引用本文:孙晓荣,杨爽爽,潘学萍,郭金鹏,秦景辉.交互能源机制下多区域综合能源系统能源共享协同调度[J].电力自动化设备,2023,43(11):9-17
SUN Xiaorong,YANG Shuangshuang,PAN Xueping,GUO Jinpeng,QIN Jinghui.Energy sharing and cooperative scheduling of multi-regional integrated energy system under transactive energy mechanism[J].Electric Power Automation Equipment,2023,43(11):9-17
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交互能源机制下多区域综合能源系统能源共享协同调度
孙晓荣, 杨爽爽, 潘学萍, 郭金鹏, 秦景辉
河海大学 能源与电气学院,江苏 南京 211100
摘要:
能源共享需求下多区域综合能源系统存在集中调度决策变量多、约束复杂、区域主体信息隐私难以保护,以及传统分布式算法收敛不光滑、收敛速度慢等问题。为此,设计了交互能源机制下地区系统运营商进行多区域能源管理的框架,建立了考虑新能源不确定性的能源共享日前调度随机优化模型,并构建了基于绝对值函数线性化的代理增广拉格朗日松弛算法进行求解。基于所提模型和算法,地区系统运营商根据各区域提交的初始供求信息制定区域间的交易价格,各区域以运行成本、碳排放成本、弃光成本最小为目标优化设备出力和能源交互量,并进行迭代出清。算例结果表明所提模型能够有效提升区域运行效益,提高新能源消纳,且所提算法较常用分布式算法在求解速度和求解质量方面更具优越性。
关键词:  多区域综合能源系统  分布式优化  能源共享  代理增广拉格朗日松弛
DOI:10.16081/j.epae.202309019
分类号:TM73
基金项目:国家自然科学基金资助项目(52107087);中央高校基本科研业务费专项资金资助项目(B230201049)
Energy sharing and cooperative scheduling of multi-regional integrated energy system under transactive energy mechanism
SUN Xiaorong, YANG Shuangshuang, PAN Xueping, GUO Jinpeng, QIN Jinghui
College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Abstract:
Under the demand of energy sharing, the centralized scheduling of multi-regional integrated energy system has the problems of multiple decision-making variables, complex constraints, difficult to protect the information privacy of regional subjects, and non-smooth convergence and slow convergence speed when adopting traditional distributed algorithms. Therefore, a multi-regional energy management framework for area system operators under the transactive energy mechanism is designed, a stochastic optimization model for energy sharing day-ahead scheduling considering the uncertainty of renewable energy sources is established, and an absolute value function-based linearized surrogate augmented Lagrangian relaxation algorithm is constructed to solve the problem. Based on the proposed model and algorithm, the area system operators set inter-regional trading prices according to the initial supply and demand information submitted by each region, and each region optimizes the equipment output and the transactive energy capacity with the goal of minimizing the operation cost, carbon emission cost and photovoltaic abandonment cost, and performs iterative clearing. The numerical results show that the proposed model can effectively improve the operation benefits of regions and renewable energy consumption, and the proposed algorithm has more advantages in solving speed and solving quality than the commonly used distributed algorithms.
Key words:  multi-regional integrated energy system  distributed optimization  energy sharing  surrogate augmented Lagrangian relaxation

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