Two-stage low-carbon dispatch of integrated energy system considering locational fairness of nodal carbon intensity

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a novel method combining carbon emission flow with Shapley value for fair carbon pricing in IES, useful for further research in carbon accounting and dispatch optimization.

🏢実務担当者:Offers a practical framework for energy utilities and grid operators to implement fair carbon pricing and demand response, potentially reducing costs and emissions.

🏛政策担当者:Highlights the importance of locational fairness in carbon pricing mechanisms, informing policy design for carbon markets and grid decarbonization.

Integrated energy systems (IESs) integrate multiple energy carriers and provide an effective way to improve energy efficiency and decarbonization. However, existing low-carbon dispatch methods still face challenges in fair carbon responsibility allocation and effective demand-side carbon reduction. In particular, the fairness issue caused by node location in nodal carbon intensity (NCI) calculation has not been well addressed. To address these issues, this paper proposes a two-stage low-carbon dispatch framework for electricity-heat-gas IESs considering the locational fairness of NCI based on carbon emission flow (CEF) theory. First, a unified CEF model for an IES is established by considering differences in carbon carriers among multiple energy forms and the carbon transfer characteristics of energy conversion devices. Second, an improved NCI index is developed to reduce unfair carbon responsibility allocation. On this basis, to support carbon-price-based demand response, high-, medium-, and low-carbon responsibility intervals are identified using the Shapley value, based on which a stepped carbon pricing mechanism is established. Finally, a two-stage low-carbon dispatch framework is developed, with pre-dispatch to enable NCI calculation in the first stage and redispatch with low-carbon-oriented demand response in the second stage. The model is solved through distributionally robust optimization and adaptive alternating direction method of multipliers to coordinate optimizations of the distribution network and microgrid loads. Compared with the demand response method based on the original NCI, the proposed method improves the carbon reduction effect by 21.2% and reduces the total cost by 1% in a 33-6-6-bus electricity-heat-gas IES.

• openalex https://doi.org/10.1016/j.ecmx.2026.102219first seen 2026-08-15 04:51:44