Optimization Strategies for Flexibility-Oriented Supply–Demand Matching in Industrial Park Integrated Energy Supply Systems: A Review of Modeling, Scheduling, and Flexibility Utilization

The low-carbon transition of industrial parks is driving an increasing demand for advanced energy systems. Integrated energy supply systems (IESSs), which couple multiple energy forms, offer a critical pathway to alleviate the high-carbon intensity of energy structures and supply–demand imbalances in industrial parks by enhancing energy efficiency and reducing carbon emissions. The rapid advancement of energy storage technologies, multi-energy system modeling, and advanced energy management strategies has further propelled the research and application of IESSs. This review comprehensively delineates the distinctions between IESSs and traditional energy systems, highlighting the architecture and operational characteristics of IESSs to elucidate the impacts of multi-energy coupling and source–grid–load–storage interactions. We examine existing equipment and system modeling approaches and load modeling methods, and discuss modeling techniques for variable operating conditions. We analyze operational optimization methods for IESSs under deterministic, multi-time-scale, and uncertain conditions, and investigate the utilization mechanisms of flexibility resources across source–grid–load–storage links to illustrate how system flexibility supports dynamic supply–demand coordination. The review also identifies emerging trends in AI-driven IESS operation, highlighting the integration of physics-informed modeling, large language models, and multi-agent systems. This review establishes a unified analytical perspective for flexible supply–demand matching within IESSs, offering theoretical support for the development of future low-carbon industrial energy systems.

Authors

Institutions

Publication Details

Journal
Energies
Published
2026-04-14
DOI
https://doi.org/10.3390/en19081903
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization Strategies for Flexibility-Oriented Supply–Demand Matching in Industrial Park Integrated Energy Supply Systems: A Review of Modeling, Scheduling, and Flexibility Utilization

Xiaojie Lin, Hailong Zhang, Xingtao Tian, Jing Li et al.
Energies
Integrated Energy Systems Optimization
article

Optimization Strategies for Flexibility-Oriented Supply–Demand Matching in Industrial Park Integrated Energy Supply Systems: A Review of Modeling, Scheduling, and Flexibility Utilization

Xiaojie Lin, Hailong Zhang, Xingtao Tian, Jing Li, Xueru Lin, Wei Zhong
article en

Abstract

The low-carbon transition of industrial parks is driving an increasing demand for advanced energy systems. Integrated energy supply systems (IESSs), which couple multiple energy forms, offer a critical pathway to alleviate the high-carbon intensity of energy structures and supply–demand imbalances in industrial parks by enhancing energy efficiency and reducing carbon emissions. The rapid advancement of energy storage technologies, multi-energy system modeling, and advanced energy management strategies has further propelled the research and application of IESSs. This review comprehensively delineates the distinctions between IESSs and traditional energy systems, highlighting the architecture and operational characteristics of IESSs to elucidate the impacts of multi-energy coupling and source–grid–load–storage interactions. We examine existing equipment and system modeling approaches and load modeling methods, and discuss modeling techniques for variable operating conditions. We analyze operational optimization methods for IESSs under deterministic, multi-time-scale, and uncertain conditions, and investigate the utilization mechanisms of flexibility resources across source–grid–load–storage links to illustrate how system flexibility supports dynamic supply–demand coordination. The review also identifies emerging trends in AI-driven IESS operation, highlighting the integration of physics-informed modeling, large language models, and multi-agent systems. This review establishes a unified analytical perspective for flexible supply–demand matching within IESSs, offering theoretical support for the development of future low-carbon industrial energy systems.

EnergiesVol. 19(8)
North China Electric Power University (CN), Zhejiang Energy Research Institute (CN), Hangzhou City University, Zhejiang University (CN), Taiyuan University of Technology (CN)
State Key Laboratory Of Alternate Electrical Power System With Renewable Energy Sources, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 24%
Integrated Energy Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.