Multi-layer voltage control method for parallel quantum artificial emotion deep learning
A voltage control method and deep learning technology, applied in neural learning methods, quantum computers, electrical digital data processing, etc.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2021-05-14
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Abstract
Description
technical field
[0001] The invention belongs to the field of power system voltage control, and relates to a power system voltage control method based on an artificial intelligence method, which is suitable for controlling the voltage of a power system generator set. Background technique
[0002] Due to the current mismatch between the distribution of energy storage resources and economic development, the construction of a coordinated development of voltage networks at various levels has become the mainstream trend in the development of my country's power grid units. While the current grid system brings huge economic benefits, it also puts forward higher requirements for the accuracy, reliability and stability of the grid voltage, which brings great challenges to the coordinated control of the grid voltage. Therefore, it is of great significance to study the development of grid voltage coordination control. Among them, the prediction based on precise voltage command is the k...
Examples
Embodiment Construction
[0048] A multilayer voltage control method for parallel parallel quantum artificial emotion deep learning proposed by the present invention is described in detail in conjunction with the accompanying drawings as follows:
[0049] figure 1 It is the flow chart of the power system voltage prediction of the method of the present invention. First, build a parallel control system, respectively build a complex engineering control system model and an artificial engineering system model and form a closed-loop negative feedback mechanism. Then, the quantum walk search method is used as the artificial control model to search the target action solution of the current artificial system, and the control of the artificial model is completed, and the generated data parameters are mutually corrected with the complex control system; the deep neural network based on artificial emotion is used as the complex control system. The controller in the control link learns and trains the current voltag...