSO provides the best performance. The overall active power loss in the case 3 DGs was reduced from 202.67 to 52.29 kW, representing 74.20%reduction.

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Coordinated planning of Distributed Energy Resources and microgrid network

Guo

Cheng

2016

2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

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Dijkstra Algorithm for Feeder Routing of Radial Distribution System

Cited by 3 publications

References 13 publications

Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution

Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution

Optimal Active Power Loss with Feeder Routing Collaborate Distributed Generation Allocation and Sizing in Smart Grid Distribution

Coordinated planning of Distributed Energy Resources and microgrid network

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