Dynamic programming-based low-carbon and economic scheduling of integrated energy system

Jin Ye, Qilin Shuai and Qingsong Hua

Energy, 2025, vol. 322, issue C

Abstract: The extensive exploitation of traditional energy sources has significantly intensified pressure on environmental protection, making carbon emission reduction a critical strategy to mitigate global warming. Integrated energy systems (IES), based on multi-energy coupling and complementarity, offer a promising approach to enhance renewable energy consumption, improve energy efficiency, and enable low-carbon operation. However, uncertainties in renewable energy generation and user demand present challenges for optimizing IES operation and scheduling. To address these, power-to-gas (P2G) technology, acting as both a renewable energy consumption and CO2 absorption facility, is incorporated into the IES to facilitate electricity-heat-gas cogeneration. Additionally, a carbon emission factor is integrated into the optimization objective, providing a comprehensive assessment of the system's economic and environmental benefits. A multi-objective optimization model is developed, with constraints on energy balance, equipment capacity, and energy storage or release. Dynamic programming (DP) is applied to solve the model and obtain real-time system outputs for the next 24 h, balancing economic and environmental goals. Sensitivity analyses of energy storage capacity and carbon tax price are performed to explore their impacts on system scheduling optimization.

Keywords: Scheduling optimization; Integrated energy system; Power to gas; Dynamic programming (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:322:y:2025:i:c:s0360544225012101

DOI: 10.1016/j.energy.2025.135568

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