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Open AccessArticle
The Low-Carbon Path of Active Distribution Networks: A Two-Stage Model from Day-Ahead Reconfiguration to Real-Time Optimization
by
Taorong Jia
Taorong Jia ,
Guoqing Yang
Guoqing Yang * and
Lixiao Yao
Lixiao Yao
School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China
*
Author to whom correspondence should be addressed.
Energies 2024, 17(19), 4989; https://doi.org/10.3390/en17194989 (registering DOI)
Submission received: 21 August 2024
/
Revised: 30 September 2024
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Accepted: 4 October 2024
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Published: 6 October 2024
Abstract
The integration of renewable energy sources and distributed energy storage systems increasingly complicates the operation of distribution networks, while stringent carbon reduction targets demand low-carbon operational strategies. To address these complexities, this paper introduces a two-stage model for reconfiguring distribution networks and ensuring low-carbon dispatch. Initially, second-order cone programming is employed to minimize losses in the network. Subsequently, the outputs of renewable energy and energy storage systems are optimized using the mantis search algorithm (MSA) to achieve low-carbon dispatch, with the network’s carbon potential as the evaluation metric. The proposed model demonstrates a significant reduction in average active power loss by 34.85%, a decrease in daily carbon emissions by 509.97 kg, and a reduction in carbon emission costs by 17.24%, thereby markedly enhancing the economic and social benefits of grid operations.
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MDPI and ACS Style
Jia, T.; Yang, G.; Yao, L.
The Low-Carbon Path of Active Distribution Networks: A Two-Stage Model from Day-Ahead Reconfiguration to Real-Time Optimization. Energies 2024, 17, 4989.
https://doi.org/10.3390/en17194989
AMA Style
Jia T, Yang G, Yao L.
The Low-Carbon Path of Active Distribution Networks: A Two-Stage Model from Day-Ahead Reconfiguration to Real-Time Optimization. Energies. 2024; 17(19):4989.
https://doi.org/10.3390/en17194989
Chicago/Turabian Style
Jia, Taorong, Guoqing Yang, and Lixiao Yao.
2024. "The Low-Carbon Path of Active Distribution Networks: A Two-Stage Model from Day-Ahead Reconfiguration to Real-Time Optimization" Energies 17, no. 19: 4989.
https://doi.org/10.3390/en17194989
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