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Distribution network reactive power optimization control sequence determining method based on big data

A determination method and optimization control technology, applied in the field of distribution network, to achieve the effect of high calculation efficiency, accident prevention, and fast convergence speed

Active Publication Date: 2017-09-05
CHINA ELECTRIC POWER RES INST +2
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Problems solved by technology

[0009] The purpose of the present invention is to provide a method for determining the reactive power optimization control sequence of the distribution network based on big data, which solves the problem of reactive power operation optimization of the distribution network

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  • Distribution network reactive power optimization control sequence determining method based on big data
  • Distribution network reactive power optimization control sequence determining method based on big data
  • Distribution network reactive power optimization control sequence determining method based on big data

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Embodiment 1

[0054] The purpose of the present invention is to provide a method for determining a reactive power optimization control sequence of a distribution network based on big data. The present invention uses the existing historical load data and historical optimization data of the electric power system as the data source, and calculates the average spectral radius of the load random matrix by constructing the reactive power optimization random matrix of the distribution network and combining the single-loop law, and according to the average spectral radius, calculates The correlation coefficient between the historical load and the current load, by comparing the size of the correlation coefficient, obtains the load day with greater correlation, and takes the reactive power optimization control sequence of that day as the current optimization sequence.

[0055] The flow of the method for determining the reactive power optimization control sequence of the distribution network based on b...

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Abstract

The invention relates to a distribution network reactive power optimization control sequence determining method based on big data. The method comprises the following steps: taking the existing historical load data and historical optimization data of a power system as a data source; constructing a distribution network reactive power optimization random matrix; calculating the average spectral radius of the load random matrix based on the ring law; calculating the correlation coefficient of historical load and current load; obtaining a load day with larger correlation by comparing the values of correlation coefficient, and taking the reactive power optimization control sequence of the day as the current optimization sequence. Through the technical scheme of the invention, the problem concerning distribution network reactive power operation optimization is solved.

Description

technical field [0001] The present invention relates to the field of distribution network technology, and more specifically to a method for determining a reactive power optimization control sequence of a distribution network based on big data. Background technique [0002] Reactive power optimization of distribution network aims to improve voltage quality and reduce network loss. It uses reactive power compensation or regulating equipment as a control method, and belongs to nonlinear programming problems. Facing the high-dimensionality, strong coupling, and high randomness of distribution network data under the background of big data, the traditional reactive power optimization method based on linear programming or nonlinear programming mainly has the problem that it is difficult to obtain the global optimal solution. The reactive power optimization methods of artificial intelligence algorithms such as genetic algorithm, simulated annealing algorithm, and tabu search algorit...

Claims

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Application Information

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IPC IPC(8): H02J3/18
CPCH02J3/003H02J3/18H02J2203/20Y02E40/30
Inventor 刘科研盛万兴贾东梨李运华裴宏岩胡丽娟何开元叶学顺刁赢龙唐建岗董伟杰李雅洁
Owner CHINA ELECTRIC POWER RES INST
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