基于CART决策树的110 kV供电区域分布式光伏承载能力测算模型

代守乐, 李萍

代守乐, 李萍. 基于CART决策树的110 kV供电区域分布式光伏承载能力测算模型[J]. 分布式能源, 2024, 9(3): 82-88. DOI: 10.16513/j.2096-2185.DE.2409310
引用本文: 代守乐, 李萍. 基于CART决策树的110 kV供电区域分布式光伏承载能力测算模型[J]. 分布式能源, 2024, 9(3): 82-88. DOI: 10.16513/j.2096-2185.DE.2409310
DAI Shou-le, LI Ping. Calculation Model of Distributed Photovoltaic Carrying Capacity for 110 kV Power Supply Area Based on CART Decision Tree[J]. Distributed Energy, 2024, 9(3): 82-88. DOI: 10.16513/j.2096-2185.DE.2409310
Citation: DAI Shou-le, LI Ping. Calculation Model of Distributed Photovoltaic Carrying Capacity for 110 kV Power Supply Area Based on CART Decision Tree[J]. Distributed Energy, 2024, 9(3): 82-88. DOI: 10.16513/j.2096-2185.DE.2409310

基于CART决策树的110 kV供电区域分布式光伏承载能力测算模型

详细信息
    作者简介:

    代守乐(1987),男,硕士,工程师,主要研究方向为工厂供电技术、高压变频器与高压电机速度控制等,yaluben8nf@163.com;李萍(1984),女,学士,助理工程师,主要研究方向为工厂供电技术、自动化仪表技术等

  • 中图分类号: TM615

Calculation Model of Distributed Photovoltaic Carrying Capacity for 110 kV Power Supply Area Based on CART Decision Tree

  • 摘要: 分布式光伏受天气影响较大,测算110 kV供电区域的分布式光伏承载能力,对区域供电来说意义重大。基于此,提出基于分类与回归树(calssification and regression tree, CART)的110 kV供电区域分布式光伏承载能力测算模型。该模型以分布式电源输出功率、区域分布式电源发电量占比、局部分布式电源线损增量等数据为基础,利用CART决策树建立110 kV供电区域分布式光伏承载能力测算模型,并使用改进鲸鱼优化算法求解测算结果。经实验测试发现,该模型对分布式光伏承载能力的测算精准度较高,可有效测算不同实验区域在不同季节时的分布式光伏承载能力,具有较高的应用价值。
    Abstract: Distributed photovoltaics are greatly affected by weather conditions, and calculating the carrying capacity of distributed photovoltaics in 110 kV power supply areas is of great significance for regional power supply. A calculation model of distributed photovoltaic carrying capacity for 110 kV power supply areas based on classification and regression trees(CART) is proposed to address this issue. This model is based on the output power of distributed power sources, the proportion of regional distributed power generation, and the incremental line loss of local distributed power sources, etc. Using the CART decision tree, a calculation model of the distributed photovoltaic carrying capacity for 110 kV power supply areas is established, and the improved whale optimization algorithm is used to solve the calculation results. After experimental testing, it is found that the model has higher accuracy in calculating the distributed photovoltaic carrying capacity. This indicates that the method can effectively calculate the distributed photovoltaic carrying capacity of different experimental areas in different seasons, and has high application value.
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出版历程
  • 收稿日期:  2024-01-03
  • 刊出日期:  2024-06-27

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