Dynamic energy flow analysis of the heat-electricity integrated energy systems with a novel decomposition-iteration algorithm
Dynamic energy flow analysis of the heat-electricity integrated energy systems with a novel decomposition-iteration algorithm
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利用新颖的分解迭代算法进行热电综合能源系统的动态能量流分析
DOI：
10.1016/j.apenergy.2022.119492
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发表时间：
2022-09
期刊：
影响因子：
11.2
通讯作者：
Shuai Lu
中科院分区：
文献类型：
--
作者：
Shuai Yao;Wei Gu;Jianzhong Wu;Hai Lu;Suhan Zhang;Yue Zhou;Shuai Lu
集成能源系统的仿真和运行优化研究因其在提高能源效率和增加可再生能源并网方面的潜力而受到广泛关注，其中能量流计算任务是确定网络状态的基本工具。本文研究了综合能源系统中两个强耦合网络--电网和供热网络的动态能流分析模型和方法。首先，深入分析了电网与热网的复杂耦合机理，并将其分为四种具有代表性的耦合模式。在此基础上，给出了每种耦合模式的详细动态能流分析方法。其次，采用精细差分格式对描述热网长效温度动态的偏微分方程组进行离散化。然后用一种新的分解迭代算法求解高维离散模型。与已有方法相比，该算法避免了求解网络方程的庞大系数矩阵，提高了能量流计算结果的准确性。最后，考虑到由于忽略了热源的惯性约束和调节约束而引起的系统误差，首先引入修正阶段对松弛源的热功率输出进行修正，帮助得到更准确的能量流动结果。算例表明，所提出的方法以3.21 S的时间获得了一个118节点的电网和8个35节点的集中供热网组成的耦合系统在300分钟的仿真过程中的动态能量流，能够为实际应用中的仿真和优化提供支持。·深入分析了PG和HN的偶联机理。·提出了一种数据处理策略来解决PG和HN之间的时间尺度不匹配问题。提出了一种新的求解高维离散能流模型的“分解-迭代”算法。·从理论上和数值上分析了该算法的收敛性能。引入修正阶段，以减小因忽略热源调节约束而引起的系统误差。
Simulation and operation optimization studies on the integrated energy system have received extensive attention recently for its potential in improving energy efficiency and increasing grid integration of renewable energy, where the task of energy flow calculation serves as a fundamental tool to determine the network states. This paper investigates the models and methods for dynamic energy flow analysis of two strongly coupled networks in the integrated energy systems — the power grid and the heating network. First, the complicated coupling mechanisms of power grid and heating network are thoroughly analyzed and classified into four representative coupling modes. On this basis, the detailed dynamic energy flow analysis method for each coupling mode is developed. Second, a refined difference scheme is applied to discretize the partial differential equations describing the long-lasting temperature dynamics in the heating network. The high-dimensional dicretized model is then solved by a novel decomposition-iteration algorithm. Compared with existing methods, this algorithm avoids deriving the gigantic coefficient matrix of network equations and can improve the accuracy of energy flow results. Finally, considering the systematical error caused by neglecting the inertial and adjusting constraints of heat sources, a revision stage is firstly introduced to correct the heat power output of the slack source and help obtain more accurate energy flow results. Case study shows that the proposed methods take 3.21 s to obtain the dynamic energy flows of a coupled system consisting of a 118-node power grid and eight 35-node district heating networks over a 300-minutes simulation course, which is qualified to provide support for simulation and optimization related applications in practice. • Coupling mechanisms of PG and HN are thoroughly analyzed. • A data processing strategy is proposed to settle the timescale mismatches between PG and HN. • A novel “decomposition-iteration” algorithm is developed to solve the high-dimensional discretized energy flow model of HN. • Convergence of the proposed algorithm is analyzed analytically and numerically. • A revision stage is introduced to reduce the systematical error caused by omitting the adjusting constraints of heat sources.
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影响因子：
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作者：
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