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Method for wind power plant equivalence based on multi-objective optimization algorithm

A multi-objective optimization and wind farm technology, applied in the value field, can solve problems such as the difficulty in ensuring the accuracy and validity of the equivalent model, reduce the amount of calculation and running time, avoid too many identification parameters, and ensure accuracy Effect

Active Publication Date: 2018-08-28
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Application Information

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Problems solved by technology

However, in actual wind farms, wind speed fluctuations and fault disturbances often coexist. In this article, the equivalent model obtained by parameter identification based on a certain disturbance may produce errors in another disturbance situation, so the single-objective optimization parameter identification method is difficult to guarantee Equivalent Accuracy and Effectiveness of Equivalent Model in Power System Analysis

Method used

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  • Method for wind power plant equivalence based on multi-objective optimization algorithm
  • Method for wind power plant equivalence based on multi-objective optimization algorithm
  • Method for wind power plant equivalence based on multi-objective optimization algorithm

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Embodiment

[0044] In this embodiment, an actual wind farm in Ningxia is built with PSASP software, and its structural diagram is as follows figure 1 shown. The wind farm includes 66 sets of 1.5MW permanent magnet direct-drive wind turbines. The wind turbines are boosted and converged to the PCC bus through a 0.62 / 35kV machine-end transformer, and then connected to some external systems through a 35 / 110kV wind farm outlet transformer. Structural diagram such as figure 2 shown.

[0045] The wind speed fluctuation conditions are set as follows: the initial wind speed is 11m / s, there is a gust from the 2nd to the 6th, and the maximum gust is 3m / s. Considering the wake effect and time lag effect, the specific input wind speed of each fan is calculated through the wake model. The simulation time is set to 20s.

[0046]The fault condition is set as follows: a two-phase ground short-circuit fault occurs at 50% of the line between bus 9 and bus 7 of the external system, and the fault time is...

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Abstract

The invention discloses a method for wind power plant equivalence based on a multi-objective optimization algorithm. According to the method, a fan is divided into K machine groups according to a K-means algorithm, and the interior of the each machine group is subjected to electric collection system equivalence and fan equivalence. A fan equivalence method is mainly improved. Based on wind speed fluctuation and fault conditions, to-be-identified parameters are selected according to a trace sensitivity method; the equivalent fan with the highest capacity is selected as a to-be-identified fan, and parameters of the equivalent fan are identified according to the NSGA-II multi-target optimization algorithm, so that a wind power plant equivalence model applicable to wind speed fluctuation and disturbance as well as fault disturbance is acquired.

Description

technical field [0001] The invention belongs to the field of electric power systems, and more specifically relates to a method for performing wind farm equivalents based on a multi-objective optimization algorithm. Background technique [0002] Since the beginning of the new century, the social economy has developed rapidly, the demand for energy has increased sharply, and the problem of energy shortage has become increasingly prominent. As a new energy generation technology with mature technology and good development prospects, wind power industry has developed rapidly in my country. According to data from the China Renewable Energy Society, from 2006 to 2016, my country's wind power installed capacity has been increasing year by year, and the cumulative installed capacity in 2016 has reached 169 million kilowatts. The World Meteorological Organization (WMO) estimates that the available wind energy on the earth is about 20 billion kilowatts, which is 10 times larger than th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62
CPCG06F30/367G06F2111/06G06F18/23213
Inventor 李坚黄琦王妮胡维昊王鹏张真源易建波井实蔡东升桂勋
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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