LI Xue, LI Dong, JIANG Tao, et al. Multi-germ and Multi-dimensional Holomorphic Embedding Method for Probabilistic Energy Flow of Integrated Energy System[J]. 2026, 46(7): 2882-2899.
LI Xue, LI Dong, JIANG Tao, et al. Multi-germ and Multi-dimensional Holomorphic Embedding Method for Probabilistic Energy Flow of Integrated Energy System[J]. 2026, 46(7): 2882-2899.DOI: 10.13334/j.0258-8013.pcsee.242447.
多维全纯嵌入法(multi-dimensional holomorphic embedding method,MDHEM)是求解综合能源系统(integrated energy system,IES)能量流的新方法,该方法无需初值、无雅可比矩阵奇异,但在概率能量流计算时存在幂级数阶数高、计算量较大的难题。为此,该文根据全纯嵌入理论的半解析解特性,提出一种IES概率能量流的多胚解-多维全纯嵌入计算方法(multi-germ solution and multi- dimensional holomorphic embedding method,MG-MDHEM)。该方法首先构建IES能量流的MDHEM模型;然后,将IES中多维随机输入变量的波动范围划分为多个子区间,在各子区间内设置物理胚解,递推各子区间内待求变量的低阶半解析解表达式;进一步,将蒙特卡洛模拟法抽样的样本预处理后代入所属子区间待求变量的低阶半解析解中,借助多元商差并行求解各样本的能量流结果,通过对能量流计算结果的统计分析获得IES能量流的概率分布特征;最后,通过E14-G6和E118-G20测试系统算例验证所提方法的准确性和有效性。
Abstract
Multi-dimensional holomorphic embedding method (MDHEM) is a new method for solving the energy flow of integrated energy systems (IES). This method boasts two key advantages: freedom from initial value dependence and non-singularity of the Jacobian matrix. However
it faces notable challenges in probabilistic energy flow (PEF) calculations
particularly the requirement for high-order power series expansions and the resulting heavy computational burden. In order to address the above issues
this paper proposes a multi-germ solution and multi-dimensional holomorphic embedding method (MG-MDHEM) to calculate the PEF of IES via the semi-analytical solution characteristics of HEM. Firstly
the MDHEM-based energy flow model of IES is formulated. Then
the fluctuation range of the multidimensional stochastic inputs in IES is divided into multiple subintervals
and physical solutions of MDHEM in each subinterval are set up. In each subinterval
the low-order semi-analytical solution expressions for the variables can be recursively obtained. Further
for the stochastic samples obtained by Monte Carlo simulation
the samples are preprocessed and substituted into the low-order semi-analytical solutions of the variables in the subintervals
and the Pade approximation is used to solve the low-order semi-analytical formulations using parallel multi-dimensional difference methods to achieve the energy flow result of IES in each sample
and the probability distribution of PEF for the IES is hereby obtained using the energy flow calculation results of Monte Carlo simulation. Finally
the accuracy and effectiveness of the proposed method are proved by the energy flow calculation results of the E14-G6 and E118-G20 test systems.