A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources

Introduction: With the increasing demand for energy utilization efficiency and minimization of environmental carbon emissions in industrial parks, optimizing the configuration and scheduling of integrated energy systems has become crucial. This study focuses on integrated energy systems with massive flexible load resources, aiming to maximize energy utilization efficiency while reducing environmental impact. Methods: To model the uncertainties in wind and solar power outputs, we employed three-parameter Weibull distribution models and Beta distribution models. Flexible loads were categorized into three types to match different electricity consumption patterns. Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. The effectiveness of the proposed optimization scheduling and configuration methods was validated through a case study of an industrial park located in a coastal area of southeastern China. Results: The results show that using three-parameter Weibull distribution models and Beta distribution models more accurately reflects the variations in actual wind speeds and solar irradiance levels, achieving peak shaving and valley filling effects and enhancing renewable energy utilization. The EKOA algorithm significantly reduced curtailment rates of wind and solar power generation while achieving substantial economic benefits. Compared with other operation modes of hydrogen, the daily average cost is reduced by 12.92%, and external electricity purchases are reduced by an average of 20.2 MW h/day. Discussion: Although our approach shows potential in improving energy utilization efficiency and economic gains, this paper only considered hydrogen energy for single-use pathways and did not account for the economic benefits from selling hydrogen in the market. Future research will further incorporate hydrogen demand response mechanisms and optimize the output of integrated energy systems from the perspective of spot markets. These findings provide valuable references for relevant engineering applications.

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Publication Details

Journal
Frontiers in Energy Research
Published
2025-03-19
DOI
https://doi.org/10.3389/fenrg.2025.1556000
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73
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article

A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources

Hanwen Ni, Jun Zhang, Shouyang Wang, Zihao Wang et al.
1 citations
Frontiers in Energy Research
Integrated Energy Systems Optimization
0.73
article

A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources

Hanwen Ni, Jun Zhang, Shouyang Wang, Zihao Wang, Jinghua Wang
article en
1 citations

Abstract

Introduction: With the increasing demand for energy utilization efficiency and minimization of environmental carbon emissions in industrial parks, optimizing the configuration and scheduling of integrated energy systems has become crucial. This study focuses on integrated energy systems with massive flexible load resources, aiming to maximize energy utilization efficiency while reducing environmental impact. Methods: To model the uncertainties in wind and solar power outputs, we employed three-parameter Weibull distribution models and Beta distribution models. Flexible loads were categorized into three types to match different electricity consumption patterns. Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. The effectiveness of the proposed optimization scheduling and configuration methods was validated through a case study of an industrial park located in a coastal area of southeastern China. Results: The results show that using three-parameter Weibull distribution models and Beta distribution models more accurately reflects the variations in actual wind speeds and solar irradiance levels, achieving peak shaving and valley filling effects and enhancing renewable energy utilization. The EKOA algorithm significantly reduced curtailment rates of wind and solar power generation while achieving substantial economic benefits. Compared with other operation modes of hydrogen, the daily average cost is reduced by 12.92%, and external electricity purchases are reduced by an average of 20.2 MW h/day. Discussion: Although our approach shows potential in improving energy utilization efficiency and economic gains, this paper only considered hydrogen energy for single-use pathways and did not account for the economic benefits from selling hydrogen in the market. Future research will further incorporate hydrogen demand response mechanisms and optimize the output of integrated energy systems from the perspective of spot markets. These findings provide valuable references for relevant engineering applications.

Frontiers in Energy ResearchVol. 13
China Three Gorges University (CN), State Grid Corporation of China (China) (CN)
Openalex Percentile: Top 30%
Integrated Energy Systems Optimization
0.73
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