Research of Multi-Objective Power Network Planning Based on Improved Fish Swarm Algorithm

Xin Yi; Li Xin Ma; Wen Fei Cai; Jin Sun

doi:10.4028/www.scientific.net/AMM.494-495.1735

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Dynamic Characteristic Analysis of Transmission Tower
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A Feasibility Urban Power Network Black-Start Scheme Based on Gas-Steam CCPP
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Planning of Terminal Unit Amount in Distribution Automation Systems
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Self-Organizing Feature Extraction Method for the High-Voltage Discharge Fault in Ultraviolet Imaging Detection System
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Online Method for Location of Single Phase to Ground Fault through Cement Pole in Distribution Network
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Study on the User-Side Risk of Smart Grid System in Big Data Age
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Study on Technological Evaluation Modeling of Smart Grid
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Research on Centralized Short-Circuit and Leakage Protection for High-Voltage System of Underground Central Substation
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 494-495Research of Multi-Objective Power Network Planning...

Research of Multi-Objective Power Network Planning Based on Improved Fish Swarm Algorithm

Abstract:

According to the problem that traditional single objective network planning cant meet the demand of complex gird and key supply mission, using improved artificial fish swarm algorithm (AFSA) for multi-objective grid planning. The paper presents a method through selecting Pareto optimal compromise solution by calculating and comparing the degree of satisfaction of each planning scheme with the reference of scholar Paretos approach of striking a multi-objective optimal solution. This method can effectively balance weights between multiple targets and improve the reliability and economy of power grid. The experiment results show the good performance of the proposed method.

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Periodical:

Applied Mechanics and Materials (Volumes 494-495)

Pages:

1735-1738

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.494-495.1735

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Online since:

February 2014

Authors:

Xin Yi, Li Xin Ma*, Wen Fei Cai, Jin Sun

Keywords:

Artificial Fish Swarm Algorithm, Grid Planning, Multi-Objective, Reliability

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* - Corresponding Author

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