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Approximations of power system dynamic load characteristics by artificial neural networks

机译:人工神经网络电力系统动态负荷特性的近似值

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The static and dynamic characteristics of power system loads are critical to obtaining quality operating point predictions or stability calculations. The composite behavior of components at load buses are usually too complicated to be expressed in a simple form. Based on the approximation capability of artificial neural networks the authors explore the possibility of using neural networks to emulate load behaviours. The results verify the potential of load representation by neural networks.
机译:电力系统负载的静态和动态特性对于获得质量操作点预测或稳定性计算至关重要。负载总线的组件的复合行为通常太复杂,不能以简单的形式表示。基于人工神经网络的近似能力,作者探讨了使用神经网络模拟负载行为的可能性。结果验证了神经网络负载表示的潜力。

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