Streamlined Method for Determining Distribution System Hosting Capacity

Abstract

This document outlines the methodology of a streamlined analysis to determine the amount of photovoltaics that can be accommodated on a distribution feeder before adverse impacts occur (commonly termed hosting capacity). The solution can effectively be used in screening new interconnection requests as well as to estimate how much and where PV can be located such that grid upgrades are minimized. The method is being implemented in commercial distribution system analysis tools where it can be applied system-wide or on individual feeders. The streamlined analysis of an individual feeder would take in the order of minutes compared to hours for a detailed analysis. Application of the results include improved screening tools, visualization of hosting capacity constrained feeders, and identification of problematic locations within a feeder. Speed and accuracy are mandatory, thus the methodology has been compared and validated to detailed analyses.

An Analysis of Photo-Voltaic Hosting Capacity in Finnish Low Voltage Distribution Networks

“…In [12,13], thermal limits of conductors were taken to be one of the network constraints, while the transformer capacity was the performance factor considered in [14,15]. Moreover, voltage unbalance was used as a performance constraint in [7,16].…”

Statistical Inference for Visualization of Large Utility Power Distribution Systems

“…Studies [7,8,[10][11][12][13][14][15]17,18,24,25,27,29] show the application of this approach to validate proposed strategies or devices. In summary, the following are examples of typical applications for snapshot analysis and validation:…”

Stochastic Hosting Capacity in LV Distribution Networks

“…In [8] the authors study the hosting capacity of a number of feeders, considering how the hosting capacity varies if the location of the DG is restricted to specific zones, as well as considering the impact of changes in power factor. In [9], a 'streamlined' approach is contrasted with the authors previous 'detailed' approach [2]. The streamlined method uses network impedance data to study network hosting capacity in a computationally efficient manner.…”