Industrial users participate in the distribution network cooperative dispatching of wind power consumption

Based on the in-depth analysis of wind power output characteristics, the practical feasibility of high load industrial users participating in wind power consumption is discussed. By analyzing the operation characteristics of enterprises in steel, chemical, non-ferrous metals and other industries, a strategy for distribution network scheduling is designed. By comparing with the actual running power curves of various industrial users, the validity of the established collaborative scheduling model of industrial users' participation in wind power consumption is confirmed, which lays a solid foundation for subsequent research on the participation of high-load energy loads in wind power consumption.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/ic2ecs64405.2024.10928404
Primary Topic
Nonlinear Dynamics and Pattern Formation
Type
article
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Industrial users participate in the distribution network cooperative dispatching of wind power consumption

Jian S. Dai, Xinyong Su, Xiaowei Wang, Kai Huang et al.
Nonlinear Dynamics and Pattern Formation
article

Industrial users participate in the distribution network cooperative dispatching of wind power consumption

Jian S. Dai, Xinyong Su, Xiaowei Wang, Kai Huang, H.J. Jing
article en

Abstract

Based on the in-depth analysis of wind power output characteristics, the practical feasibility of high load industrial users participating in wind power consumption is discussed. By analyzing the operation characteristics of enterprises in steel, chemical, non-ferrous metals and other industries, a strategy for distribution network scheduling is designed. By comparing with the actual running power curves of various industrial users, the validity of the established collaborative scheduling model of industrial users' participation in wind power consumption is confirmed, which lays a solid foundation for subsequent research on the participation of high-load energy loads in wind power consumption.

Inner Mongolia Electric Power (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 66%
Nonlinear Dynamics and Pattern Formation
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