IEEE Power & Energy Magazine - March/April 2015 - 24

Impact
Impact
Impact
Below
Above
Depends
Threshold
Threshold

25

Nonoptimal
DER Location
Optimal
DER Location

Impact

Feeder

20

15

Feeder 14

Impact
Threshold

10
Total DER Penetration
Feeder Voltage Peak Minimum
Total
End of Line
Class Load
Load Length (mi) Length (mi)

5

0

0

1
2
3
4
Hosting Capacity (MW)

3
6
7
14

12.5
12.5
12.5
12.0

4.3
4.4
4.5
4.4

(a)

0.9
1.3
1.1
0.5
(b)

19
6
9
22

Feeder 1

3
2
4
3
(c)

figure 3. (a) Feeder hosting capacity, (b) impact of DER penetration and table showing the characteristics of four apparently similar feeders, and (c) determining the optimal location for DERs.

of service if remedial actions are not taken. If done properly,
a hosting capacity assessment provides a range of information, including:
✔✔ how many DERs can be accommodated without system
upgrades
✔✔ what issues arise at the hosting capacity limits
✔✔ where DERs can be sited so that problems can be avoided
✔✔ the locations where additional DERs are likely to cause
issues on the grid.
Figure 3 illustrates results for these four topics, in this
case specifically related to distributed PVs. The amount of
PVs that can be supported for 28 different feeders is illustrated in Figure 3(a), where the colored regions represent no
issues (green), issues dependent on location (yellow), and
issues regardless of location (red). In many cases, a range of
impacts is observed even where PVs can be more or less optimally placed based on its location. The issues that arise are
because of the increase in impact that comes along with the
increased penetration of DERs, as illustrated in Figure 3(b).
The two images in Figure 3(c) offer a visual interpretation of the hosting capacity plotted against the schematic of
the feeder. The darkness and thickness of the schematic indicate where the DERs can be sited such that adverse issues
are avoided and, conversely, where the DERs are more likely
to be problematic.
One observation that can readily be made is that there is a
considerable range in the amount of DERs that can be easily
accommodated across all the feeders without taking preventative measures. Feeders 3, 6, 7, and 14, in particular, all have
similar peak loads of 4.3-4.5 MW, as shown in Figure 3(b).
24

ieee power & energy magazine

The minimum hosting capacity-as indicated by the green
area in Figure 3(a)-for these four feeders, however, ranges
from 0.6-1.5 MW. Therefore, indicators such as peak load
fail to provide adequate estimates of DER hosting capacity.
A slightly more detailed approach would consider several
feeder characteristics to better understand their impact on a
feeder's ability to accommodate PVs. The four feeders in the
previous example are also in the same voltage class, but it
is clear that basing the analysis on those two characteristics
alone will not improve a determination of impact. Additional
characteristics such as end-of-feeder length could be used in
the clustering, but there is not much variation in those characteristics for the four feeders: they are 2-4 mi long. Out of the
28-feeder data set, the end-of-line length ranges from 1 to 27 mi,
so including line length in a clustering methodology may still
group these four feeders together as being "similar."
In short, such techniques for screening feeders and/or
reducing the number of feeders analyzed reduces the time and
effort that go into analysis. Both these techniques result in
less-than-optimal visibility in terms of how DERs will potentially impact the grid, however, particularly when it comes to
location. Feeder clustering can be used, however, when the
clustering is based on the actual feeder response rather than
topological data. Taking into consideration such things as
where the DERs are located as well as how the feeder responds
provides a better metric for clustering.
There is a complex interrelationship among the forces that
determine how electricity flows in a conventional distribution
system, and that complexity deepens when DERs produce
two-way flows. The location, size, and DER technology are
march/april 2015



Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - March/April 2015

IEEE Power & Energy Magazine - March/April 2015 - Cover1
IEEE Power & Energy Magazine - March/April 2015 - Cover2
IEEE Power & Energy Magazine - March/April 2015 - 1
IEEE Power & Energy Magazine - March/April 2015 - 2
IEEE Power & Energy Magazine - March/April 2015 - 3
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IEEE Power & Energy Magazine - March/April 2015 - 96
IEEE Power & Energy Magazine - March/April 2015 - Cover3
IEEE Power & Energy Magazine - March/April 2015 - Cover4
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