Photovoltaic power distribution network reactive voltage prediction method and system based on recurrent neural network

Abstract

The invention discloses a photovoltaic power distribution network reactive voltage prediction method and system based on a recurrent neural network. According to the technical scheme, the method comprises: establishing a voltage prediction framework based on the high-proportion photovoltaic power distribution network; analyzing and processing the reactive voltage historical data of the high-proportion photovoltaic power distribution network, namely analyzing key factors influencing global reactive voltage characteristics, and preprocessing reactive voltage in combination with the existing reactive voltage historical data of the high-proportion photovoltaic power distribution network; and establishing a reactive voltage prediction strategy containing the high-proportion photovoltaic power distribution network: carrying out variational mode decomposition on the processed voltage sequence, decomposing the voltage sequence into a plurality of components with different characteristics, thenrespectively inputting each component into a recurrent neural network, and superposing prediction results of each component to obtain a final prediction value. According to the invention, the electric energy quality is improved, the safety and stability of power grid operation are improved, energy conservation and loss reduction can be realized through reactive compensation and other modes, and the operation economy and reliability are improved.

Description

technical field [0001] The invention relates to the field of voltage prediction of a distribution network with a high proportion of photovoltaics, in particular to a method and system for predicting reactive power and voltage of a photovoltaic distribution network based on a cyclic neural network. Background technique [0002] With the high proportion of photovoltaic power stations connected, it has a great impact on the voltage level and power quality of the distribution network. The connection of large-scale photovoltaic power stations will have an impact on the voltage of the distribution network, and may even cause voltage stability problems. ; In addition, changes in the output current of the photovoltaic power generation system will also cause voltage fluctuations, making the voltage on the load side exceed the limit, and it is greatly affected by light and temperature, which will aggravate voltage fluctuations. [0003] A high proportion of photovoltaics (generally be...

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Problems solved by technology

[0002] With the high proportion of photovoltaic power stations connected, it has a great impact on the voltage level and power quality of the distribution network. The connection of large-scale photovoltaic power stations will have an impact on the voltage of the distribution network, and may even cause voltage stability problems. ;In addition, changes in the output current of the photovoltaic power generation system will also cause voltage fluctuations, which will cause the voltage on the load side to exceed the limit, and it is greatly affected by light and temperature, which will aggravate voltage fluctuations

[0003] A high proportion of photovoltaics (generally believed that photovoltaic power generation accounts for 20-40% of the total power generation) connected to the grid has a serious impact on the safe operation of the system. It is imminent to intelligently predict the global reactive power voltage of the distribution network with a high proportion of photovoltaic distribution network. However, although the current distribution network prediction technology has been vigorously developed, the current various prediction methods Mature, how to carry out in-depth fusion and analysis of the prediction results has not been effectively processed, and it has very strong practical significance to carry out in-depth research on voltage prediction of distribution networks containing photovoltaics

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