Improved Admittance Matrix Estimation on Power Networks Based on Hybrid Measurements

Publisher:闻天明Release Time:2021-07-21Number of visits:10

Speaker:     Mr. Yixiong Jia

Time:          Jul.23.2021 14:00-15:00

Location:    SIST 1C 101

Host:            PSPAL



Parameters of power system networks (for example series resistance, series reactance and shunt admittance) are usually provided by the utilities. Nevertheless, in practice these parameters may not be quite accurate in the utility database. Furthermore, the values of parameters could be easily affected by environmental factors like temperature or weather, human activities and usage time. Therefore, line parameters in the power networks always vary from the nominal values: there could be even 25%-30% differences between the actual values and the nominal values. This leads to problematic results for many applications such as power flow calculation, transmission line protection, fault location etc., since these applications in the power networks require accurate line parameters. As a result, an accurate and reliable line parameters estimation method of the power networks is of great importance. Present methods which include classical estimation methods and network estimation methods are all require installations of PMUs at all the buses to ensure synchronization, which may still increase costs for a practical power network. To overcome this limitation. This talk will mainly introduce the existing admittance matrix estimation methods as well as the proposed admittance matrix estimation method based on hybrid measurements. Instead of installing PMUs at all the buses for a power network, accurate and reliable admittance matrix can be obtained through installing PMUs at a few key buses and measuring the magnitude of the voltage at the rest of the buses. Moreover, the proposed method presents robustness towards measurement errors and the estimated admittance matrix enables very accurate power flow results.



Mr. Yixiong Jia joined PSPAL in March 2019. He is currently a master student in PSPAL (starting from September 2019). He received the B.S. degree of Mathematics from North West Agriculture and Forestry University, Yangling, Xi'an, China, in 2019. His research interests include fault diagnosis of power system and power electronic systems.