《无线互联科技》杂志社 ›› 2025, Vol. 22 ›› Issue (1): 114-117.

• 研究创新 • 上一篇    下一篇

基于边缘计算的发电行业数字化转型模型方法研究

陈忠勇   

  1. 华电金沙江上游水电开发有限公司,四川 成都 610041
  • 出版日期:2025-01-10 发布日期:2025-03-21
  • 作者简介:陈忠勇(1968— ),男,高级工程师,学士;研究方向:高海拔高寒条件下新能源电站建设,电力生产运营及相应数字化转型。

Research on the digital transformation model method of power generation industry based on edge computing

CHEN Zhongyong   

  1. Huadian Jinsha River Upstream Hydropower Development Co., Ltd., Chengdu 610041, China
  • Online:2025-01-10 Published:2025-03-21

摘要: 为提高电网发电中的能源转换效率,推进发电行业的数字化发展,文章引进边缘计算技术,开展发电行业数字化转型模型的构建研究。文章根据发电企业的实际需求,确定采集数据的类型,进行发电行业数字化生产数据的采集;利用采集的发电行业生产作业数据,引进边缘计算,进行电力生产调度的设计。文章明确电力生产过程中存在多种约束,选择混合整数线性规划算法,将发电行业数字化转型中的电力生产最优调度作为目标,生成基于多约束条件下的数字化转型模型。对比实验结果表明:设计方法应用后的能源转换效率显著提升,呈现出提升趋势,说明该方法可以实现对发电行业数字化转型发展的全面推进。

关键词: 边缘计算, 电力生产调度, 模型, 转型, 数字化, 发电行业

Abstract: In order to improve the energy conversion efficiency in the power generation and promote the digital development of the power generation industry, this paper introduces the edge computing technology and carries out the research on the construction of the digital transformation model of the power generation industry. According to the actual demand of power generation enterprises, the paper determines the type of data collection and collects the digital production data of power generation industry, introduces the power production scheduling, defines the power production process, selects the mixed integer linear planning algorithm, and takes the optimal dispatching of power generation industry as the goal to generate the digital transformation model based on multi-constraint condition. The comparative experimental results show that the energy conversion efficiency of the application of the design method is significantly improved, and shows a trend of improvement, indicating that the method can realize the comprehensive promotion of the digital transformation and development of the power generation industry.

Key words: edge computing, power production scheduling, model, transformation, digital, power generation industry

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