TY - GEN
T1 - Optimization-Based Estimation of Microgrid Equivalent Parameters for Voltage and Frequency Dynamics
AU - Bhujel, Niranjan
AU - Hansen, Timothy M.
AU - Tonkoski, Reinaldo
AU - Tamrakar, Ujjwol
AU - Byrne, Raymond H.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6/28
Y1 - 2021/6/28
N2 - Microgrid parameter estimation is essential to enable optimal voltage and frequency control using distributed energy resources (DER). Microgrid parameters vary through time, e.g., when generation is re-dispatched/committed, during microgrid reconfiguration. Furthermore, sensor measurements are noisy and preservation of the fast dynamics measurements is required, which is difficult to achieve with a lowpass filter. In this paper, a moving horizon estimation (MHE) approach is applied to estimate microgrid parameters for voltage and frequency support. The proposed approach estimates the states i.e., frequency, rate of change of frequency, grid voltage and current, and system parameters i.e., inertia, damping, and equivalent impedance. The MHE is formulated as an optimization problem using data over a fixed past horizon and solved online such that the sum of the square of measurement noise and process noise is minimized. Results showed that the proposed approach was able to estimate microgrid states, parameters, and disturbances within 5% for most values, which is sufficient to use in microgrid voltage and frequency control.
AB - Microgrid parameter estimation is essential to enable optimal voltage and frequency control using distributed energy resources (DER). Microgrid parameters vary through time, e.g., when generation is re-dispatched/committed, during microgrid reconfiguration. Furthermore, sensor measurements are noisy and preservation of the fast dynamics measurements is required, which is difficult to achieve with a lowpass filter. In this paper, a moving horizon estimation (MHE) approach is applied to estimate microgrid parameters for voltage and frequency support. The proposed approach estimates the states i.e., frequency, rate of change of frequency, grid voltage and current, and system parameters i.e., inertia, damping, and equivalent impedance. The MHE is formulated as an optimization problem using data over a fixed past horizon and solved online such that the sum of the square of measurement noise and process noise is minimized. Results showed that the proposed approach was able to estimate microgrid states, parameters, and disturbances within 5% for most values, which is sufficient to use in microgrid voltage and frequency control.
KW - Energy storage systems
KW - microgrids
KW - moving horizon estimation
KW - optimal state and parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=85112378450&partnerID=8YFLogxK
U2 - 10.1109/PowerTech46648.2021.9494858
DO - 10.1109/PowerTech46648.2021.9494858
M3 - Conference contribution
AN - SCOPUS:85112378450
T3 - 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings
BT - 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Madrid PowerTech, PowerTech 2021
Y2 - 28 June 2021 through 2 July 2021
ER -