High-Fidelity Large-Signal Order Reduction Approach for Composite Load Model
High-Fidelity Large-Signal Order Reduction Approach for Composite Load Model
复制标题
复合负载模型的高保真大信号降阶方法
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Bai Cui
中科院分区：
文献类型：
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作者：
Zixiao Ma;Zhaoyu Wang;Dongbo Zhao;Bai Cui
随着电子负载和分布式能源（DER）的日益普及，传统的负载模型无法捕捉它们的动态。为此，西部电力协调理事会（WECC）提出了一种新的综合负荷模型。然而，该模型是一个复杂的高阶非线性系统，具有多时间尺度特性，这对大规模仿真的稳定性分析和计算负担提出了挑战。为了在保持原模型准确性的前提下减少计算量，提出了一种通用的高保真降阶方法，并将其应用于WECC复合负荷模型。首先，我们发展了一个大信号降阶（LSOR）方法，利用奇异摄动理论。在该方法中，快速动态被集成到缓慢的动态，以保持快速动态的瞬态特性。然后，我们提出了精确降阶的必要条件，并将其嵌入到LSOR中，以提高和保证降阶模型的精度。最后，我们开发的降阶WECC复合负载模型使用所提出的算法。仿真结果表明，降阶大信号模型显着减轻了计算负担，同时保持类似的动态响应作为原始的复合负荷模型。
With the increasing penetration of electronic loads and distributed energy resources (DERs), conventional load models cannot capture their dynamics. Therefore, a new comprehensive composite load model is developed by Western Electricity Coordinating Council (WECC). However, this model is a complex high-order nonlinear system with multi-time-scale property, which poses challenges on stability analysis and computational burden in large-scale simulations. In order to reduce the computational burden while preserving the accuracy of the original model, this paper proposes a generic high-fidelity order reduction approach and then apply it to WECC composite load model. First, we develop a large-signal order reduction (LSOR) method using singular perturbation theory. In this method, the fast dynamics are integrated into the slow dynamics to preserve the transient characteristics of fast dynamics. Then, we propose the necessary conditions for accurate order reduction and embed them into the LSOR to improve and guarantee the accuracy of reduced-order model. Finally, we develop the reduced-order WECC composite load model using the proposed algorithm. Simulation results show the reduced-order large signal model significantly alleviates the computational burden while maintaining similar dynamic responses as the original composite load model.