基于机器学习算法的电网运行方式计算实践研究

The Practice Research of Power System Operation Mode Calculation Based On Machine Learning

  • 摘要: 电力系统中电网运行方式的变化会引起了电力设备参数的变化,运行方式的计算量会随着电网复杂程度的增加而逐渐增大,为解决这种工作量繁重而又重复性的工作,结合TensorFlow架构的优势和机器学习算法对电网运行方式计算进行实践研究,结合实际需求对线性回归算法、逻辑回归二分类算法以及深度神经网络算法进行对比分析,给出了性能评价指标.

     

    Abstract: The change of power system operation mode can cause the change of the power equipment parameters, operation mode of the calculation with the power grid is gradually increasing with the increase of complexity. In order to solve the heavy workload and repetitive tasks, this paper describes how to take the advantage of TensorFlow architecture and machine learning algorithm to study thegrid operation mode calculation. The linear regression algorithm, logical regression two-classification algorithm and depth neural network algorithm are analyzed comparatively. Index of performance evaluation can be provided combining with the actual requirements.

     

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