scholarly journals Method for Real-Time Abnormal State Detection of a Distribution Network Based on Maximum and Minimum Eigenvalues

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Keyan Liu ◽  
Kaiyuan He ◽  
Huanna Niu ◽  
Yuzhu Wang ◽  
Jingxiang Zhao

The state analysis method of a traditional distribution network operation is strictly dependent on the physical model of itself, but it varies as the geography changes, and it is difficult to find the abnormal state of a district network on real-time, especially the sudden change caused by the distributed energy and EV load. So, a method of the abnormal state detecting for the distribution network is proposed based on the maximum and minimum eigenvalues. Firstly, a high-dimensional random matrix is established by the big data from the distribution network management system to take abnormal state detection through a real-time sliding window. Then, the maximum and minimum eigenvalues of the distribution network are gained by calculating the sample covariance matrix of the random matrix and determining the maximum and minimum eigenvalues of the latter matrix. Finally, an 1177-node testing system was taken as an example, and the simulation results showed that the proposed method could detect the abnormal state in real-time without depending on the physical model and fault type of the grid.

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Zhiqing Sun ◽  
Weiguo Si ◽  
Yi Xuan ◽  
Shaojie Luo ◽  
Jian Zhao ◽  
...  

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Arvind Sharma ◽  
Mohan Kolhe ◽  
Alkistis Kontou ◽  
Dimitrios Lagos ◽  
Panos Kotsampopoulos

Abstract In this paper, solar photovoltaic hosting capacity within the electrical distribution network is estimated for different buses, and the impacts of high PV penetration are evaluated using power hardware-in-loop testing methods. It is observed that the considered operational constraints (i.e. voltage and loadings) and their operational limits have a significant impact on the hosting capacity results. However, with increasing photovoltaic penetration, some of the network buses reach maximum hosting capacity, which affects the network operation (e.g. bus voltages, line loading). The results show that even distributing the maximum hosting capacity among different buses can increase the bus voltage rise to 9%. To maintain the network bus voltages within acceptable limits, reactive power voltage-based droop control is implemented in the photovoltaic conditioning devices to test the dynamics of the network operation. The results show that implementation of the droop control technique can reduce the maximum voltage rise from 9% to 4% in the considered case. This paper also presents the impact of forming a mesh type network (i.e. from radial network) on the voltage profile during PV penetration, and a comparative analysis of the operational performance of a mesh type and radial type electrical network is performed. It is observed that the cumulative effect of forming a mesh type network along with a droop control strategy can further improve the voltage profile and contribute to increase photovoltaic penetration. The results are verified using an experimental setup of digital real-time simulator and power hardware-in-loop test methods. The results from this work will be useful for estimating the appropriate photovoltaic hosting capacity within a distribution network and implementation of a droop control strategy in power conditioning devices to maintain the network operational parameters within the specified limits. Highlights Voltage and line loading constraints’ combination can reduce PV hosting capacity by 50% as compared to only voltage as a constraint. Implementation of reactive power versus voltage droop control in PV power conditioning device can reduce voltage variation from 9% to 4%. In a PV integrated electrical energy network, line loading can be reduced by 20% if the network is configured from radial to mesh type.


2007 ◽  
Vol 1 (4) ◽  
pp. 307-321 ◽  
Author(s):  
Anna Tanskanen ◽  
Ari Jantunen ◽  
Juha‐Matti Saksa ◽  
Jarmo Partanen ◽  
Jukka Bergman

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