Journal
ENERGIES
Volume 16, Issue 11, Pages -Publisher
MDPI
DOI: 10.3390/en16114366
Keywords
data-driven modeling; distribution power systems; grey-box modeling; generalized additive models; phase voltage estimation
Categories
Ask authors/readers for more resources
This paper develops a method for nodal voltage estimation in unbalanced radial low-voltage grids using a data-driven grey-box modeling approach. The method relies on experimental data from a real-world LV grid in Denmark and uses data input from only one measuring device per feeder. The prediction results show high accuracy at root mean squared errors (RMSEs) of 0.002-0.0004 p.u. and a short computation time that meets requirements for practical, real-time monitoring of distribution system operator (DSO) grids.
Increasing levels of distributed generation (DG), as well as changes in electricity consumption behavior, are reshaping power distribution systems. These changes might place particular stress on the secondary low-voltage (LV) distribution systems not originally designed for bi-directional power flows. Voltage violations, reverse power flow, and congestion are the main arising concerns for distribution system operators (DSOs), while observability in these grids is typically nonexistent or very low. The present paper addresses this issue by developing a method for nodal voltage estimation in unbalanced radial LV grids (at 0.4 kV). The workflow of the proposed method combines a data-driven grey-box modeling approach with generalized additive models (GAMs). Furthermore, the proposed method relies on experimental data from a real-world LV grid in Denmark and uses data input from only one measuring device per feeder. Predictions are evaluated by using a test data set of 31 days, which is more than twice the size of the training data set of 13 days. The prediction results show high accuracy at root mean squared errors (RMSEs) of 0.002-0.0004 p.u. The method also requires a short computation time (14 s for the first stage and 2 s for the second stage) that meets requirements for the practical, real-time monitoring of DSO grids.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available