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Academic Journal of Energy, 2022, 3(2); doi: 10.38007/RE.2022.030201.

Power Network Planning Method of New Energy Consumption Based on Automatic Control Theory


Lixi Liu and Linyuan Fan

Corresponding Author:
Linyuan Fan

College of Mathematics and Data Science, Minjiang University, Fuzhou 350108, China


With the shortage of resources of traditional fossil energy and the increasingly serious problems of environmental pollution, wind power generation began to develop rapidly. Therefore, how to improve the absorption capacity of new energy and reduce wind abandonment new energy. In particular, as a major energy, Xinjiang wind has broad prospects for new energy development. "Abandoning wind and limiting power" is also very serious, which restricts the development of new energy. Therefore, in order to make up for the lack of local consumption capacity of level, this paper considers building power transmission channels across regions and countries, expanding the wind power balance area and reducing wind abandonment. In the context of large-scale access of new energy to the power grid, the power grid planning research is mainly based on the consumption capacity of new energy, and this method is applied to the actual power grid research in a province of China. Based on the actual data of a region in a province, a comprehensive calculation example is designed to simulate and analyze the contribution of various innovative consumption paths to the consumption of new energy; Two groups of different data are selected for simulation to reflect the relationship between the development scale of new energy and the demand for consumption capacity under different energy structure scenarios. Through simulation analysis, the technical feasibility and economy of comprehensive consumption of new energy are verified, in order to provide reference for other regions.


New Energy, Energy Consumption, Power Grid Planning, Automatic Control

Cite This Paper

Lixi Liu and Linyuan Fan. Power Network Planning Method of New Energy Consumption Based on Automatic Control Theory. Academic Journal of Energy (2022), Vol. 3, Issue 2: 1-9. https://doi.org/10.38007/RE.2022.030201.


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