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Optimization scheduling of microgrid comprehensive demand response load considering user satisfaction.
Wang, Chaoliang; Li, Xiong.
Afiliação
  • Wang C; State Grid Zhejiang Marketing Service Centre, Hangzhou, Zhejiang, China. 15575525348@163.com.
  • Li X; State Grid Zhejiang Marketing Service Centre, Hangzhou, Zhejiang, China.
Sci Rep ; 14(1): 16034, 2024 Jul 11.
Article em En | MEDLINE | ID: mdl-38992090
ABSTRACT
The original load control model of microgrid based on demand response lacks the factors of incentive demand response, the overall satisfaction of users is low, the degree of demand response is low, the Time Of Use (TOU) price of peak-valley filling capacity is weak, and the peak-valley difference of load curve is large. Regarding the limitations of the current microgrid demand response model, this study further optimizes the flexible load control strategy and proposes a two-objective optimization model based on price and incentive. Meanwhile, the model is solved using an improved chaotic particle group algorithm. Finally, the microgrid load data were selected for simulation analysis. The simulation results showed that the comprehensive demand response of flexible control model proposed increased the overall satisfaction of users by 9.51%, the overall operating cost of microgrid suppliers decreased by 12.975/ten thousand yuan, the peak valley difference decreased by 4.61%, and the user demand response increased by 27.24%. The model effectively improves the overall profit of the supply side of the microgrid, improves the user satisfaction, and maximizes the linkage benefits of the supply and demand of the micro grid. In addition, the model effectively reduces the phenomenon of distributed power supply in the microgrid, and realizes the supply and demand matching of the whole load in the microgrid.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article