Abstract
The number of grid-tied inverters interfacing renewable resources, energy-storage devices, and flexible loads in distribution networks is steadily increasing. State-space models for inverters are nonlinear and high dimensional which renders the task of modeling large numbers at the edge of the grid to be a difficult undertaking. To address this issue, we develop a distribution-network-cognizant aggregation approach that describes the collective dynamics of grid-tied three-phase inverters. Inverters are clustered based on effective impedances to an infinite bus (modeling the transmission-distribution boundary) and for each cluster, an aggregate dynamical model is developed to preserve the structure and order of each individual inverter state-space model. The K-means algorithm is leveraged for clustering and a suitable linearization of the power-flow equations reduces computational burden involved in determining terminal voltages for the clusters. Numerical simulation results for the IEEE 37-bus feeder system demonstrate the accuracy and computational benefits of the proposed aggregation method.
Original language | English (US) |
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Article number | 8843913 |
Pages (from-to) | 1520-1530 |
Number of pages | 11 |
Journal | IEEE Transactions on Power Systems |
Volume | 35 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2020 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 1969-2012 IEEE.
Keywords
- Distribution network
- model reduction
- three-phase inverter
- voltage-source inverter