Space load forecasting considering distributed energy and electric vehicles
CSTR:
Author:
Affiliation:

(1. State Grid Anhui Electric Power Limited Company, Hefei 230022, China;2. State Grid Wuwei Power Supply Limited Company, Wuwei 238300, China;3. North China Electric Power University, Beijing 102206, China)

Clc Number:

TK018;TM715;U469.72

Fund Project:

This work is supported by National Natural Science Foundation of China(No. 51207050); Science and Technology Project of State Grid Corporation(No. SGAHJY00GHJS1700156)

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Compared with the traditional load forecasting,the spatial load forecasting pays more attention to the load distribution in a certain space, so it can better determine the selection and spatial layout of the electrical equipment. The rapid development of distributed energy and electric vehicles makes the urban spatial load distribution more complex. The original load forecasting method based on time series may bring large error, which is not conducive to the economy and reliability of urban power grid planning.Due to the nonlinear mapping ability of least squares support vector machine, a spatial load forecasting model for distributed and electric vehicle charging load is established. Finally, a practical example in a certain area of central China shows the effectiveness of the proposed method.

    Reference
    Related
    Cited by
Get Citation

蒯圣宇,田佳,台德群,王加庆,韩天轮.计及分布式能源与电动汽车接入的空间负荷预测[J].电力需求侧管理英文版,2019,21(1):47-51.

Copy
Related Videos

Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:September 28,2018
  • Revised:October 13,2018
  • Adopted:
  • Online: February 01,2019
  • Published:
Article QR Code