What Is the Optimal Solution for Scheduling Multiple Energy Systems? Overview and Analysis of Integrated Energy Co-Dispatch Models

Xiaozhi Gao, Han Xiao, Shiwei Xu, Hsiung-Cheng Lin () and Pengyu Chang
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Xiaozhi Gao: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Han Xiao: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Shiwei Xu: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Hsiung-Cheng Lin: Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Pengyu Chang: School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China

Energies, 2024, vol. 17, issue 18, 1-25

Abstract: With increasing dual pressure from global large energy consumption and environmental protection, multiple integrated energy systems (IESs) can provide more effective ways to achieve better energy utilization performance. However, in actual circumstances, many challenges have been brought to coupling multiple energy sources along with the uncertainty of each generated power to achieve efficient operation of IESs. To resolve this problem, this article reviews primary research on integrated energy optimization and scheduling technology to give constructive guidance in power systems. Firstly, the conceptual composition and classification of IESs are presented. Secondly, the coupling relationship between multiple energy sources based on mathematical expression is studied deeply. Thirdly, the scheduling of IESs with different types and regions is classified, analyzed, and summarized for clarification. Fourthly, on this basis, potential solutions for applications of key optimization technologies involved in the scheduling process in IESs can be found systematically. Finally, the future development trends to optimize scheduling integrated energy systems is explored and prospected in depth.

Keywords: integrated energy system; coupling relationship; optimize scheduling; model; solution method; technical challenges (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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