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author:

Shao, Zhenguo (Shao, Zhenguo.) [1] (Scholars:邵振国) | Lin, Yongqi (Lin, Yongqi.) [2] | Chen, Feixiong (Chen, Feixiong.) [3] (Scholars:陈飞雄) | Zheng, Xianghao (Zheng, Xianghao.) [4] | Guo, Yixin (Guo, Yixin.) [5] | Yan, Xiying (Yan, Xiying.) [6]

Indexed by:

EI Scopus PKU CSCD

Abstract:

In order to protect the information privacy of different operators in the integrated energy system (IES),balance the low-carbon and economy of the system operation and solve the problem that the robust model of natural gas network is difficult to solve,a distributionally robust low-carbon economic dispatch method of electricity-gas-heat IES considering the carbon-green certificate coupling mechanism is proposed. Considering the dynamic characteristics of natural gas and heat networks and the carbon-green certificate coupling mechanism,the dynamic low-carbon economic dispatch model of IES is constructed. In order to protect the data privacy of each network operator,a distributed collaborative optimization model of the electricity-gas-heat IES is constructed by decoupling the IES according to the energy coupling relationship. On this basis,considering the uncertainties of wind power output and multi-energy load,a distributionally robust optimization framework based on the consensus-based alternating direction method of multipliers is proposed. And the robust sub-problems with second-order cone constraints and binary variables are solved by using the second-order cone dual theory and alternative optimization method. A modified IEEE 39-bus electricity network,Belgium 20-node natural gas network and a 15-node heat network are taken as examples for simulation analysis. It is verified that the proposed method can realize the decentralized autonomous operation of each network in IES under the condition of uncertain source and load,while balancing the low-carbon and economy of system operation. © 2024 Electric Power Automation Equipment Press. All rights reserved.

Keyword:

Carbon Data privacy Dynamics Electric load dispatching Gases Natural gas Optimization Wind power

Community:

  • [ 1 ] [Shao, Zhenguo]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Lin, Yongqi]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Chen, Feixiong]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Zheng, Xianghao]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 5 ] [Guo, Yixin]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 6 ] [Yan, Xiying]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China

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Source :

Electric Power Automation Equipment

ISSN: 1006-6047

CN: 32-1318/TM

Year: 2024

Issue: 6

Volume: 44

Page: 50-58 and 76

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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