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August 5, 2026Sustainability0 citationsOpen Access

Stochastic Source–Load Optimal Scheduling of an Integrated Energy System Considering Carbon–Green Certificate Market Synergy and Diversified Hydrogen Utilization

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YYYunyun YunKLKaidi LiZYZhaoguang Yang

Key Points

  • This research aims to develop a stochastic optimization method to enhance scheduling in integrated energy systems while addressing carbon emissions and operational costs.
  • Constructed an integrated 'electricity-carbon-hydrogen-methanol' model incorporating PEM electrolyzers and hydrogen fuel cells.
  • Integrated a concentrated solar power plant with an electric heater based on an 'electricity-heat-electricity' mechanism.
  • Applied Information Gap Decision Theory to manage uncertainties in energy source-load scheduling.
  • Achieved 100% renewable energy accommodation with thermal output from the electric heater-coupled CSP plant increased by 4.96%.
  • Reduced carbon emissions by 8.07% and natural gas procurement costs by 14.1% compared to the scenario without an electric heater.
  • Increased carbon trading revenues by 298.01% and lowered total operating costs by 39.6% with the joint CET-GCT mechanism.

Abstract

To address the challenges of restricted renewable energy accommodation, high carbon emissions, and elevated operating costs in integrated energy systems (IES), this paper proposes a stochastic optimization scheduling method that incorporates the synergy between carbon–green certificate trading and the multi-use applications of hydrogen energy. First, an integrated “electricity–carbon–hydrogen–methanol” model is constructed, incorporating proton exchange membrane (PEM) electrolyzers (ELs), methanol synthesis reactors, hydrogen storage systems, and hydrogen fuel cells (HFCs). Second, a concentrating solar power (CSP) plant coupled with an electric heater (EH) is integrated based on an “electricity–heat–electricity” mechanism. Concurrently, a joint carbon emission trading (CET) and green certificate trading (GCT) mechanism is incorporated into a low-carbon economic dispatch model to minimize total operational costs. On this basis, Information Gap Decision Theory (IGDT) is applied to address source–load uncertainties via risk-averse (RAS) and opportunity-seeking (OSS) strategies. Simulation results demonstrate that the proposed strategy achieves full accommodation of renewable energy. The EH-coupled CSP plant increases thermal output by 4.96%, reducing system carbon emissions by 8.07% compared with the non-EH scenario and decreasing natural gas procurement costs by 14.1%. Furthermore, the joint CET-GCT mechanism overcomes single-market limitations, increasing carbon trading revenues by 298.01% and lowering total operating costs by 39.6% compared with uncoordinated mechanisms. Finally, under IGDT uncertainty analysis, the opportunity-seeking strategy further reduces operating costs by 9.5% compared with the risk-averse strategy, enhancing the system’s low-carbon economic performance and operational flexibility. From the perspective of sustainable development, this study provides a practical dispatch framework for regional integrated energy systems to balance energy security, low-carbon transition and economic cost, offering methodological support for advancing the sustainable transformation of multi-energy systems amid the dual-carbon drive.

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Cite This Study

Yun et al. (2026) studied this question.

synapsesocial.com/papers/6a72e7d2226790f3706571dbhttps://doi.org/10.3390/su18157853
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