面向能源互联网的电-水耦合系统双线性加权最小二乘状态估计
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1.重庆大学电气工程学院;2.国网河北经研院

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TM732???????

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Bilinear weighted least square state estimation of the electricity-water coupled system for energy internet
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1.School of electrical engineering,Chongqing University;2.Economic and Technology Research Institute, State Grid Hebei Electric Power Co., Ltd.

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    摘要:

    多能流状态估计是能源互联网的重要研究领域。目前,关于电-水耦合系统状态估计的研究刚刚起步,还存在对水网工况适应性差、对电-水耦合信息利用不充分等问题。为此,本文提出一种考虑管道摩阻系数修正的水网双线性最小二乘(WLS)状态估计方法,并进一步基于水泵虚拟量测构造电-水耦合信息双向传递,提出适用于电-水耦合系统分立运行、协同运行和联合运行的双线性WLS状态估计方法。用11节点水网及其与IEEE-14节点、IEEE-118节点电网耦合形成的两个电-水耦合系统验证了所提双线性WLS估计的有效性。算例结果证明了水网状态估计中修正管道摩阻系数的必要性与双线性WLS估计方法在计算效率与小流量水网适应性方面的优越性,以及协同估计与联合估计在提升电网/水网状态估计精度、数据一致性与可观性方面的有效性。

    Abstract:

    Multi-energy flow state estimation is an important research field of energy Internet. At present, the research on the state estimation of electricity-water coupling system has just started, and there are still some problems, such as poor adaptability to the working conditions of water network, inadequate utilization of electricity-water coupling information and so on. For this reason, a bilinear least square (WLS) state estimation method for water network considering the correction of friction coefficient is proposed in this paper. Based on the virtual measurement of the water pump and the bi-directional transmission of coupling information, a bilinear WLS state estimation method is proposed, which is suitable for discrete operation, cooperative operation and joint operation of electricity-water coupling system. The effectiveness of the proposed bilinear WLS estimation is verified by 11-node water network and two electricity-water coupling systems formed by coupling with IEEE-14 node and IEEE-118 node power system. The results of numerical examples prove the necessity of correcting friction coefficient in water network state estimation, the superiority of bilinear WLS estimation method in computational efficiency and adaptability of low flow rate water network, and the effectiveness of cooperative estimation and joint estimation in improving the accuracy, data consistency and observability of power system and water network state estimation.

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  • 收稿日期:2023-02-21
  • 最后修改日期:2023-04-17
  • 录用日期:2023-04-25
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