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On-line Update Method for the Sensitivity Consistency Model of Interconnected Power Grid Based on Electric Power Big Data

机译:基于电力大数据的互联电网灵敏度一致性模型的在线更新方法

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Real-time fast calculation of the power flow of the interconnected power grid is an important guarantee for the reliable operation of the interconnected power grid. The topology of the interconnected power grid is complex, and the calculation of the power flow of the whole network is large and timeconsuming. The sensitivity equivalent model can effectively simplify the interconnected power grid and shorten the time of the power flow calculation of the whole network. The operating state of the power grid is constantly changing. In order to ensure the accuracy of the power flow calculation results, it is necessary to update the uniform sensitivity equivalent model in real time. Due to factors such as the vertical management system between the interconnected power grids and the principle of commercial confidentiality, it is difficult to share information between interconnected power grids in real time, and the sensitivity equivalent model cannot be updated in real time, resulting in too much error in the calculation results and no reference value. To solve this problem, this paper proposes an online update method for the sensitivity equivalent model of the interconnected power grid based on power big data to solve the problem of excessive power flow calculation errors caused by the untimely update of the equivalent model parameters, and to ensure the operational reliability of the interconnected power grid.
机译:互联电网功率流的实时快速计算是互联电网可靠操作的重要保证。互连电网的拓扑是复杂的,整个网络的电力流量的计算大而定时。灵敏度等效模型可以有效地简化互连的电网并缩短整个网络的功率流量计算的时间。电网的操作状态不断变化。为了确保功率流量计算结果的准确性,有必要实时更新均匀灵敏度等效模型。由于诸如互联电网之间的垂直管理系统等因素和商业机密性的原理,因此难以实时在互联电网之间共享信息,并且灵敏度等效模型不能实时更新,从而导致计算结果中有很大的错误,没有参考值。为了解决这个问题,本文提出了一种基于电力大数据的互联电网的灵敏度等效模型的在线更新方法,以解决由等效模型参数的不及时更新引起的过度功率流计算误差的问题,以及确保互联电网的操作可靠性。

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