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Substation Plan Based on Improved Model and Adaptive Mutation Particle Swarm Optimization Algorithm

Authors: Zhiqiang Wang; Huakun Que; Lixin Zhang;

Substation Plan Based on Improved Model and Adaptive Mutation Particle Swarm Optimization Algorithm

Abstract

Take the unitary minimal investment and annual operating cost of multi voltage grades for the objective function, adopt the line length calculating means of rectangular and adaptive mutation particle swarm optimization algorithm to make sure number and position of substations, the capacity and number of transformers, the power supply range of substations. Based on Maplnfo platform, deal with geography information of substation planning involved factors by visual, off-line processing method, create the map layer of feasible plots and append it to iterative formula as constraint condition, this method can ensure scientific and utility of optimization result in economy and geography. At the same time, it proofs efficiency and correctness of algorithm through examples.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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