Study on multi-energy scheduling strategy considering dynamic energy prices and low-carbon demand response

Xin Su, Qian Zhang, YangDong Lu, RuiYi Hao, TianXi Qin, ChunYan Li, ShengWei Huang and KeFan Bi

Renewable Energy, 2025, vol. 247, issue C

Abstract: Addressing the coupling issue between dynamic energy prices and low-carbon demand response under a low-carbon context, this paper proposes a multi-energy scheduling strategy considering dynamic energy prices and low-carbon demand response. First, in the Regional Integrated Energy Service Provider (RIESP), a time-varying carbon flow state model is established based on carbon emission flow theory, tracing the carbon flow from the input to the output end. A dynamic response willingness model for user participation in demand response is developed under the influence of multi-factor signals, stimulating the low-carbon potential of users through environmental awareness. Meanwhile, dynamic energy prices are constructed under multi-factor signals to guide users to consume energy during low-carbon periods. Then, through the coupling effect of dynamic energy prices and users' low-carbon response willingness, the collaborative low-carbon optimization potential of the “source-load” system is further explored. The problem is formulated as a bi-level optimization problem, and the optimal solution is obtained through iterative interaction between the upper and lower levels. Finally, a case study is conducted to verify the proposed strategy. The results show that, after implementing the proposed strategy, the system's energy purchasing cost is reduced by 10.27 %, carbon emissions are reduced by 2525.25 kg, and the renewable energy absorption rate is increased by 7.66 %.

Keywords: Carbon emission flow; Time-varying carbon emission factor; Dynamic pricing; Low-carbon demand response; Multi energy system (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:247:y:2025:i:c:s0960148125007104

DOI: 10.1016/j.renene.2025.123048

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