Weijia Yang , Yuping Huang , Suliang Liao , Daiqing Zhao , Duan Yao
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Additionally, we reconstruct a holomorphic matrix, integrating hydraulic flow to bridge thermal and electric power flows, thereby improving the operational heterogeneity among different networks. Real-case simulations show that when the Taylor expansion order in HEM is equal to 4, the proposed method achieves a mere 1 % discrepancy from actual operational data, enhancing computational efficiency by 60 % compared to the Newton-Raphson method. Moreover, in this real-case scenario, the TN exhibits a maximum delay response time of 180 seconds compared to electrical networks. 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引用次数: 0
摘要
分析多能源系统中多能源网络(MEN)的运行状态对于确保系统稳定性至关重要。不同能源流的动态运行特性给计算分析带来了挑战。传统的稳态方法不足以解决多能源网络(MEN)的动态问题,尤其是在处理热网(TN)中水力流和热力流之间的时间差异以及热网和电网之间的异质性时。因此,本文提出了一种基于多级分解法的新型全态嵌入法(HEM)。所开发的 HEM 构建了一个时间系数矩阵,并利用内-外循环递归来处理 TN 中热流与水流之间的时滞。此外,我们还重建了一个全态矩阵,将水力流整合为热力流和电力流的桥梁,从而改善了不同网络之间的运行异质性。实际案例模拟表明,当 HEM 中的泰勒扩展阶数等于 4 时,所提出的方法与实际运行数据的偏差仅为 1%,与牛顿-拉斐森方法相比,计算效率提高了 60%。此外,在这种实际情况下,与电网相比,TN 的最大延迟响应时间为 180 秒。利用这一延迟时间,多能源系统中的可再生能源发电量每天可有效增加 961.58 千瓦。
Temporal asynchrony analysis for dynamic operation of hydraulic-thermal-electricity multiple energy networks based on holomorphic embedding method
Analyzing the operational states of multiple energy networks (MEN) in multi-energy systems is crucial for ensuring system stability. The dynamic operational characteristics of different energy flows pose challenges for computational analysis. Traditional steady-state methods are inadequate for addressing the dynamics of MEN, especially when dealing with temporal discrepancies between hydraulic and thermal flows in thermal networks (TN) and the heterogeneity between TN and electrical networks. Therefore, this paper proposes a novel holomorphic embedding method (HEM) based on multi-stage decomposition method. The developed HEM constructs a time coefficient matrix and utilize inner-outer loop recursion to handle the time lag between thermal flow and hydraulic flow in the TN. Additionally, we reconstruct a holomorphic matrix, integrating hydraulic flow to bridge thermal and electric power flows, thereby improving the operational heterogeneity among different networks. Real-case simulations show that when the Taylor expansion order in HEM is equal to 4, the proposed method achieves a mere 1 % discrepancy from actual operational data, enhancing computational efficiency by 60 % compared to the Newton-Raphson method. Moreover, in this real-case scenario, the TN exhibits a maximum delay response time of 180 seconds compared to electrical networks. Exploiting this delay time effectively increases renewable energy generation within multi-energy systems by 961.58 kW per day.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.