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Deep power generation load prediction based power grid reactive power control method

A power generation load and power control technology, applied in reactive power compensation, AC networks with the same frequency from different sources, and single-network parallel feeding arrangements, etc. and other issues to achieve the effect of intelligent balance

Active Publication Date: 2019-11-19
STATE GRID FUJIAN ELECTRIC POWER CO LTD +2
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Problems solved by technology

[0002] There are many types of traditional modern power grid loads and distributed renewable energy sources, and the output fluctuates greatly
Different types of loads and changes in the output of distributed power sources cause deviations between the reactive power data of the grid power flow calculations and the actual node reactive power, which affects the accuracy of power flow calculations
The existing AVC is an ex-post control strategy, which cannot effectively meet the reactive power adjustment requirements of the grid under the circumstances of new energy generation and load reactive power fluctuations. Frequent adjustments will affect the service life of the adjustment equipment.

Method used

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  • Deep power generation load prediction based power grid reactive power control method
  • Deep power generation load prediction based power grid reactive power control method
  • Deep power generation load prediction based power grid reactive power control method

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Embodiment Construction

[0032] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0033] Such as figure 1 As shown, the present invention provides a grid reactive power control method based on deep power generation load forecasting. Firstly, the deep learning method is used to perform time-series progressive and accurate forecasting of the day-ahead and real-time power generation and load; then, according to the predicted value, reinforcement learning is used Optimal regulation of timing power flow based on the idea. The specific implementation steps of this method are as follows:

[0034] S1. Input the historical data of {time-power generation-load} for N days

[0035] For the accuracy of the algorithm, the present invention uses 3 years of power generation and load data for analysis, and divides the data into training data and test data at a ratio of 4:1.

[0036] The type of historical data is divided according t...

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Abstract

The invention relates to a deep power generation load prediction based power grid reactive power control method. The method includes adopting a deep learning method to perform time-series progressiveaccurate prediction on before-intraday and real-time generating capacity and loads; and adopting the thinking of reinforcement learning to perform the optimizing and adjusting of time-series power flow according to a predicted value. Through the accurate prediction on new energy power generation and loads, automatic adjusting can be performed on grid reactive power by utilizing reinforcement learning means, so that the intelligent balance of power flow reactive power of the grid can be realized.

Description

technical field [0001] The invention relates to the field of power grid planning and protection operation, and more specifically, to a reactive power control method of a power grid based on deep power generation load prediction. Background technique [0002] There are many types of traditional modern power grid loads and distributed renewable energy sources, and the output fluctuates greatly. Different types of loads and changes in the output of distributed power sources cause deviations between the reactive power data of the grid power flow calculation and the actual node reactive power, which affects the accuracy of the power flow calculation. The existing AVC is an ex-post control strategy, which cannot effectively respond to the reactive power adjustment requirements of the grid under the circumstances of new energy generation and load reactive power fluctuations, and frequent adjustments will affect the service life of the adjustment equipment. In order to solve this p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/06H02J3/50
CPCH02J3/06H02J3/50Y02E40/30
Inventor 唐雨晨林毅方朝雄吴威严通煜王康元
Owner STATE GRID FUJIAN ELECTRIC POWER CO LTD
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