计及多微网灵活性的端对端分散式交易策略

doi:10.11930/j.issn.1004-9649.202411059

摘要/Abstract

摘要：

以可再生能源为主导地位的主动配电网需要激励各类分布式资源参与电网运行以增强系统的灵活性。为解决可再生能源大量并网引发的功率波动问题，在充分考虑主动配电网与微电网相互作用的基础上，引入共享储能（shared energy storage system，SESS）和端对端（peer to peer，P2P）交易机制，研究多微电网租赁SESS进行功率波动平抑和多微电网P2P灵活性交易策略。然后，提出基于非对称纳什议价的多微网系统收益分配机制，以非线性能量映射函数评估各微电网主体的贡献度，实现多微电网系统合作收益的公平分配。最后，采用交替方向乘子法对所提模型进行分布式计算求解，实现对各主体信息安全的有效保护。通过算例对比证明了所提方法的有效性。

关键词: 微电网, 灵活性, 非对称纳什议价, 端对端交易

Abstract:

Active distribution network dominated by renewable energy need to incentivize the participation of various distributed energy resources to enhance system flexibility. To address the power fluctuation problems caused by the large-scale access of renewable energy, this paper firstly introduced a shared energy storage system (SESS) and a peer to peer (P2P) energy trading mechanism, with full consideration of the interactions between active distribution networks and microgrids (MG), and investigated the multi-MG power fluctuation mitigation strategy and the P2P flexibility trading strategy based on SESS leasing. Secondly, a multi-MG revenue allocation mechanism based on asymmetric Nash bargaining was proposed and a nonlinear energy mapping function was used for evaluating each MG's contribution in order to attain fair allocation of cooperative revenue. Finally, the proposed model was solved distributively using the alternating direction method of multipliers (ADMM), effectively protecting information security for all stakeholders. The effectiveness of the proposed method was then demonstrated through comparative case studies.

Key words: microgrids, flexibility, asymmetric Nash bargaining, peer-to-peer trading

皇甫霄文, 李科, 许长清, 蒋小亮, 于昊正, 王汝靖. 计及多微网灵活性的端对端分散式交易策略[J]. 中国电力, 2025, 58(9): 194-204, 218.

HUANGFU Xiaowen, LI Ke, XU Changqing, JIANG Xiaoliang, YU Haozheng, WANG Rujing. Decentralized Peer-to-peer Trading Strategy Considering Flexibility of Multiple Microgrids[J]. Electric Power, 2025, 58(9): 194-204, 218.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202411059

https://www.electricpower.com.cn/CN/Y2025/V58/I9/194

图/表 12

图 1 多MG日前灵活性交易机制

Fig.1 The day-ahead flexibility trading mechanism of multiple MG

图 2 基于ADMM的纳什议价模型求解流程

Fig.2 The solution process of the proposed ADMM-based Nash bargaining model

图 3 带有多MG的ADN结构示意

Fig.3 Schematic network structure of the ADN with multiple MG

图 4 ADN及MG的可再生能源出力和负荷

Fig.4 Renewable energy output and load profile of MG and ADN

图 5 SESS充放电策略及SOC 变化

Fig.5 Charging/discharging strategies and SOC variation of SESS

图 6 各MG的SESS租赁需求

Fig.6 SESS leasing demands from each MG

表 1 各MG多目标优化结果

Table 1 The multi-objective optimization results of each MG

MG	租赁成本/ 元	租赁前净负荷均方差/kW²	租赁后净负荷均方差/kW²
1	1273.5	9.42×10⁶	4.99×10⁶
2	1157.3	3.44×10⁶	7.62×10⁵
3	1110.6	6.83×10⁶	4.41×10⁶

图 7 MG间电能交易结果

Fig.7 Trading results among MG

图 8 各MG内部电能出力

Fig.8 Scheduling results of MG under cooperative operation

表 2 基于对称议价的成本和利益分配

Table 2 The cost-benefit distribution based on symmetric bargaining 单位：元

MG	参与P2P 交易时微电网运行成本	参与P2P 交易时纳什议价收益	参与P2P 交易时微电网总成本	不参与P2P 交易时微电网总成本	收益提升值
1	3759.39	1172.95	2586.44	3269.33	682.88
2	3604.19	–928.16	4532.36	5215.18	682.81
3	2252.52	–244.59	2497.12	3180.00	682.87

表 3 基于非对称议价的成本利益分配

Table 3 The cost-benefit distribution based on asymmetric Nash bargaining

MG	非对称议价因子	参与P2P交易时纳什议价收益/元	参与P2P交易时MG 总成本/元	收益提升值/元	电能贡献量/(kW·h)
1	2.1595	1672.22	2087.17	1182.15	2807.0
2	0.6974	–1229.09	4833.29	381.89	–1650.7
3	0.8860	–442.40	2694.93	485.07	–1156.4

图 9 迭代收敛结果

Fig.9 Converged results

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