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Demonstrates a multi-objective optimization framework to improve sustainability in electricity-hydrogen multi-microgrids, indicating better resource management and emissions reduction.
To enhance the sustainable operation of electricity–hydrogen coupling multi-microgrids (EHCMMG), this study proposes a multi-objective dispatch optimization framework driven by electricity price prediction. Although EHCMMG plays a vital role in renewable energy integration and multi-energy synergy, three major sustainability-related research gaps remain: insufficient consideration of cross-regional, multi-market, and multi-stakeholder interests; inadequate electricity–hydrogen demand response mechanisms; and limited investigation of uncertainty modeling that balances economy and security. To address these issues, this study first designs an EHCMMG architecture that supports electric-hydrogen interactions both within and outside the cluster. An electricity price prediction-driven multi-objective dispatch optimization model oriented toward multiple stakeholders is then proposed. This model incorporates incentive-based electricity–hydrogen demand response and constraints on carbon emissions. Moreover, operational uncertainties arising from renewable energy generation are addressed through the coordinated integration of spinning reserve capacity constraint and chance-constrained programming. The results show that the cluster cost, the market integrated operator (MIO) net revenue, user energy cost, and total carbon emissions are CNY 17.502 million, CNY 12.684 million, CNY 5.556 million, and 8168.126 tons in baseline scenario, respectively. The proposed model effectively balances economic efficiency, operational reliability, and low-carbon performance, thereby enhancing the overall sustainability of the EHCMMG.
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Lu et al. (2026) studied this question.
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