As the penetration of distributed energy resources (DERs) continues to grow across many parts of North America and around the world, it is becoming increasingly important to model and study the impacts that DER may have on bulk power system (BPS) reliability. In particular, representing DER in the interconnectionwide powerflow and dynamics cases using reasonable modeling assumptions is becoming critical. Various forms of DER model verification, using historical data and future projections of gross demand and DER, will provide a technical basis for the modeling assumptions applied. Further, understanding the operating conditions and challenges that may be faced when attempting to study these conditions in planning models is also important. This paper provided recommended practices, and a case creation and verification process, for integrating DER into planning assessments of interconnection-wide reliability. These practices can be expanded or adapted by local transmission planners for their footprint.

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51
Summary
Asthepenetrationofdistributedenergyresources(DERs)
continues to grow across many parts of North America
and around the world, it is becoming increasingly
important to model and study the impacts that DER
may have on bulk power system (BPS) reliability. In
particular, representing DER in the interconnection-
wide powerflow and dynamics cases using reasonable
modeling assumptions is becoming critical. Various
forms of DER model verification, using historical data
and future projections of gross demand and DER, will
provide a technical basis for the modeling assumptions
applied. Further, understanding the operating conditions
andchallengesthatmaybefacedwhenattemptingtostudy
these conditions in planning models is also important.
This paper provided recommended practices, and a case
creation and verification process, for integrating DER
into planning assessments of interconnection-wide
reliability. These practices can be expanded or adapted
by local transmission planners for their footprint.
1. Introduction
Distributed energy resources (DERs) are being installed
across North America, driven by state renewable
portfolio standards and economic incentives. Accurately
modeling and studying the impacts of DER on the bulk
power system (BPS) is becoming an integral part of BPS
reliability planning. Planners are adapting their modeling
assumptions and study techniques to ensure a reasonable
representation of aggregate DER as the generation
mix continues to change. This adaptation starts by
understanding the installed and expected capacity of
DER as well as the operating characteristics of the DER.
The variability and uncertainty of DER drive the need
for accurate modeling and reasonable assumptions in the
dispatch of DER in planning base cases.
Aggregate DERs can be explicitly represented in the
root-mean-square (rms) positive sequence powerflow
and dynamics cases, and should not be netted with the
gross load [1]. Differentiating between the dynamics
of the load and the aggregate DER is becoming an
important element of base case creation. Verification of
the dispatch and assumptions used in the planning cases
will be critical, as investment decisions may rely on the
assumptions used for these resources.
Similar to end-use loads modeled in bulk power
system (BPS) reliability study cases, an aggregate DER
representation is used. The aggregate DER is typically
modeled at the bus-, load-, or feeder-level. In the steady-
state powerflow base cases, the DER may be modeled as
either a utility-scale DER (U-DER) or retail-scale DER
(R-DER) [2]. Fig. 1 shows the recommended modeling
approach for DER in North America [3],[4],[5]. In either
case, DER is explicitly differentiated from end-use load
and a dynamic model is used to represent these aggregate
resources for stability simulations [6],[7].
Grid disturbances in California have shown that BPS
fault events can have an impact on neighboring entities,
both at the transmission and distribution levels [8]. This
drives the need for transmission planners to ensure
accurate modeling and simulations both in their footprint
as well as neighboring systems and across the BPS.
Verification rocess for DER
odeling in nterconnection-wide
ase ase reation
R. QUINT1
*, S. SHAO2
, J. SKEATH1
, B. MARSZALKOWSKI3
,
D. RAMASUBRAMANIAN4
, I. GREEN5
, M. ELNASHAR6
, P. WANG6
, S. XU2
1
North American Electric Reliability Corporation, USA,
2
Pacific Gas & Electric, USA, 3
Independent System Operator of New England, USA,
4
Electric Power Research Institute, USA, 5
California Independent System Operator, USA,
6
Independent Electricity System Operator, Canada
United States of America, Canada
KEYWORDS
distributed energy resource, gross load, modeling, net load, reliability
* ryan.quint@nerc.net

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52
of variability, redefining “stressed system conditions,”
and a reconsideration as to whether system peak demand
is the most critically stressed condition to be studied.
Industry planners acknowledge that the TPL-001-4
standard has gaps in what is required compared to what
the actual most stressed conditions may be. Consider, for
example, Figs. 2-3 which show the solar PV DER (D-
PV) and load profiles for a typical summer and spring
day in ISO New England (ISO-NE) region. In this case,
consider the following:
Maximum gross demand: Gross demand peaks
slightly before 1–2 PM local time and D-PV output is
around 90% of its daily maximum (see Fig. 2-left).
Maximum net demand: Net demand peaks at
around 6 PM local time when D-PV has ramped
down to nearly 10% (see Fig. 2-left).
Minimum gross demand: Minimum gross demand
still occurs during early morning around 3 AM local
time when D-PV is at zero (see Fig. 2-right).
Minimum net demand: Minimum net demand, due
to D-PV growth, is shifting the midday net load down
to points that will drop below the 3 AM gross load
minimum.As penetration of D-PV continues to grow,
the minimum net demand period will occur around
midday local time when D-PV output is around
90-95%. Due to the significantly different dispatch
conditions, both potential operating states should be
studied.
These types of conditions are being observed across
North America. Systems from California to New
England are experiencing the impacts of DER on net
load reduction during daytime hours. Areas with winter
extremes will need to consider time of day and dispatch
at their peak conditions as well.As the time of day/year of
occurrence of peak and low load changes with increases
in DERs, planners must be aware of this as they develop
base cases that are representative of the most stressed
operating conditions. Further, efforts should be made to
verify these stressed conditions with real-time operating
data.
Base Case Assumptions for Future DER and Load
Dispatch – PG&E Example
Future year base cases use assumptions on DER (and
demand) forecasts. Accurately forecasting these
quantities is critical for developing a base case that
Planning studies typically use an interconnection-wide
base case as the starting point for modeling, developed
per NERC Reliability Standard MOD-032-1 in North
America [9]. Those interconnection-wide base cases
have, in some areas, not included representation of the
aggregate DERs.
Fig. 1. Dynamic representation of DER [2], [3]
This paper proposes recommended techniques for
modeling DERs and verifying dispatch assumptions in
the interconnection-wide base cases. While different
modeling practices can be used to accomplish this goal,
the principles described here can be adapted to different
regions and systems.
2. Case setup process
There are many aspects of developing reasonable
assumptions for modeling DER (both R-DER and
U-DER) in reliability studies. These generally start at a
regional or interconnection-wide level and move inward
towards each feeder or transmission-distribution load-
serving transformer (T-D TX). This section describes
these aspects and recommended practices.
DifferentiatingGrossLoadandDERandEstablishing
Case Assumptions
The NERC TPL-001-4 standard requires planners to
study BPS reliability for “system peak load,” (“load” is
more accurately described as “demand” in the context
of this paper) [10]. Implicitly, this refers to gross system
demand rather than net system demand (offset by DERs
at the T-D interface). However, DERs introduce a degree

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53
R-DERs) based on PG&E allocation assumptions
to match the modeled total DER capacity with the
CEC forecasts1
. These differences are trued up for the
purposes of BPS planning.
a. Values for installed DERs reported by PG&E
are often slightly higher than CEC-forecasted
values; however, PG&E future-year forecasts
are often lower than CEC forecasts2
. For
example, PG&E forecast 7,000 MW of DERs
while the CEC forecast closer to 9,000 MW of
DERs for a 2029 case (see Fig. 3).
6. PG&E TP uses solar irradiance profiles based on time
of day and season to adjust DER output for different
base case assumptions.
Fig. 3 illustrates the DER forecasts as well as the
assumption used for DER output in the planning
assessment for peak summer conditions. Note the
slight divergence in the PG&E and CEC forecasts, as
described above. The PG&E forecast is trued up with the
CEC forecasts for developing the base cases. However,
note that the DER output drops to only around 2-3% of
total capacity starting in the 2023 base case. This is due
to the time of projected maximum net demand occurring
later in the evening when DER output is lower. The
maximum net demand shifts from 5 PM PT in the near-
term cases, to 6 PM PT between 2020 and 2023, and
then to 7 PM PT after 2023. This is important to consider
when developing base case assumptions for net load and
DER output.
This process illustrates how PG&E DP coordinates with
thePG&ETPtogatheraccurateDERdataforthepurposes
of BPS modeling. Other entities across North America
are faced with challenges where DER information is
not collected or aggregated at the distribution level,
and significant modeling assumptions are required at
the transmission planning stage. Distribution providers
need to adapt to the rapid increase of DERs, and should
can identify potential reliability issues in the future.
PG&E employs a process that creates relatively accurate
representations of aggregate DERs for use in planning
assessments. PG&E follows the recommended modeling
framework [3],[4], including both U-DER as individual
generators and R-DER as a component of the load
records. The following steps are performed by PG&E to
develop a DER output assumption:
1. PG&E Distribution Planning (PG&E DP) keeps
records of installed capacity for all R-DERs and
aggregates this by feeder. This provides PG&E
Transmission Planning (PG&E TP) with necessary
data for modeling maximum DER capacity in the
base case.
2. Existing DER capacity is incorporated into the base
case based on per-feeder information, which is then
aggregated (typically 4-6 feeders per T-D TX) to
each transmission-distribution T-D TX (generally
represented as a load in the powerflow case) by
PG&E TP. PG&E TP and PG&E DP coordinate to
map feeders and T-D TXs to base case load elements.
This is used as a starting point for existing DER
locations and capacity.
3. The California Energy Commission (CEC), in its
annual Integrated Energy Policy Report, develops
forecasts for various scenarios of baseline installed
solar PV capacity [11]. This data is used as the
assumptions applied to the California Independent
System Operator (CAISO) planning assessments
(PG&E is a member of CAISO).
4. Forecasted DER capacity growth is added to the
base case using feeder-level mapping to develop
specific planning year base cases. For example, a 10-
year projection of DER growth, mapped to specific
feeders and T-D TXs, is used to create the 10-year out
planning base case.
5. DER capacity is scaled in the base case using a
uniform scaling factor applied to all DERs (mostly
Fig. 2. Profiles for Typical “Summer Peak Load” (left) and “Spring Light Load” (right) Days
1 - In the future, PG&E may explore keeping existing DERs fixed and scaling only future DER installation levels to meet CEC forecasts. This is due to changing vintages
of IEEE 1547 installations of DERs.
2 - The discrepancies between PG&E and CEC forecasts of future DER penetrations are simply based on different forecast methodologies. The CEC uses a capacity
factor method and PG&E uses more localized information by feeder.

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54
irradiation, and other data points. Given the capacity
and geographic location of DERs (both R-DER and
U-DER), IESO generates ten years of DERs production.
Next, IESO modifies the hourly demand forecast of the
study year (e.g., year 2029) per the weather conditions
of those ten years of historical wind and solar PV data.
The result is a two column matrix of ten years of data
for different combinations of hourly forecasted demand
and DER production for the study year. This covers a
broad range of load and DER profiles that can be used
in base case creation. Taking one day of load and DER
data profiles mimics the “one day in ten years” loss
of load expectation principle commonly implied for
BPS reliability assessments [12]. Fig. 4 shows gross
demand, DER output, and net demand for a light
loading conditions with high DER penetration. These
profiles are then applied to the planning case as dispatch
assumptions.
Similar methods can be used for developing other base
cases for different conditions. For example, one may
ensure that all DER installations provide some level of
information upon interconnection such that DER data
can be used for accurate planning, operating, and design
of the distribution system and BPS. As the penetration
of DERs grows, the potential modeling inaccuracies
could manifest into reliability issues if forecasted data
is not sufficiently accurate. Regional estimates of DER
forecasts are not suitable under high penetration DER
conditions.
DER Dispatch Assumptions – IESO Example
Weather conditions can impact end-use loads as well
as the production of DERs. The Ontario Independent
Electricity System Operator (IESO) considers correlation
between forecasted demand levels and DER production
to develop its planning base case dispatch assumptions.
Ten years of historical hourly data for wind and solar
PV production in over 400 locations across Ontario are
collected. This data set also includes weather conditions
such as ambient temperature, humidity, angle of solar
Fig. 3. PG&E DER Forecast Comparison
Fig. 4. DER and Light Load Correlation in IESO

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55
performed with respect to DER dispatch assumptions.
This practice of comparing actual DER installation
to modeled projections, as well as year-over-year
comparison, should be integrated into each distribution
entity’s forecasting practices. Transmission planners
can use this information to compare the accuracy and
reasonability of their base case assumptions as well.
Area-Level or T-D Bank-Level Dispatch Analysis
Another form of verification includes analyzing the
extent to which DER is having an impact on net loading
across a larger area. In particular, the powerflow case
can be reviewed to observe variations in net loads. Fig. 6
shows net loading in the PG&E footprint for a 2029 light
spring case with high DER penetration (represented as
R-DER, which offsets the net load calculation in the base
case). The majority of net loads are less than 5 MW, and
about 25% of the load records in the case are actually
back-feeding onto the BPS. Similar comparison of the
entire CAISO footprint determined this percentage of
back-feeding T-D banks to be 22% in the 2021 light
spring (off-peak) case, 28.6% in the 2024 off-peak case,
and 31.5% in the 2029 off-peak case. However, in each
of the peak cases, these DER output percentages are
about 1%.
The amount and level of DER penetration in the base
cases, as illustrated in Fig. 6 for the 2029 spring off-peak
case, appear to be a reasonable match to actual DER
penetration levels in the PG&E area. Analysis of actual
DER levels in the PG&E system, reviewing installed
capacity per feeder and other factors, shows that these
future cases would be a reasonable assumption in DER
growth into the future using existing DER levels as a
baseline. This provides a general understanding of the
trends to be expected in the annual cases created, and
also a foundation for comparison against actual system
conditions. Any discrepancies (i.e., actual % higher
want to study night time light loading conditions since
the DER output will be low (due to no solar irradiance)
or may need to develop similar correlations for summer
peak conditions. In addition, the methods used for DER
dispatch assumptions could vary by type of planning
studies, such as the ones that have local focuses.
3. Case verification process
The process of model verification involves using
historical information (i.e., forecast or disturbance data)
and comparing this to the modeled assumptions applied
in reliability studies. The outcome of this activity
is a determination of whether the model reasonably
represents actual system conditions and behavior.
The first step in verifying the DER output in a future year
planning case is to use historical forecast information to
analyze the accuracy of these assumptions compared
with reality. Fig. 5 shows year-over-year DER forecasts,
particularly behind-the-meter solar PV, in the ISO-
NE region. It is clear that forecasting practices are
improving compared to early forecasts3
that vastly
underestimated the amount of DER installations. The
2017 and 2018 forecasts are fairly accurate for short-
term DER forecasts; however, long-term DER forecast
accuracy continues to be a problem each year. This can
significantly affect the assumptions used to represent
DERs in long-term transmission planning studies. For
example, the 5-year and 10-year DER forecasts in 2014
would have been inaccurate by around 1,800 MW and an
estimated 3,600 MW, respectively.
Fig. 5 illustrates an effective means of analyzing the
accuracy of DER forecasts used for planning assessments
each year. Review of the forecast accuracy can help
determine the level of sensitivity studies that should be
Fig. 5. DER Forecasts in the ISO-NE Region
3 - Forecasts are typically policy-based, and therefore are somewhat subject to speculation regarding future policies around DERs. Early forecasts somewhat discounted
future policies since there were uncertain; however, later forecasts corrected this issue and provided much more accurate forecasts compared to near-term actual values.

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56
Future projections of DER growth at area-, regional-,
or T-D TX-levels can be used in conjunction with the
historical data to increase the confidence level regarding
DER data in the base case. This is particularly useful
for loads with large DER prevalence and for verifying
reasonability of R-DER penetration, which is expected
to grow more linearly (i.e., the method does not estimate
potential large changes caused by new U-DER).
In addition to forecast verification, a “reasonability”
check on the developed base case should also be
performed to determine if the case is realistic. Consider
Table I which compares the case dispatch conditions
between a 2029 summer peak demand case and a spring
light demand case. Highlighted in red are those fields
which deserve attention. Consider first the dispatch
assumptions, based on time of day, for BPS-connected
and DER solar PV. While the summer peak (7 PM PT)
case assumed near-zero solar PV dispatch, the light
spring (1 PM PT) case assumes around 80–90% solar
PV dispatch. This accounts for over 11,500 MW of
than future projected %) warrant additional analysis to
understand these anomalous trends.
Similarly, individual T-D TXs can be analyzed to observe
if DER penetration has changed. Fig. 7 shows the sum
of power flow through two parallel T-D TXs at a single
substation on the same springtime date in each year
from 2014 to 2018. These T-D TXs include a substantial
amount of R-DERs and U-DERs causing back-feed to
the BPS. Each T-D TX is modeled in the powerflow
base case individually. In 2014, there was no DERs on
the distribution feeders, which establishes a baseline. In
2015, a large DER (modelled as U-DER) connected to
the distribution system, which can be observed by the
large change in net load reduction. In subsequent years,
DER penetration has increased slightly and the net load
has continued to slowly decrease. Note that the amount
of load during the early morning, late evening, and night
time hours changes across the year due to many different
factors. More detailed analysis correlating day, season,
temperature, weather conditions, and other factors could
further enhance this analysis.
Fig. 6. PG&E T-D Bank Loading Levels in 2029 Spring Off-Peak Base Case
Fig. 7. Yearly Comparison of Absolute and Normalized T-D Bank Flow at PG&E Substation

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57
necessary for reaching a solved powerflow solution and
are an artefact of variable energy resources displacing
conventional resources to the point where dispatchability
of these resources will become increasingly critical.
Reliance on variable energy resources is straining the
available generation capacity during certain hours
and operating conditions. Reflecting these in base
case dispatch assumptions is becoming increasingly
challenging as the energy-limited resources are not
available during specific hours of the day. Planners
are faced with developing a “reasonable” case with
significantly different dispatch and transmission flows,
leading to potential reliability issues such as high voltage
conditions, transient stability limitations, spinning and
frequency responsive reserve limitations, and other
problems. The next section will explore these issues that
arise when developing base cases with high DERs and
BPS-connected inverter-based resources.
To allow for efficient RMS positive sequence
simulations, distribution system network topology
is kept to a minimal. Only the substation, load step-
generation in the PG&E area.4
Similarly, net and gross
loading in the PG&E footprint go from nearly 29 GW
and 30 GW in the summer peak case to only 9 GW and
16 GW in the spring case, respectively. With such little
net demand, in combination with high BPS-connected
renewables, the majority of the thermal generation is
forced to run near zero output as well. This alone can
cause a number of issues when trying to attain a solved
powerflow base case, due to the limited amount of
dispatchable resources relative to the area net loading.
Further, intertie flows with neighboring areas are
approaching limits in opposite directions under different
operating conditions, which have not been observed
in the past, and will need to be coordinated with these
respective area planners. In the summer, due to high net
demand and solar PV off-line, intertie flows are near
maximum imports from both the Pacific Northwest
and the Southern California regions. Conversely, in the
spring light load case with significant solar PV on-line,
PG&E must export significant amounts of power up to
the Pacific Northwest and down to Southern California
(again, likely not realistic). These dispatch conditions
are not determined by the planner; rather, they are
4 - This is the combination of BPS-connected solar PV and DERs in the PG&E footprint.
Table I: 2029 Summer Peak and Spring Case Comparison
2029 Summer Peak 2029 Light Spring
PG&E* BPS Generation 23287.7 15060.3
Thermal Fossil Fuel 11095.6 1002.7
Geothermal 780.6 778.1
Hydro 5673.5 6125.2
Biomass and Other 550.3 530.5
Wind 1471.8 1467.8
Solar PV 0 4096.5
Battery Energy Storage 0 0
PG&E Muni Gen 3015.4 2471
PG&E Local DER** 45.5 45.5
Nuclear 0 0
Pumping 655 -1457
PG&E* Gross Load 30065.19 16552.11
PG&E* DER 279.63 7497.94
PG&E* Net Load 29785.56 9054.17
Path 66 Into PG&E 4800 -3762
Path 26 Into PG&E 2718 -1518
Other Paths Into PG&E 79 33
PG&E Area Losses 1158.95 759.06
* PG&E area includes municipality demand - ** Generally end-use customers with small diesel gens

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58
If the exact value of losses is not known, then with active
power loss roughly estimated as 5-10% of the feeder
loading when DER active power output is close to zero,
feeder resistance (R) can be determined. Then, feeder
reactance (X) can be solved for in the IEEE 8500 Node
feeder as:
Here, the value of Vend
is obtained either from the voltage
profile as shown in Fig. 8 or an estimate of the voltage
drop across the feeder can be used. Usually, voltage drop
in an urban feeder is around 0.02–0.05 pu while voltage
drop in a rural feeder is around 0.08–0.1 pu. Voltage
drop for feeders serving residential load can be assumed
to be closer to the lower boundary of the range while
voltage drop for commercial load can be assumed to be
closer to the upper boundary.
Solving the equation above results in X = 2.37 pu, which
also includes some portion of reactive power load along
the feeder. From these calculated values, final values
of resistance and reactance of the equivalent feeder
are obtained by subtracting transformer resistance and
reactance. The active and reactive part of the gross
load to be placed at the end of this equivalent feeder
is obtained by subtracting the losses from the power
supplied by the substation.
4. Planning assessment
challenges with DERs
Increasing amounts of DERs, combined with increasing
amounts of BPS-connected inverter-based resources,
are causing grid planners to re-evaluate conventional
methods for ensuring BPS reliability. This section
down transformer, and equivalent feeder impedance
are typically represented. Phase shift in the transformer
should be considered and can usually be obtained from
feeder data. Alternatively, a 30-degree phase difference
between its primary and secondary windings to account
for a commonly used delta-wye connection is also an
appropriate assumption. The MVA base and impedance
of the transformers can also be obtained from feeder
specifications.
Taking the IEEE 8500 node feeder as an example [13],
the MVA base of the transformer is 27.5 MVA while the
reactance is 15.51% on its MVAbase. When converted to
the100MVAsystembase,thereactanceofthetransformer
is 0.5455pu (0.15*100.0/27.5). Values of resistance and
reactance of the equivalent feeder for positive sequence
simulation are calculated by approximating losses in the
entire feeder. The base topology of the feeder (without
any U-DERs or R-DERs) has an electrical loss of 1.21
MW and 2.77 Mvar. Additionally, power supplied
by the substation at 1.05 pu voltage is 11.98 MW and
1.38 Mvar. Assuming that the substation voltage is the
reference voltage, current supplied by the substation can
be calculated as:
With this value of current, feeder resistance and reactance
can be calculated such that losses are maintained.
The resultant value of resistance and reactance can be
calculated as:
Fig. 8. IEEE 8500 Node Feeder Voltage Profile [14]

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59
voltage control can mitigate or alleviate some of these
issues; however, this would need to be coordinated with
the distribution companies given that dynamic voltage
control can cause protection coordination issues on the
distribution network. Lastly, displacement of reactive
capability from BPS-connected generation caused by
increasing DER penetration may potentially cause
voltage stability risks if sufficient reactive reserves are
not carried.
Thedisplacementandpossibleretirementofsynchronous
generation due to their decreased capacity factor caused
by DERs can also have an impact on the ability of
transmission operators to reliable control BPS voltages.
Transmission-connected reactive resources such as
static var compensators (SVCs), static compensators
(STATCOMs), and synchronous condensers may be
used more frequently in the future to provide necessary
dynamic reactive reserves to maintain voltages within
acceptable bounds during normal and emergency grid
conditions.Theinabilitytorelyonsynchronousgeneration
to be on-line during all hours where this reactive power
may be needed poses additional challenges. Developing
reasonable study cases, particularly focusing on dispatch
(displacement) of synchronous resources and potential
outage of transmission-connected reactive devices, will
be critical in the future.
Short Circuit Strength Reduction
The displacement of synchronous generation due to
increased DER penetration (combined with BPS-
connected inverter-based resources) is causing areas
of the grid to have relatively low short circuit strength.
With the increasing uncertainty in the 5-year and
10-year planning horizons, grids may be faced with
unexpected and unstudied operating conditions that
could potentially have low short circuit strength. This
may lead to a propensity of inverter controls instability,
sub-synchronous oscillations, controls interactions,
and other adverse impacts to the BPS [15]. Advanced
screening methods should be applied during the
transmission planning process and even during planned
maintenance outage studies to determine areas where
highlights the predominant impacts that DERs are
having on planning assessments.
BPS Power Flow Variability, Generator Dispatch,
and Voltage Control
Increasing penetration of DERs is driving unexpected
flows across areas of the BPS that have not historically
occurred, creating challenges for transmission planners.
For example, while historical flows between the
Pacific Northwest and California areas of the Western
Interconnection have experienced north-to-south flows
during daytime hours, these patterns are changing with the
growthofDERs.ItisquitecommonforCaliforniatoexport
power to neighboring systems during high DER output
conditions. Further, flows within the CAISO footprint
are rapidly changing, and this variability also causes
issues for localized planning assessments. Synchronous
generation is forced off-line in the study cases at high
DER conditions, causing challenges in assessing BPS
reliability. Planners should ensure that reasonable gross
load values are used in the case, in addition to DER output
levels and BPS-connected synchronous resource (and
other reactive device) dispatch.
BPS Voltage Control and Reliance on Reactive
Resources
As DERs offload the BPS during certain hours,
transmission planners are faced with high voltage
conditions due to the net load reduction across a large
portion of the BPS.5
While historically these conditions
occurred during night time hours, the new dispatch
patterns are causing additional areas of high voltage
conditions to occur midday. In New England, DERs
are often installed in a fixed power factor (sometimes
unity, sometimes not) mode based on the distribution
studies and planned load power factor. BPS reliability
needs and the ability to manage increased variability
across the transmission-distribution system interface
are generally not considered. This causes more operator
actions such as tripping DERs/feeders, changing voltage
schedules after a contingency, or manually changing
taps on auto transformers. Preliminary studies by ISO-
NE have highlighted that DERs operating in dynamic
5 - In addition to net load reduction, another issue identified by ISO-NE in recent DER cluster studies was distribution capacitors were switched in based on seasonal
expectations of when they would historically be needed during peak season (and switched out during off-peak season). With the addition of DERs, capacitors were
switched in during peak season but DERs were also delivering power; hence, significant high voltages were observed. The solution was to install smart capacitors that
monitor distribution feeder power flow.

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60
techniques and DER accounting should be coordinated
with transmission entities, and all distribution entities
should at least move towards feeder-level identification
of DERs. Assumption on aggregate DER profiles and
dispatch made by the transmission planners should also
be coordinated with the distribution entities. California
utilities have requirements in place for DER owners to
submit applications to the distribution provider prior to
operation of DERs, and this has proved highly effective
in the tracking of DER growth in California.
Verification of U-DER and R-DER levels in the case
can be performed in many ways. DER forecasts can
be compared year-over-year and also compared with
historical data to observe trends in forecast accuracy.
DER output patterns should be linked to time of day for
reasonable study assumptions under different operating
conditions. Area-wide net loading can be analyzed to
understand historical and future projects of DER output.
This also provides an indication as to the degree of DER
impact to net loading over time. Individual T-D TXs
with high DER penetration (possibly large negative net
loading) can be analyzed in greater detail to compare
historical data with future projections in the base case.
All of these activities help verify that the modeling
assumptions used in the base case reasonably match
the expected levels of DERs in future planning cases.
Those assumptions of DER output under different
operating conditions can have significant impacts to
BPS performance in the planning assessments. Even
for steady-state and contingency analysis, a number of
performance issues could manifest that will need to be
addressed with creative solutions under highly variable
and uncertain future grid conditions.
Future activities will explore how battery energy storage
connected to the distribution system will impact these
assumptions even further. Distribution-connected
energy storage, as well as DER aggregators and DER
management systems, will add additional layers of
uncertainty to the planning assessments as well.
6. Bibliography
[1] NERC, “Distributed Energy Resources: Connection Modeling and
Reliability Considerations,” Atlanta, GA, Feb 2017.
[2] NERC, “Reliability Guideline: Modeling Distributed Energy
Resources in Dynamic Load Models,” Atlanta, GA, Dec 2016.
low short circuit strength issues could cause wide-area
disturbances [16].
Stability Assessments with DERs
For many of the same reasons described above, DERs
can have an impact on the stable performance of the
BPS following large contingency events. This has been
observed in multiple grid disturbances [8],[17]. During
light load, a decreased amount of responsive resources
may lead to lower stability margins. These conditions, in
combination with potentially lower frequency responsive
reserves and lower system synchronous inertia, are
driving higher rate-of-change-of-frequency (ROCOF)
and may also lead to insufficient frequency response.
In some systems, high ROCOF and large instantaneous
changes in phase may pose risks for DER tripping due
to their present trip settings, which further exacerbates
contingency events on the BPS [17]. Further, appropriate
dynamic models for representation of dynamic behaviour
of DERs [4],[5] along with suitable parameterization
of its parameters [14],[18] must be considered while
carrying out stability assessments.
All of these issues are typically studied in the long-term
planning and near-term planning horizons. However,
accurate assumptions on DER output and performance
drive the results of these studies. Therefore, it is
increasingly important to verify the DER assumptions
used in these assessments and also to be prepared for
greater levels of variability and uncertainty.
5. Conclusions and
recommendations
Reasonable forecasts and representative modeling of
aggregate amounts of DERs is becoming a critical aspect
of the transmission planning case creation process. This
paper provides a flexible set of verification activities to
ensure that the base case used for these studies is suitable
for ensuring reliable operation of the BPS in the future.
Distribution entities firstly need to have visibility and
tracking of DER integration to their systems.Availability
of data from an advanced metering infrastructure (AMI)
would be an ideal source of forecast in order to have
near complete visibility of the output of DER on feeders.
However, many legacy feeders do not presently have
an inherent AMI in place. In lieu of this, forecasting

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61
[13] R. F. Arritt and R. C. Dugan, “The IEEE 8500-node test feeder,”
IEEE PES T&D 2010, New Orleans, LA, 2010, pp. 1-6.
[14] I. Alvarez-Fernandez, D. Ramasubramanian, A. Gaikwad, J.
Boemer, “Parameterization of Aggregated Distributed Energy
Resources (DER_A) Model for Transmission Planning Studies,”
CIGRE Science & Engineering, vol. 15, pp. 158-168, October
2019.
[15] NERC, “Reliability Guideline: Integrating Inverter-Based
Resources into Low Short Circuit Strength Systems,” Atlanta, GA,
Dec 2017.
[16] Guidelines for Studies on Weak Grids with Inverter Based
Resources: A Path from Screening Metrics and Positive Sequence
Simulations to Point on Wave Simulations, EPRI, Palo Alto, CA:
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[17] Ofgem, “Technical Report of the events of 9 August 2019,” 10 Sept
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updates/ofgem-has-published-national-grid-electricity-system-
operator-s-technical-report.
[18] D. Ramasubramanian, I. Alvarez-Fernandez, P. Mitra, A.
Gaikwad, J.C. Boemer, “Ability of Positive Sequence Aggregated
Distributed Energy Resource Model to Represent Unbalanced
Tripping of Distribution Inverters,” 2019 IEEE PES General
Meeting, Atlanta, GA, 2019.
[3] NERC, “Reliability Guideline: Distributed Energy Resource
Modeling,” Atlanta, GA, Sept 2017.
[4] NERC, “Parametrization of the DER_A Model,” Atlanta, GA,
Sept 2019.
[5] R. Quint, et al., “Recommended DER Modeling Practices in North
America,” 25th International Conference and Exhibition on
Electricity Distribution (CIRED), Madrid, Spain, 2019, pp. 1-5.
[6] FERC, “Distributed Energy Resources: Technical Considerations
for the Bulk Power System,” Docket No. AD18-10-000,
Washington, DC, Feb 2018.
[7] P. Pourbeik, et al., “An Aggregate Dynamic Model for Distributed
Energy Resources for Power System Stability Studies,” CIGRE
Science & Engineering, vol. 14, pp. 38-48, June 2019.
[8] NERC, “April and May 2018 Fault Induced Solar Photovoltaic
Resource Interruption Disturbances Report,” Atlanta, GA, Jan
2019.
[9] NERC, “MOD-032-1: Data for Power System Modeling and
Analysis,” Atlanta, GA, May 2014.
[10] NERC, “TPL-001-4: Transmission System Planning Performance
Requirements,” Atlanta, GA, Nov 2014.
[11] California Energy Commission, “Draft 2019 Integrated Energy
Policy Report,” Docket No. 19-IEPR-01, Nov 2019.
[12] NERC, “2018 Long-Term Reliability Assessment,” Atlanta, GA,
Dec 2018.