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Distributed power supply siting and sizing optimization method and system based on improved genetic algorithm

A technology for improving genetic algorithms and distributed power sources, applied in the field of distributed power source location selection and capacity optimization, it can solve the problems of complex programming implementation process, insufficient development and utilization of parallel mechanisms, and long solution time, so as to ensure safe production and stability. Operation, good practical application value, simple calculation effect

Inactive Publication Date: 2018-11-02
STATE GRID SHANDONG ELECTRIC POWER
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Problems solved by technology

However, there are defects such as long solution time, complex programming implementation process, and insufficient development and utilization of potential parallel mechanisms, so genetic algorithms are still a current research hotspot.

Method used

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  • Distributed power supply siting and sizing optimization method and system based on improved genetic algorithm
  • Distributed power supply siting and sizing optimization method and system based on improved genetic algorithm
  • Distributed power supply siting and sizing optimization method and system based on improved genetic algorithm

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with accompanying drawing.

[0046] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0047] It should be noted that the terminology used here is only for describing specific embodiments, and is not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0048] In order to solve the p...

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Abstract

The invention discloses a distributed power supply siting and sizing optimization method and system. The method comprises the following steps: firstly investigating the actual condition of an experiment region, determining an optimal target function and a constraint condition, and performing normalization processing on the multi-target optimal function on this basis; secondly, performing modellingbased on OpenDSS on a power distribution network containing the distributed power supply, accomplishing the power flow calculation and the solution of the related parameter, and optimizing the installation location and capacity of the grid-connected distributed power supply by applying the improved genetic algorithm. The OpenDSS is applied to performing modelling and power flow analysis on the power distribution network containing the distributed power supply, the time required by the computation of the power flow computation and the node voltage is reduced, and the condition of trapping in local optimum can be effectively avoided by adopting the improved genetic algorithm, thereby facilitating the overall optimal solution; therefore, the selection of the distributed power supply grid-connection location and capacity is more reasonable, and the bad influence on the power distribution network is reduced fundamentally.

Description

technical field [0001] The invention relates to an optimization method and system for site selection and capacity determination of a distributed power supply based on an improved genetic algorithm. Background technique [0002] At present, common distributed power generation site selection and capacity optimization algorithms can be divided into traditional mathematical algorithms and intelligent algorithms, among which intelligent algorithms include classical genetic algorithm, particle swarm algorithm, ant colony algorithm and Tabu search algorithm. Genetic algorithm is a global optimization method based on genetic mechanism and natural selection principle, which is applicable to any function expression form and can effectively solve practical problems. Due to the advantages and limitations of the genetic algorithm itself, there are advantages and disadvantages in practical applications. The algorithm has fast search ability, has parallelism, can compare multiple individu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/12
CPCG06N3/126G06Q10/04G06Q50/06Y02E40/70Y04S10/50
Inventor 徐珂聂萌王洋侯广松甄颖荆树志张冰田运涛
Owner STATE GRID SHANDONG ELECTRIC POWER
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