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ORIGINAL RESEARCH article

Front. Phys.
Sec. Social Physics
Volume 12 - 2024 | doi: 10.3389/fphy.2024.1514628
This article is part of the Research Topic Real-World Applications of Game Theory and Optimization, Volume II View all 5 articles

Low-Carbon Optimal Scheduling for Distribution Networks under Supply and Demand Uncertainty

Provisionally accepted
Nan Yu Nan Yu *Zhi Li Zhi Li Xin Gao Xin Gao
  • Henan Kaifeng Power Supply Company, Kaifeng, China

The final, formatted version of the article will be published soon.

    This paper presents a low-carbon optimal scheduling model for distribution networks with wind and photovoltaic (PV), accounting for supply and demand uncertainties. The model optimizes thermal generation costs, wind and PV maintenance costs, and carbon emissions using a chanceconstrained approach with fuzzy variables. The clear equivalent class method simplifies these constraints for easier problem-solving. Validation on the IEEE-30 node system shows the model reduces costs by 32.9% and carbon emissions by 19.2% compared to traditional scheduling, effectively lowering both costs and the carbon footprint. This real-world optimization approach tackles uncertainty in renewable energy supply and improves system efficiency and sustainability.

    Keywords: Low-carbon scheduling model, uncertainty, Chance-constrained approach, Distribution networks, Real-world optimization

    Received: 21 Oct 2024; Accepted: 05 Nov 2024.

    Copyright: © 2024 Yu, Li and Gao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Nan Yu, Henan Kaifeng Power Supply Company, Kaifeng, China

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