考虑精细化碳交易的共享储能多微网系统经济调度

艾欣; 张瑛楠; 潘玺安

doi:doi:10.19912/j.0254-0096.tynxb.2024-1014

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考虑精细化碳交易的共享储能多微网系统经济调度

更新时间：2025-12-17

- 考虑精细化碳交易的共享储能多微网系统经济调度
- Issue 10, Pages: 65-76(2025)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1014
  CLC： M715
- Published Online：31 October 2025，
  
  Published：31 October 2025
- 稿件说明：
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艾欣, 张瑛楠, 潘玺安. 考虑精细化碳交易的共享储能多微网系统经济调度[J]. 2025, (10): 65-76.
DOI：

艾欣, 张瑛楠, 潘玺安. 考虑精细化碳交易的共享储能多微网系统经济调度[J]. 2025, (10): 65-76. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1014.

摘要

为提升配电系统的低碳经济性

首先构建多微网共享储能系统协同优化调度框架

同时为在充分考虑碳交易市场供需关系的基础上实现减排激励的灵活调整与精细刻画

提出基于动态碳价和碳配额供求关系的精细化碳交易成本计算方法;然后

为在提升多微网共享储能系统在实时阶段的功率决策时效性的同时增强决策模型对含不确定性因素的风光出力时序信息的感知能力

提出一种结合长短期记忆网络与多智能体近端策略优化方法的强化学习算法;最后

在IEEE 33节点系统中对所提模型与方法在系统低碳运行能力、运行经济性与决策时效性等方面的提升作用进行仿真验证。

Abstract

In order to improve the low-carbon economy of the distribution system

this paper first constructs the collaborative optimization scheduling framework of multi microgrid shared energy storage system. At the same time

in order to realize the flexible adjustment and fine characterization of emission reduction incentives on the basis of fully considering the supply-demand relationship of the carbon trading market

a refined carbon trading cost calculation method based on the dynamic carbon price and carbon quota supply-demand relationship is proposed; Then

in order to improve the timeliness of power decision-making in the real-time phase of the multi microgrid shared energy storage system and enhance the ability of the decision-making model to perceive the time-series information of wind and solar output with uncertain factors

a reinforcement learning algorithm combining short-term and long-term memory network and multi-agent near end strategy optimization method is proposed; Finally

in IEEE 33 bus system

the improvement effect of the proposed model and method on the low-carbon operation ability

operation economy and decision timeliness of the system is verified by simulation.

关键词

Keywords

references

栗峰, 丁杰, 周才期, 等. 新型电力系统下分布式光伏规模化并网运行关键技术探讨[J]. 电网技术, 2024, 48(1): 184-199.

DAI R, ESMAEILBEIGI R, CHARKHGARD H.The utilization of shared energy storage in energy systems: a comprehensive review[J]. IEEE transactions on smart grid, 2021, 12(4): 3163-3174.

ZHU H, LI H, LIU G J, et al.Energy storage in high variable renewable energy penetration power systems: technologies and applications[J]. CSEE journal of power and energy systems, 2023, 9(6): 2099-2108.

刘畅, 卓建坤, 赵东明, 等. 利用储能系统实现可再生能源微电网灵活安全运行的研究综述[J]. 中国电机工程学报, 2020, 40(1): 1-18, 369.

LI L X, CAO X L, ZHANG S.Shared energy storage system for prosumers in a community: investment decision, economic operation, and benefits allocation under a cost-effective way[J]. Journal of energy storage, 2022, 50: 104710.

LU J G, ZHENG W J, YU Z W, et al.Optimizing grid-connected multi-microgrid systems with shared energy storage for enhanced local energy consumption[J]. IEEE access, 2024, 12: 13663-13677.

王继东, 许秋铭, 黄婷, 等. 含共享储能的数据中心微网群分布式优化调度[J]. 电网技术, 2024, 48(8): 3238-3247.

CHEN Y H, ZHU Z Y, LIN H J, et al.Shared energy storage optimization considering electricity price and PV output uncertainty[C]//2023 5th Asia Energy and Electrical Engineering Symposium (AEEES), Chengdu, China, 2023: 1696-1703.

ZHANG L, LIU D Y, CAI G W, et al.An optimal dispatch model for virtual power plant that incorporates carbon trading and green certificate trading[J]. International journal of electrical power & energy systems, 2023, 144: 108558.

崔杨, 沈卓, 王铮, 等. 考虑绿证-碳排等价交互机制的区域综合能源系统绿色调度[J]. 中国电机工程学报, 2023, 43(12): 4508-4517.

YAN N, LI X J, WU Z L, et al.Low-carbon economic scheduling with Demand-Side response uncertainty in regional integrated energy system[J]. International journal of electrical power & energy systems, 2024, 156: 109691.

骆钊, 黎博文, 毕贵红, 等. 含CCUS和P2G的综合能源系统分布式鲁棒优化调度[J]. 高电压技术, 2024, 50(8): 3486-3499.

WANG R H, BI X W, BU S Q.Real-time coordination of dynamic network reconfiguration and volt-VAR control in active distribution network: a graph-aware deep reinforcement learning approach[J]. IEEE transactions on smart grid, 2024, 15(3): 3288-3302.

CAO D, HU W H, ZHAO J B, et al.Reinforcement learning and its applications in modern power and energy systems: a review[J]. Journal of modern power systems and clean energy, 2020, 8(6): 1029-1042.

HE X T, GE S Y, LIU H, et al.Frequency regulation of multi-microgrid with shared energy storage based on deep reinforcement learning[J]. Electric power systems research, 2023, 214: 108962.

DING L F, CUI Y K, YAN G F, et al.Distributed energy management of multi-area integrated energy system based on multi-agent deep reinforcement learning[J]. International journal of electrical power & energy systems, 2024, 157: 109867.

陈泽宇, 方志远, 杨瑞鑫, 等. 基于深度强化学习的混合动力汽车能量管理策略[J]. 电工技术学报, 2022, 37(23): 6157-6168.

余兴兴, 李元诚, 王庆乐, 等. 基于联邦强化学习的社区共享储能日前调度[J]. 中国电机工程学报, 2024, 44(20): 8103-8113.

LEE S, XIE L, CHOI D H.Privacy-preserving energy management of a shared energy storage system for smart buildings: a federated deep reinforcement learning approach[J]. Sensors, 2021, 21(14): 4898.

陈金富, 朱乔木, 石东源, 等. 利用时空相关性的多位置多步风速预测模型[J]. 中国电机工程学报, 2019, 39(7): 2093-2106.

张晓英, 陈宝奇, 马志程, 等. 基于主从博弈理论的热电联供型太阳能热发电站冬季优化运行研究[J]. 太阳能学报, 2023, 44(11): 155-165.

李亚峰, 王维庆, 寇洋, 等. 考虑绿证-碳联合交易与需求响应综合能源系统经济运行[J]. 太阳能学报, 2023, 44(11): 538-546.

SHEN J R.Low-carbon optimal dispatch of campus integrated energy system considering flexible interactions between supply and demand[J]. International journal of electrical power & energy systems, 2024, 156: 109776.

杨秀, 傅广努, 刘方, 等. 考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究[J]. 电网技术, 2022, 46(2): 699-714.

TOSTADO-VÉLIZ M, REZAEE JORDEHI A, HASANIEN H M, et al. A novel stochastic home energy management system considering negawatt trading[J]. Sustainable Cities and Society, 2023, 97: 104757.

ZHAO J, YANG Z L, SHI L Y, et al.Photovoltaic capacity dynamic tracking model predictive control strategy of air-conditioning systems with consideration of flexible loads[J]. Applied energy, 2024, 356: 122430.

WU Z Y, WANG J X, ZHONG H W, et al.Sharing economy in local energy markets[J]. Journal of modern power systems and clean energy, 2023, 11(3): 714-726.

谭海旺, 杨启亮, 邢建春, 等. 基于XGBoost-LSTM组合模型的光伏发电功率预测[J]. 太阳能学报, 2022, 43(8): 75-81.

WIESE F, SCHLECHT I, BUNKE W D, et al.Open power system data-frictionless data for electricity system modelling[J]. Applied energy, 2019, 236: 401-409.

段新会, 黄嵘, 齐传杰, 等. 计及碳交易与需求响应的微能源网双层优化模型[J]. 太阳能学报, 2024, 45(3): 310-318.

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