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Multi-population traction differential evolution power distribution network planning method and device and storage medium

A technology of distribution network planning and differential evolution, applied in photovoltaic power generation, instruments, biological models, etc., can solve the problems of lack of diversity of population, slow iteration speed, low algorithm convergence speed, etc., to improve diversity and quality. , the effect of improving the convergence speed

Active Publication Date: 2021-08-06
RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] Therefore, the present invention aims to solve the technical problems that the convergence speed of the algorithm in the existing distribution network planning problem is relatively low, the population used in the iterative process lacks diversity, and the iterative speed is slow, thereby providing a multi-population traction differential evolution Distribution network planning method, equipment and storage medium

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  • Multi-population traction differential evolution power distribution network planning method and device and storage medium
  • Multi-population traction differential evolution power distribution network planning method and device and storage medium
  • Multi-population traction differential evolution power distribution network planning method and device and storage medium

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Embodiment 1

[0081] An embodiment of the present invention provides a multi-population traction differential evolution method distribution network planning method, which is used to determine the access location of the distributed photovoltaic distribution point for distribution network planning based on the multi-population traction differential evolution algorithm, see figure 1 As shown, the method includes:

[0082] Step S12, clustering the acquired feature quantity data through the K-means algorithm to obtain cluster data; the feature quantity data includes distributed photovoltaic output data and load history data;

[0083] In the embodiment of the present invention, the load of the distribution network obeys the same distribution, and the output level will be different in different periods of the year, so the daily average load power (ie mean value) and daily maximum load power of each load node can be taken as The difference (that is, the extreme difference) is used as the characteri...

Embodiment 2

[0196] This embodiment provides a multi-population differential mutation evolution method distribution network planning equipment, which plans the distribution network based on the multi-population traction differential evolution algorithm, and is used to determine the access position of the distributed photovoltaic distribution point. See Figure 13 shown, including:

[0197] The clustering module 32 is used to cluster the acquired feature quantity data through the K-means algorithm to obtain cluster data; the feature quantity data includes distributed photovoltaic output data and load history data;

[0198] The model construction module 34 is used to construct a distribution network planning model for distributed power access according to the clustering data; the calculation model of the investment cost of the distribution network planning model, the calculation model of the operation cost and the calculation model of the performance index Constitute the objective function, ...

Embodiment 3

[0207] This embodiment provides a multi-population traction differential evolution method distribution network planning equipment, which plans the distribution network based on the multi-population traction differential evolution algorithm, such as Figure 14 As shown, the multi-population traction differential evolution method distribution network planning equipment includes a processor 1401 and a memory 1402, wherein the processor 1401 and the memory 1402 can be connected through a bus or in other ways, Figure 14 Take connection via bus as an example.

[0208]The processor 1401 can be a central processing unit (Central Processing Unit, CPU) or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), graphics processing units (Graphics Processing Unit, GPU), embedded neural network processing Neural-network Processing Unit (NPU) or other dedicated deep learning coprocessor, Application Specific Integrated Circuit (ASIC), Field-Programmable...

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Abstract

The invention discloses a multi-population traction evolution method power distribution network planning method, equipment and a storage medium. Based on a multi-population traction differential evolution algorithm, the method is used for determining access positions of distributed photovoltaic distribution points, and comprises the following steps: clustering acquired characteristic quantity data through a K-means algorithm to obtain clustering data; constructing a power distribution network planning model connected with the distributed power supply according to the clustering data; enabling a calculation model of the investment cost, a calculation model of the operation cost and a calculation model of the performance index of the power distribution network planning model to form a target function, and taking a power flow equation, node voltage constraint, branch current constraint and a single load node access distributed photovoltaic upper limit as constraint conditions; solving the power distribution network planning model based on a multi-population traction differential evolution algorithm, and determining a photovoltaic node access position. By implementing the method, the iteration speed and quality are improved, the diversity of populations adopted in the iteration process is ensured, and more reasonable access of distributed photovoltaic distribution points is ensured.

Description

technical field [0001] The invention relates to the technical field of distribution network planning, in particular to a distribution network planning method, equipment and storage medium of a multi-population traction differential evolution method. Background technique [0002] As an important part of the national energy industry, electric energy is an essential energy source in national life and an important pillar of national development. However, the traditional power system has problems such as high investment costs, large power transmission losses, and difficult operation coordination. Many questions. Distributed power is widely connected to distribution network due to its characteristics of flexibility, decentralization, high efficiency, and environmental friendliness. [0003] However, the access of Distributed Generation (DG) has completely changed the operation structure of the distribution network, making the distribution network change from a single power source...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06Q30/02G06K9/62G06N3/00
CPCG06Q10/0631G06Q10/067G06Q50/06G06Q30/0206G06N3/006G06F18/23213Y04S10/50
Inventor 郑志杰梁荣杨波王耀雷刘钊王延朔綦陆杰崔灿李昭杨扬李昊赵韧刘淑莉张雯杨慎全邓少治李凯张博颐
Owner RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER
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