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Active power distribution network multi-period dynamic reconstruction method based on improved recursive ordered clustering

A dynamic reconfiguration and distribution network technology, which is applied to AC networks with the same frequency from different sources, electrical components, circuit devices, etc., can solve the problem of many switching operations, improve ergodicity, speed up convergence, The effect of high accuracy

Active Publication Date: 2019-12-03
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Problems solved by technology

[0005] Static reconfiguration is performed sequentially on the unit time period in the reconfiguration cycle to ensure the optimal topology in the whole time period, which can effectively reduce the system network loss, but it will lead to too many switching operations. Therefore, according to the equivalent load curve, orderly clustering can be obtained a wide range of applications

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  • Active power distribution network multi-period dynamic reconstruction method based on improved recursive ordered clustering
  • Active power distribution network multi-period dynamic reconstruction method based on improved recursive ordered clustering
  • Active power distribution network multi-period dynamic reconstruction method based on improved recursive ordered clustering

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Embodiment

[0064] The invention relates to a multi-period dynamic reconstruction method for active distribution networks based on improved recursive orderly clustering, such as figure 1 shown, including the following steps:

[0065] 1. According to the characteristics of the test system, the data types are divided into three categories, namely load, fan injection power and photovoltaic injection power. According to the source load prediction curve, the period is divided by the improved recursive order clustering method.

[0066] 1. Assume that the reconstruction cycle is divided into T unit periods on average, and the ath full-time power matrix is ​​A a , then A a =[X a1 , X a2 ,...,X aT ] T , where the power value X at time m am =[x am,1 , x am,2 ,...,x am,n ], n represents the number of nodes, x am,l means A a The power value of node l at time m, define the unit period included in the jth period as {β j , β j+1 ,...,β j+1 -1} Then A a The Euclidean distance for the jth ...

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Abstract

The invention relates to an active power distribution network multi-period dynamic reconstruction method based on improved recursive ordered clustering. The method comprises the following steps of: S1, employing the Euclidean distance to describe the similarity degree of data in a segment, and employing the improved recursive ordered clustering to take the maximum similarity degree in various types of power prediction curve segments as a target for period division; S2, calculating an uncertain power flow by using an affine-linear optimization interval power flow algorithm so as to calculate aninterval value of the network loss, and taking a midpoint of the interval value as a fitness function; S3, according to the determined fitness function, solving the model by adopting an adaptive quantum particle swarm algorithm of a Blot spherical surface to obtain an optimal solution which is a disconnecting switch set corresponding to the optimal network topology; and S4, adjusting the topological structure of the power distribution network by adopting the obtained disconnection switch set. Compared with the prior art, the method has the advantages of quick optimization, safe and economic operation of the power grid and the like.

Description

technical field [0001] The invention relates to a distribution network reconfiguration technology, in particular to a multi-period dynamic reconfiguration method of an active distribution network based on improved recursive orderly clustering. Background technique [0002] At present, the integration of renewable energy and smart grid has been widely used. This integration form can effectively improve the stability and flexibility of the power system. While reducing power loss, it also has the advantages of energy saving, environmental protection, and investment reduction. It is 21 The development direction of the power industry in the century. Distributed power generation is generally combined with low-voltage distribution network, which has the characteristics of reducing energy loss, low construction cost, less environmental pollution, safety and stability, and flexible power generation methods. In today's energy shortage, the emergence of distributed power has brought p...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00H02J3/06
CPCH02J3/00H02J3/06Y04S10/50
Inventor 于艾清高纯
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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