4.6 Article

Research on Urban Load Rapid Recovery Strategy Based on Improved Weighted Power Flow Entropy

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 10634-10644

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3051186

Keywords

Electric vehicles; Load modeling; Load flow; Entropy; Process control; Linear programming; Discharges (electric); Load recovery; electric vehicle; cold load pick-up; improved weighted power flow entropy

Funding

  1. State Grid Shanghai Electric Power Company [B30940190004]

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This study focuses on load restoration in power system restoration, considering the sudden increase in load and the auxiliary effect of electric vehicle discharge. It establishes a fast and safe load recovery model, optimizing it using a multi-objective evolutionary algorithm based on decomposition. The proposed method is verified to effectively establish a load recovery plan that meets the actual grid environment.
As the final stage of power system restoration, the critical task of load restoration is to restore the remaining load as quickly as possible. With the continuous increase of the temperature-controlled load and the proportion of electric vehicle load in the urban power grid, the complexity of the load side in the restoration process gradually increases. Therefore, based on the existing grid environment, this paper considers the sudden increase in load recovery caused by cold load pick-up and the auxiliary effect of electric vehicle discharge on load recovery during the load recovery process. From the perspective of economy, safety, and speed, this paper establishes a multi-objective function that includes the amount of load, improved weighted power flow entropy, and the number of recovered lines. The multi-objective evolutionary algorithm based on decomposition is used to optimize the constructed multi-objective load recovery model. Through the IEEE30 node system, it is verified that the method proposed in this paper can effectively establish a fast and safe load recovery plan that meets the actual grid environment.

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