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[期刊论文]

Bi-level Optimal Dispatching of Power System Based on Demand Response Considering Nodal Carbon Intensity

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author:

Liang, Ning (Liang, Ning.) [1] | Fang, Qian (Fang, Qian.) [2] | Xu, Huihui (Xu, Huihui.) [3] | Unfold

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EI Scopus PKU CSCD

Abstract:

In order to realize the low-carbon emission of power system and boost the economic growth, a bi-level optimal dispatching strategy based on the demand response considering nodal carbon intensity is proposed, which uses the model of carbon intensity guided multivariate flexible load as basic. First, by using the principle of proportional sharing to track the carbon emission flow, a carbon emission flow model is built, and the carbon intensity variation law of each node is perceived from a spatiotemporal dimension. Then, the carbon flow analysis is incorporated into the load-side demand response mechanism, the nodal carbon intensity is used to establish the carbon emission model of demand response for load aggregators, and the dispatching differences of load aggregators under different carbon intensities are clarified to build a bi-level optimal dispatching model of power system based on demand response considering nodal carbon intensity. The upper-level of the model is the optimal economic dispatching of power grid operators, and the lower-level of the model is the demand response economic dispatching of load aggregators. Finally, the effectiveness of the proposed method is verified by a modified IEEE 30-bus system. © 2024 Automation of Electric Power Systems Press. All rights reserved.

Keyword:

Carbon Economic analysis Electric load dispatching Electric power system economics

Community:

  • [ 1 ] [Liang, Ning]Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming; 650500, China
  • [ 2 ] [Fang, Qian]Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming; 650500, China
  • [ 3 ] [Xu, Huihui]Institute of Economic Technology, State Grid Gansu Electric Power Company, Lanzhou; 730000, China
  • [ 4 ] [Zheng, Feng]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350000, China
  • [ 5 ] [Miao, Meng]Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming; 650500, China

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Source :

Automation of Electric Power Systems

ISSN: 1000-1026

CN: 32-1180/TP

Year: 2024

Issue: 9

Volume: 48

Page: 44-53

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

30 Days PV: 2

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