TY - JOUR
T1 - Detailed Primary and Secondary Distribution System Model Enhancement Using AMI Data
AU - Montano-Martinez, Karen
AU - Thakar, Sushrut
AU - Ma, Shanshan
AU - Soltani, Zahra
AU - Vittal, Vijay
AU - Khorsand, Mojdeh
AU - Ayyanar, Rajapandian
AU - Rojas, Cynthia
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2022
Y1 - 2022
N2 - Reliable and accurate distribution system modeling, including the secondary network, is essential in examining distribution system performance with high penetration of distributed energy resources (DERs). This paper presents a highly automated, novel method to enhance the accuracy of utility distribution feeder models to capture their performance by matching simulation results with corresponding field measurements. The method is demonstrated using an actual feeder from an electrical utility with high penetration of DERs. The method proposed uses advanced metering infrastructure (AMI) voltage and derived active power measurements at the customer level, and data acquisition systems (DAS) measurements at the feeder-head, in conjunction with an AC optimal power flow (ACOPF) to estimate customer active and reactive power consumption over a time horizon, while accounting for unmetered loads. The ACOPF uses the measured voltage magnitudes, derived active power measurements, and the feeder head measurements to obtain a complete active power and reactive power capture of the feeder loads. Additionally, the method proposed estimates both voltage magnitude and angle for each phase at the unbalanced distribution substation. The accuracy of the method developed is verified in two stages: by comparing the time-series power flow results obtained from the enhancement algorithm with OpenDSS results and with the field measurements available. The proposed approach seamlessly manages the data available from the optimization procedure through the final model verification automatically.
AB - Reliable and accurate distribution system modeling, including the secondary network, is essential in examining distribution system performance with high penetration of distributed energy resources (DERs). This paper presents a highly automated, novel method to enhance the accuracy of utility distribution feeder models to capture their performance by matching simulation results with corresponding field measurements. The method is demonstrated using an actual feeder from an electrical utility with high penetration of DERs. The method proposed uses advanced metering infrastructure (AMI) voltage and derived active power measurements at the customer level, and data acquisition systems (DAS) measurements at the feeder-head, in conjunction with an AC optimal power flow (ACOPF) to estimate customer active and reactive power consumption over a time horizon, while accounting for unmetered loads. The ACOPF uses the measured voltage magnitudes, derived active power measurements, and the feeder head measurements to obtain a complete active power and reactive power capture of the feeder loads. Additionally, the method proposed estimates both voltage magnitude and angle for each phase at the unbalanced distribution substation. The accuracy of the method developed is verified in two stages: by comparing the time-series power flow results obtained from the enhancement algorithm with OpenDSS results and with the field measurements available. The proposed approach seamlessly manages the data available from the optimization procedure through the final model verification automatically.
KW - AC optimal power flow (ACOPF)
KW - Distributed energy resources
KW - Distribution system
KW - Load modeling
KW - Power system measurements
KW - Power system modeling
KW - Smart grids
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U2 - 10.1109/OAJPE.2021.3125900
DO - 10.1109/OAJPE.2021.3125900
M3 - Article
AN - SCOPUS:85123712789
SN - 2332-7707
VL - 9
SP - 2
EP - 15
JO - IEEE Open Access Journal of Power and Energy
JF - IEEE Open Access Journal of Power and Energy
ER -