Optimized scheduling of the park-integrated energy system considering the multiple-demand coupling response characteristics

This article first constructs a two-sided supply-demand coupling model considering demand-side energy storage and establishes the comprehensive demand response elastic matrix model based on the elastic response characteristics of electric load price. Secondly, the optimal scheduling model of the integrated energy system (IES) in the park, considering the coupled response characteristics of multiple demands is constructed. By optimizing the operation parameters of equipment on supply and demand of the park, the coordinated optimization of energy in the park is realized. To conclude, the reliability and effectiveness of the model are verified by means of simulation tests.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1117/12.3050199
Primary Topic
Smart Grid Energy Management
Type
article
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Optimized scheduling of the park-integrated energy system considering the multiple-demand coupling response characteristics

Jianghao AN
Smart Grid Energy Management
article

Optimized scheduling of the park-integrated energy system considering the multiple-demand coupling response characteristics

Jianghao AN
article en

Abstract

This article first constructs a two-sided supply-demand coupling model considering demand-side energy storage and establishes the comprehensive demand response elastic matrix model based on the elastic response characteristics of electric load price. Secondly, the optimal scheduling model of the integrated energy system (IES) in the park, considering the coupled response characteristics of multiple demands is constructed. By optimizing the operation parameters of equipment on supply and demand of the park, the coordinated optimization of energy in the park is realized. To conclude, the reliability and effectiveness of the model are verified by means of simulation tests.

Changsha University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 80%
Smart Grid Energy Management
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