On-line data splicing power flow analysis method based on sensitivity

• Main Authors: Jun Lu, Lu Lu Zhang, Dong Yu Shi, Tie Li, Jun Ci Tang, Dai Cui
• Format: Article
• Language: English
• Published: Elsevier 2021-04-01
• Series: Energy Reports
• Subjects: Data splicing; Sensitivity; Power control
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352484721000639

This paper proposes an online data splicing power flow analysis method based on sensitivity analysis. Since the step-down transformer in the whole network data is usually equivalent to the 220 kV side, the equipment below 220 kV is not modeled in detail, and the provincial network data is modeled to 110kV and 35 kV voltage level equipment in detail. Different levels of modeling have a greater impact on the accuracy of stability analysis and calculation. Therefore, the purpose of improving data accuracy is achieved by splicing the entire network data (external network) and provincial network data (internal network). This paper is based on the sensitivity analysis method to stabilize the tie-line power by adjusting the output of the external network units, and form the whole network data that can accurately analyze the stability characteristics of the provincial network. The problem of power flow deviation caused by the voltage and angle deviation of the nodes at both ends of the regional tie line during the data splicing process is solved. Through the actual application of splicing the entire network and Hunan Provincial Network data, the effectiveness and necessity of the proposed method have been verified.