skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: On Distributed PV Hosting Capacity Estimation, Sensitivity Study, and Improvement

Abstract

This paper first studies the estimated distributed PV hosting capacities of seventeen utility distribution feeders using the Monte Carlo simulation based stochastic analysis, and then analyzes the sensitivity of PV hosting capacity to both feeder and photovoltaic system characteristics. Furthermore, an active distribution network management approach is proposed to maximize PV hosting capacity by optimally switching capacitors, adjusting voltage regulator taps, managing controllable branch switches and controlling smart PV inverters. The approach is formulated as a mixed-integer nonlinear optimization problem and a genetic algorithm is developed to obtain the solution. Multiple simulation cases are studied and the effectiveness of the proposed approach on increasing PV hosting capacity is demonstrated.

Authors:
;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1369125
Report Number(s):
NREL/JA-5D00-67598
Journal ID: ISSN 1949-3029
DOE Contract Number:
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: IEEE Transactions on Sustainable Energy; Journal Volume: 8; Journal Issue: 3
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; photovoltaic; hosting capacity; voltage improvement; distribution network management; smart inverter; voltage regulation; network reconfiguration; genetic algorithm

Citation Formats

Ding, Fei, and Mather, Barry. On Distributed PV Hosting Capacity Estimation, Sensitivity Study, and Improvement. United States: N. p., 2017. Web. doi:10.1109/TSTE.2016.2640239.
Ding, Fei, & Mather, Barry. On Distributed PV Hosting Capacity Estimation, Sensitivity Study, and Improvement. United States. doi:10.1109/TSTE.2016.2640239.
Ding, Fei, and Mather, Barry. Sat . "On Distributed PV Hosting Capacity Estimation, Sensitivity Study, and Improvement". United States. doi:10.1109/TSTE.2016.2640239.
@article{osti_1369125,
title = {On Distributed PV Hosting Capacity Estimation, Sensitivity Study, and Improvement},
author = {Ding, Fei and Mather, Barry},
abstractNote = {This paper first studies the estimated distributed PV hosting capacities of seventeen utility distribution feeders using the Monte Carlo simulation based stochastic analysis, and then analyzes the sensitivity of PV hosting capacity to both feeder and photovoltaic system characteristics. Furthermore, an active distribution network management approach is proposed to maximize PV hosting capacity by optimally switching capacitors, adjusting voltage regulator taps, managing controllable branch switches and controlling smart PV inverters. The approach is formulated as a mixed-integer nonlinear optimization problem and a genetic algorithm is developed to obtain the solution. Multiple simulation cases are studied and the effectiveness of the proposed approach on increasing PV hosting capacity is demonstrated.},
doi = {10.1109/TSTE.2016.2640239},
journal = {IEEE Transactions on Sustainable Energy},
number = 3,
volume = 8,
place = {United States},
year = {Sat Jul 01 00:00:00 EDT 2017},
month = {Sat Jul 01 00:00:00 EDT 2017}
}
  • A 15% PV penetration threshold is commonly used by utilities to define photovoltaic (PV) screening methods where PV penetration is defined as the ratio of total solar PV capacity on a line section to peak load. However, this method doesn't take into account PV locational impact or feeder characteristics that could strongly change the feeder's capability to host PVs. This paper investigates the impact of PV location and phase connection type on PV hosting capacity, and then proposes a fast-track PV screening approach that leverages various PV hosting capacity metric responding to different PV locations and types. The proposed studymore » could help utilities to evaluate PV interconnection requests and also help increase the PV hosting capacity of distribution feeders without adverse impacts on system voltages.« less
  • Often PV hosting capacity analysis is performed for a limited number of distribution feeders. For medium - voltage distribution feeders, previous results generally analyze less than 20 feeders, and then the results are extrapolated out to similar types of feeders. Previous hosting capacity research has often focused on determining a single value for the hosting capacity for the entire feeder, whereas this research expands previous hosting capacity work to investigate all the regions of the feeder that may allow many different hosting capacity values wit h an idea called locational hosting capacity (LHC)to determine the largest PV size that canmore » be interconnected at different locations (buses) on the study feeders. This report discusses novel methods for analyzing PV interconnections with advanced simulati on methods. The focus is feeder and location - specific impacts of PV that determine the locational PV hosting capacity. Feeder PV impact signature are used to more precisely determine the local maximum hosting capacity of individual areas of the feeder. T he feeder signature provides improved interconnection screening with certain zones that show the risk of impact to the distribution feeder from PV interconnections.« less
  • In this paper, we present the effect of installation parameters (tilt angle, height above ground, and albedo) on the bifacial gain and energy yield of three south-facing photovoltaic (PV) system configurations: a single module, a row of five modules, and five rows of five modules utilizing RADIANCE-based ray tracing model. We show that height and albedo have a direct impact on the performance of bifacial systems. However, the impact of the tilt angle is more complicated. Seasonal optimum tilt angles are dependent on parameters such as height, albedo, size of the system, weather conditions, and time of the year. Formore » a single bifacial module installed in Albuquerque, NM, USA (35 degrees N) with a reasonable clearance (~1 m) from the ground, the seasonal optimum tilt angle is lowest (~5 degrees) for the summer solstice and highest (~65 degrees) for the winter solstice. For larger systems, seasonal optimum tilt angles are usually higher and can be up to 20 degrees greater than that for a single module system. Annual simulations also indicate that for larger fixed-tilt systems installed on a highly reflective ground (such as snow or a white roofing material with an albedo of ~81%), the optimum tilt angle is higher than the optimum angle of the smaller size systems. We also show that modules in larger scale systems generate lower energy due to horizon blocking and large shadowing area cast by the modules on the ground. For albedo of 21%, the center module in a large array generates up to 7% less energy than a single bifacial module. To validate our model, we utilize measured data from Sandia National Laboratories' fixed-tilt bifacial PV testbed and compare it with our simulations.« less
  • Abstract not provided.
  • Abstract not provided.