Distributed power supply optimal configuration method and system

A technology of distributed power supply and optimized configuration, applied in the direction of system integration technology, neural learning method, information technology support system, etc., can solve the problem of difficult to capture the nonlinear characteristics of high-dimensional data, deviate from the actual planning scene, and the robust optimization method is too conservative To achieve the effect of increasing access capacity, reducing total social cost, and improving economy

Active Publication Date: 2020-09-25
GUANGXI POWER GRID CORP
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Problems solved by technology

[0003] At present, there are mainly traditional probabilistic modeling methods, robust optimization methods, and scene generation technology for modeling the uncertainty of distributed generation technology output; while traditional probabilistic modeling methods need to accurately describe uncertain factors, and actual engineering Only part of the statistical information can be obtained, it is difficult to obtain accurate probability distribution and this method ignores the timing characteristics of distributed power output; the robust optimization method has the disadvantage of being too conservative, and cannot balance the economy and security of the planning scheme well ; Traditional scene generation technology is difficult to capture the nonlinear characteristics of high-dimensional data, there are certain limitations, and it may deviate from the actual planning scene

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  • Distributed power supply optimal configuration method and system
  • Distributed power supply optimal configuration method and system
  • Distributed power supply optimal configuration method and system

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Embodiment 1

[0045] see figure 1 , figure 1 It is a schematic flowchart of a method for optimal configuration of distributed power sources in an embodiment of the present invention.

[0046] Such as figure 1 As shown, a method for optimal configuration of a distributed power supply, the method comprising:

[0047] S11: Model the uncertainty of distributed power output based on conditional deep convolution to generate an adversarial network model, and add month label information to the model to generate wind and solar output scenarios;

[0048] In the specific implementation process of the present invention, the generation of an adversarial network model based on conditional depth convolution models the uncertainty of distributed power output, and adding month label information to the model to generate wind and solar output scenarios includes: The generator continuously generates a distribution close to the real data to determine the target of the generator network; through the discrimin...

Embodiment 2

[0126] see figure 2 , figure 2 It is a schematic diagram of the system structure composition of the distributed power supply optimization configuration in the embodiment of the present invention.

[0127] Such as figure 2 As shown, a distributed power supply optimization configuration system, the system includes:

[0128] Generation module 11: used to generate an adversarial network model based on conditional deep convolution to model the uncertainty of distributed power output, and add month label information to the model to generate wind and solar output scenarios;

[0129] Determination module 12: used to determine the upper limit and lower limit of the wind and solar output corresponding to the month label information based on the Gaussian mixture model, and generate a distributed power limit scenario;

[0130] Modeling module 13: used to establish a model of distributed power double-layer optimal configuration according to the distributed power limit scenario, and s...

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Abstract

The invention discloses a distributed power supply optimal configuration method and system. The method comprises the steps: carrying out the modeling of the uncertainty of the output of a distributedpower supply based on a conditional depth convolution generative adversarial network model, and adding month label information into the model to generate a wind and light output scene; determining anupper limit and a lower limit of wind-solar output corresponding to the month label information based on a Gaussian mixture model, and generating a distributed power supply limit scene; establishing adistributed power supply double-layer optimal configuration model according to the distributed power supply limit scene, and solving the model; and verifying and analyzing the distributed power supply double-layer optimal configuration model based on an IEEE33 node system. In the embodiment of the invention, the access capacity of the distributed power supply is improved, the total social cost iseffectively reduced, and the economical efficiency of power distribution network operation is improved.

Description

technical field [0001] The present invention relates to the technical field of power supply optimization, in particular to a method and system for optimal configuration of distributed power supplies. Background technique [0002] With the continuous consumption of traditional fossil energy and other resources, the energy crisis and environmental pollution problems are becoming more and more serious. The development of clean and sustainable energy has become an important strategy for energy development in countries all over the world. The wind and solar energy resources in nature are abundant and can be obtained continuously, providing effective support for the formation of a new global energy development pattern. However, the randomness and fluctuation characteristics of wind power and photovoltaic power generation also bring great challenges to the planning and operation of distribution network, and become the main obstacle to the vigorous development of distributed generat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/00G06N3/04G06N3/08G06N3/12
CPCG06Q10/04G06Q50/06G06N3/006G06N3/088G06N3/126G06N3/047G06N3/048G06N3/045Y02E40/70Y04S10/50
Inventor 陶毅刚李小伟谭靖黎敏陈楚谭晓虹崔志威李镕耀
Owner GUANGXI POWER GRID CORP
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