| 引用本文: | 曹华珍,徐蔚,张军,郇嘉嘉,罗强,张勇军.基于集群划分的点对点交易与共享储能协同规划运行[J].电力自动化设备,2025,45(5):31-39. |
| CAO Huazhen,XU Wei,ZHANG Jun,XUN Jiajia,LUO Qiang,ZHANG Yongjun.Cooperative planning and operation of peer-to-peer transaction and shared energy storage based on cluster partitioning[J].Electric Power Automation Equipment,2025,45(5):31-39. |
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| 摘要: |
| 随着分布式电源的日益渗透，点对点交易与共享储能是促进产消者之间能量交易与平衡的重要手段，但传统规划方法难以实现兼顾两者分区协调的运行需求。为了促进电能的高效共享与利用，建立了基于集群划分的点对点交易与共享储能双层规划运行模型。在外层规划模型中，根据配电网的电气连接距离与供需平衡度指标，划分产消者集群；初始化各集群共享储能系统的选址、容量和功率，并计算运营商的最大年化总收益。在内层运行模型中，以运营商和产消者收益最大为目标，建立点对点交易的主从博弈优化模型，并将每个集群产消者交易后的不平衡电量结果返回给外层模型。针对模型特性，在计及网络安全约束的条件下，采用双层混合迭代的Gurobi求解器与灾变遗传算法进行求解。通过仿真算例验证了所提模型与求解方法的有效性。 |
| 关键词: 集群划分 点对点交易 主从博弈 共享储能 网络安全约束 协同规划 |
| DOI：10.16081/j.epae.202503011 |
| 分类号:TM732 |
| 基金项目:国家自然科学基金资助项目(52177085)；中国南方电网有限责任公司科技项目(GDKJXM20222479) |
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| Cooperative planning and operation of peer-to-peer transaction and shared energy storage based on cluster partitioning |
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CAO Huazhen1, XU Wei1, ZHANG Jun2, XUN Jiajia1, LUO Qiang1, ZHANG Yongjun2
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1.Grid Planning Research Center of Guangdong Power Grid Co.,Ltd.,Guangzhou 510030, China;2.Smart Energy Engineering Technology Research Center, School of Electric Power, South China University of Technology, Guangzhou 510640, China
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| Abstract: |
| With the increasing penetration of distributed generation, peer-to-peer(P2P) transaction and shared energy storage are important means to promote energy trading and balance among prosumers. However, the traditional planning methods are difficult to simultaneously meet the operational requirements of regional coordination between them. In order to promote the efficient sharing and utilization of electric energy, a two-layer planning and operation model of P2P transaction and shared energy storage based on cluster partitioning is established. In the outer planning model, the prosumer clusters are divided according to the electrical connection distance and the supply-demand balance indicator of the distribution network. Then, the location, capacity and power of shared energy storage systems within each cluster are initialized, and the maximum annual total profit of operator is calculated. In the inner operation model, a master-slave game optimization model of P2P transaction is established with the goal of maximizing the profit of both operators and prosumers. The results of unbalanced electricity after the transaction of each prosumer in the cluster is fed back to the outer model. According to the characteristics of the model, a two-layer hybrid iterative Gurobi solver and the catastrophe genetic algorithm are used to solve the problem under the condition of considering the network security constraints. The effectiveness of the proposed model and solution method is verified by a simulation example. |
| Key words: cluster partitioning peer-to-peer transaction master-slave game shared energy storage network security constraints cooperative planning |
