基于数字孪生技术的云储能点对点交易双层优化策略  

Bilayer Optimization Strategy for Peer-to-peer Transaction of Cloud Energy Storage Based on Digital Twin Technology

作　　者：卢锦玲[1] 颜禄涵 周阳[1] 黄鼎越 任惠[1] LU Jinling;YAN Luhan;ZHOU Yang;HUANG Dingyue;REN Hui(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,China)

机构地区：[1]华北电力大学电气与电子工程学院,河北保定071003

出　　处：《华北电力大学学报（自然科学版）》2024年第4期18-25,I0002,I0003,共10页Journal of North China Electric Power University：Natural Science Edition

基　　金：国家重点研发计划项目(2018YFE0122200)。

摘　　要：为解决云储能(Cloud energy storage, CES)日前交易模型预测精度低、信息传输不及时、交易机制可靠性差等问题,提出一种基于数字孪生技术的云储能点对点交易双层优化策略。首先,针对环境因素的时变性,采用数字孪生(Digital Twins, DT)技术实现新能源电厂出力与负荷的超短期预测;其次,考虑到用户规模不断增大,构建以云储能供应商-社区-用户为体系的改进分布式点对点(Peer-to-peer, P2P)交易策略,实现交易的去中心化;再次,为同时满足CES供应商与用户两大主体的利益需求,建立基于日内滚动优化的双层优化配置模型,上层求解储能电站的优化配置,下层求解用户用电策略,并采用Karush-Kuhn-Tucher(KKT)条件与Big-M法将多目标双层非线性优化问题转化为单层线性优化问题;最后,通过两次使用shapley值计算社区与用户成本分摊。算例仿真结果表明,所提策略能够实现新能源电厂出力与负荷的高精度预测,降低用户群与CES供应商交易的复杂度,在用户购电成本最小的基础上最大化CES供应商的收益,保证交易市场的长期稳定运行。In order to solve the problems of low prediction accuracy of day-ahead trading model of cloud energy storage(CES),untimely information transmission and poor reliability of trading mechanism,we proposed a bilayer optimization strategy for peer-to-peer trading of cloud energy storage(CES)based on digital twin technology.Firstly,we used the digital twin(DT)technology to realize the ultra-short-term prediction of output and load of new energy power plants according to the time-varying environmental factors.Secondly,considering the increasing user scale,we proposed an improved distributed peer-to-peer(P2P)trading strategy based on the system of cloud energy storage supplier,community and user to realize the decentralization of trading.Thirdly,in order to meet the interests of both CES suppliers and users,we established a bilayer optimal allocation model based on intra-day rolling optimization.The upper layer solves the optimal allocation of energy storage power stations,and the lower layer solves the power consumption strategy of users.By using the Karush-Kuhn-Tucher(KKT)condition and BIG-M method,the multi-objective bilayer nonlinear optimization problem was transformed into a single-layer linear optimization problem.Finally,we calculated community and user cost sharing by using the Shapley value twice.The simulation results show that the proposed strategy can achieve high-precision prediction of output and load of new energy power plants,reduce the complexity of transactions between users and CES suppliers,maximize the revenue of CES suppliers based on minimizing the cost of purchasing power to the customer,and ensure the long-term stable operation of the trading market.

关 键 词：云储能 数字孪生技术 改进分布式点对点交易策略 双层优化配置 SHAPLEY值 

分 类 号：TM715[电气工程—电力系统及自动化]