Optimal scheduling of distribution network side source network load storage considering dual-carbon targets in distribution market
CSTR:
Author:
Affiliation:

(1. Hangzhou Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd., Hnagzhou 310057, China;2. Zhejiang Qicheng Electronic Technology Co., Ltd., Hnagzhou 310028, China)

Clc Number:

TM73;F426

Fund Project:

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

    With the landing practice of electricity spot market, carbon emission allowances of distribution network and electricity spot prices will become factors that cannot be ignored in the Dispatching operation of the distribution network. dispatchable resources such as electric source, storage, and load, gradually become more and more abundant. Firstly, the model of“source-network-load-storage”on the distribution network side are proposed in the spot market environment, and at the same time, the paper conduct carbon emission benefit modeling for various power sources. Then power purchase benefits and carbon emission benefit optimization optimization scheduling model with multi- objective of power purchase cost and carbon emission benefit is established by considering the impact of the carbon trading price and regional quota limit. The effectiveness of the model is proved by using the pattern search algorithm to optimize the solution based on actual data. Finally, influence of the“source, load, storage”scale ratio,carbon emissions trading prices, the price of Chinese certified emission reduction and carbon allowances on dispatch operations is analyzed.

    Reference
    Related
    Cited by
Get Citation

姚志华,余 波,袁法培,王林炎,钟 鹏.考虑碳排放目标的配电网源网荷储优化调度探究[J].电力需求侧管理英文版,2023,25(3):80-86.

Copy
Related Videos

Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:December 05,2022
  • Revised:March 07,2023
  • Adopted:
  • Online: May 31,2023
  • Published:
Article QR Code