Research on Urban Load Rapid Recovery Strategy Based on Improved Weighted Power Flow Entropy
| Autor: | Min Wang, Zhou Jian, Fan Zongyin, Shanshan Shi |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.product_category
General Computer Science Linear programming Computer science 020209 energy electric vehicle General Engineering Evolutionary algorithm Process (computing) improved weighted power flow entropy Load recovery 02 engineering and technology Grid cold load pick-up TK1-9971 Control theory Electric vehicle 0202 electrical engineering electronic engineering information engineering Entropy (information theory) Process control General Materials Science Node (circuits) Electrical engineering. Electronics. Nuclear engineering business |
| Zdroj: | IEEE Access, Vol 9, Pp 10634-10644 (2021) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2021.3051186 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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