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Title: Supervised Learning for Distribution Secondary Systems Modeling: Improving Solar Interconnection Processes

Journal Article · · IEEE Transactions on Sustainable Energy
 [1];  [1];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [2];  [3];  [4]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Kevala, Inc., San Francisco, CA (United States)
  3. Carnegie Mellon Univ., Pittsburgh, PA (United States)
  4. National Information Solutions Cooperative, Lake Saint Louis, MO (United States)
+ Show Author Affiliations

The current interconnection process and hosting capacity analysis for distributed energy resources (DERs), such as photovoltaics (PV) and battery energy storage systems, are based on analyzing grid network constraints (voltage and thermal) using only medium-voltage distribution network models. This is because most utilities do not have secondary low-voltage system models that connect service transformers and residential customers. This is important because in many cases the main impact of interconnecting DERs could occur on the low-voltage distribution systems. This paper proposes a supervised learning method to approximate local secondary models to improve the interconnection process. The proposed supervised learning method includes a decision tree model that predicts the secondary topology and a logistic regression model that predicts conductor types. The case studies demonstrate the benefits of including secondary low-voltage circuits in the interconnection process. We report the proposed modeling methodology is readily scalable and thus can reduce the cost and effort of PV interconnection for the industry and stakeholders.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1843352
Report Number(s):
NREL/JA-5C00-80234; MainId:42437; UUID:74adf01a-b8a3-404d-8ff3-64fcae74d473; MainAdminID:63695
Journal Information:
IEEE Transactions on Sustainable Energy, Journal Name: IEEE Transactions on Sustainable Energy Journal Issue: 2 Vol. 13; ISSN 1949-3029
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English

References (19)

Workflow and Process Automation of Residential DER Interconnection Review conference February 2021
Secondary circuit model creation and validation with AMI and transformer measurements conference September 2016
Detailed Primary and Secondary Distribution System Feeder Modeling Based on AMI Data conference April 2021
Identifying Errors in Service Transformer Connections conference August 2020
Model-Free Voltage Calculations for PV-Rich LV Networks: Smart Meter Data and Deep Neural Networks conference June 2021
Verifying data integrity: If you cannot believe the data, how can you believe the analytics? conference April 2013
Learning With End-Users in Distribution Grids: Topology and Parameter Estimation journal September 2020
Distribution Feeder Modeling for Time-Series Simulation of Voltage Management Strategies conference April 2018
Modeling Secondary Services in Engineering and Mapping journal January 2012
Secondary Low-Voltage Circuit Models—How Good is Good Enough? journal January 2018
Processing and Correction of Secondary System Models in Geographic Information Systems journal June 2019
Representative Residential LV Feeders: A Case Study for the North West of England journal January 2016
PaToPa: A Data-Driven Parameter and Topology Joint Estimation Framework in Distribution Grids journal July 2018
Advanced Metering for Phase Identification, Transformer Identification, and Secondary Modeling journal June 2013
Leveraging AMI Data for Distribution System Model Calibration and Situational Awareness journal July 2015
Identifying Topology of Low Voltage Distribution Networks Based on Smart Meter Data journal September 2018
Distribution System Parameter and Topology Estimation Applied to Resolve Low-Voltage Circuits on Three Real Distribution Feeders journal July 2019
A few useful things to know about machine learning journal October 2012
Voltage Correlations in Smart Meter Data
  • Mitra, Rajendu; Kota, Ramachandra; Bandyopadhyay, Sambaran
  • KDD '15: The 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining https://doi.org/10.1145/2783258.2788594
conference August 2015

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Related Subjects

14 SOLAR ENERGY
24 POWER TRANSMISSION AND DISTRIBUTION
decision tree
distribution secondary
logistic regression
solar interconnection
supervised learning