Distribution network low-carbon operation grid-side energy storage

Deep Reinforcement Learning-Based Joint Low-Carbon

This study offers an innovative perspective on the synergistic optimization of SES with DN and provides a practical methodology for low-carbon economic dispatch in power systems.

2025 Apr 09

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Low-carbon planning model for distribution network considering

This paper, therefore, proposes a low-carbon planning method for distribution networks that comprehensively considers VES resources, renewable energy, and their

2025 Aug 08

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Net-zero power: Long-duration energy storage for a renewable grid

As the world transitions to decarbonized energy systems, emerging long-duration energy storage technologies will be critical for supporting the widescale deployment of

2025 Dec 15

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Distribution network low-carbon operation grid-side energy

Under conditions ensuring reliable grid operation, a distribution network system equipped with energy storage and a tiered carbon pricing mechanism can achieve a 10.7% reduction in

2025 Nov 28

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Low-carbon scheduling of mobile energy storage in distribution

These findings validate the model''s ability to balance economic benefits and low-carbon operational goals, providing a practical and effective solution for the optimal scheduling

2025 Oct 02

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Energy Storage Scheduling Strategy Based on Dynamic Carbon

To address the aforementioned issues, this paper establishes a precise carbon emission model for energy storage in the distribution transformer area. It combines the

2025 May 17

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Multivariate low-carbon scheduling of distribution network based

This paper proposes a low-carbon economic optimization scheduling model for the distribution network, considering an improved dynamic carbon emission factor to shift carbon

2025 Jun 04

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Optimized operation of energy storage in distribution networks

With the advancement of carbon peaking and carbon neutrality goals and the evolution of new power systems, the carbon market and energy storage systems have become essential

2025 Dec 07

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Deep Reinforcement Learning-Based Joint Low-Carbon

This study focuses on optimizing shared energy storage (SES) and distribution networks (DNs) using deep reinforcement learning (DRL) techniques to enhance operation

2025 Mar 25

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Energy Storage Scheduling Strategy Based on Dynamic

To address the aforementioned issues, this paper establishes a precise carbon emis-sion model for energy storage in the distribution transformer area. It combines the influ-ence of carbon

2025 Sep 05

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