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Distributed Robust Scheduling Optimization of Wind-Thermal-Storage System Based on Hybrid Carbon Trading and Wasserstein Fuzzy Set

Gang Wang*, Yuedong Wu, Xiaoyi Qian, Yi Zhao

Institute of Electric Power, Shenyang Institute of Engineering, Shenyang, 110036, China

* Corresponding Author: Gang Wang. Email: email

Energy Engineering 2024, 121(11), 3417-3435. https://doi.org/10.32604/ee.2024.052268

Abstract

A robust scheduling optimization method for wind–fire storage system distribution based on the mixed carbon trading mechanism is proposed to improve the rationality of carbon emission quota allocation while reducing the instability of large-scale wind power access systems. A hybrid carbon trading mechanism that combines short-term and long-term carbon trading is constructed, and a fuzzy set based on Wasserstein measurement is proposed to address the uncertainty of wind power access. Moreover, a robust scheduling optimization method for wind–fire storage systems is formed. Results of the multi scenario comparative analysis of practical cases show that the proposed method can deal with the uncertainty of large-scale wind power access and can effectively reduce operating costs and carbon emissions.

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APA Style
Wang, G., Wu, Y., Qian, X., Zhao, Y. (2024). Distributed robust scheduling optimization of wind-thermal-storage system based on hybrid carbon trading and wasserstein fuzzy set. Energy Engineering, 121(11), 3417-3435. https://doi.org/10.32604/ee.2024.052268
Vancouver Style
Wang G, Wu Y, Qian X, Zhao Y. Distributed robust scheduling optimization of wind-thermal-storage system based on hybrid carbon trading and wasserstein fuzzy set. Energ Eng. 2024;121(11):3417-3435 https://doi.org/10.32604/ee.2024.052268
IEEE Style
G. Wang, Y. Wu, X. Qian, and Y. Zhao, “Distributed Robust Scheduling Optimization of Wind-Thermal-Storage System Based on Hybrid Carbon Trading and Wasserstein Fuzzy Set,” Energ. Eng., vol. 121, no. 11, pp. 3417-3435, 2024. https://doi.org/10.32604/ee.2024.052268



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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