A Two-Step Load Disaggregation Algorithm for Quasi-static Time-series Analysis on Actual Distribution Feeders

This paper focuses on developing a two-step load disaggregation method for conducting quasi-static time-series analysis using actual distribution feeder data. This can help utilities conduct power flow studies using smart meter measurements to assess the impact of high penetration of distributed energy resources. In the first step, load profiles of residential and commercial buildings obtained from smart meter data are used to match the load profile at the feeder head. This step will determine the number of residential and commercial loads on the feeder. The second step is to allocate the selected load profiles to each load node based on its transformer rating. This allows each load node to have its own load profile and the aggregation of those nodal load profiles matches closely to the metered feeder load shape at the substation. This algorithm is validated using smart meter data and the SCADA data of a real feeder. We compared the performance of the proposed method with the traditional load allocation method (i.e. use the feeder load shape for all subsequent load nodes scaling by the transformer capacities) when conducting quasi-static power flow studies. Results show that the proposed algorithm matches the utility data well and the obtained voltage profiles reveal more voltage dynamics than using the conventional load allocation method.

[1]  Charles J. Mozina Impact of smart grid and green power generation on distribution systems , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[2]  Nader Samaan,et al.  Load Aggregation Methods for Quasi-Static Power Flow Analysis on High PV Penetration Feeders , 2018, 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D).

[3]  Renke Huang,et al.  Voltage-load sensitivity matrix based demand response for voltage control in high solar penetration distribution feeders , 2017, 2017 IEEE Power & Energy Society General Meeting.

[4]  Saidur Rahman Abdul Hakim A review on global wind energy policy, Renewable and Sustainable Energy Reviews , 2010 .

[5]  Paul Denholm,et al.  Renewable Electricity Futures Study. Volume 1. Exploration of High-Penetration Renewable Electricity Futures , 2012 .

[6]  K. M. Muttaqi,et al.  Effectiveness of traditional mitigation strategies for neutral current and voltage problems under high penetration of rooftop PV , 2013, 2013 IEEE Power & Energy Society General Meeting.

[7]  P. Cappers,et al.  Demand Response in U.S. Electricity Markets: Empirical Evidence , 2010 .

[8]  Ning Lu,et al.  Control and Size Energy Storage Systems for Managing Energy Imbalance of Variable Generation Resources , 2015, IEEE Transactions on Sustainable Energy.

[9]  Renke Huang,et al.  A three-stage enhanced reactive power and voltage optimization method for high penetration of solar , 2017, 2017 IEEE Power & Energy Society General Meeting.

[10]  Ning Lu,et al.  A Graphical Performance-Based Energy Storage Capacity Sizing Method for High Solar Penetration Residential Feeders , 2017, IEEE Transactions on Smart Grid.

[11]  V. Ramachandran,et al.  Steady state analysis of high penetration PV on utility distribution feeder , 2012, PES T&D 2012.

[12]  B. A. Mather Quasi-static time-series test feeder for PV integration analysis on distribution systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[13]  Ning Lu,et al.  A probabilistic-based PV and energy storage sizing tool for residential loads , 2016, 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D).

[14]  Ning Lu,et al.  Continuation power flow analysis for PV integration studies at distribution feeders , 2017, 2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT).

[15]  H. Solangib,et al.  A review on global solar energy policy , 2011 .