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Distributed Energy Resources
Technical Considerations for the Bulk Power System

Staff Report
Docket No. AD18-10-000
February 2018

The opinions and views expressed in this staff report do not necessarily represent those of the Federal
Energy Regulatory Commission, its Chairman, or individual Commissioners, and are not binding on the
Commission.

Docket No. AD18-10-000

Table of Contents
Executive Summary ........................................................................................................... 3
1.

Background ................................................................................................................. 5

Defining DERs ............................................................................................................ 7

Bulk Power System Reliability Considerations for DERs.................................... 10
3.1

Potential DER Reliability Issues ...................................................................... 10

3.1.1 The Lack of DER Data and the Implications for the Bulk Power System ....... 11
3.1.2 Coordination between the Bulk Power System and Distribution System ........ 15
3.2

Potential Reliability Benefits of DERs ............................................................. 18

3.2.1 Communication and Technological Capabilities of DERs ............................... 18
3.3
4.

Developments at the Transmission-Distribution Interface: The DSO Model .. 19

Technical Studies and Results ................................................................................. 21
4.1

Role of Distribution Models in Planning Studies (Distribution Modeling)
21

4.1.1 Study Purpose ................................................................................................... 22
4.1.2 Assumptions and Data ...................................................................................... 23
4.1.3 Methodology ..................................................................................................... 24
4.1.4 Results ............................................................................................................... 25
4.2 DERs and System Performance Following Generator Outages (Power
Flow Study) ................................................................................................................... 27
4.2.1 Study Purpose ................................................................................................... 27
4.2.2 Assumptions and Data ...................................................................................... 27
4.2.3 Methodology ..................................................................................................... 30
4.2.4 Results .............................................................................................................. 31
4.3

Impact of DERs on Dispatch (Production Cost Modeling) ........................ 35

4.3.1 Study Purpose ................................................................................................... 35
4.3.2 Assumptions and Data ...................................................................................... 35
4.3.3 Methodology ..................................................................................................... 36
4.3.4 Results ............................................................................................................... 37
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4.4

Ancillary Services Provided by Energy Storage (Distribution Modeling) 38

4.4.1 Study Purpose ................................................................................................... 38
4.4.2 Assumptions and Data ...................................................................................... 39
4.4.3 Methodology ..................................................................................................... 39
4.4.4 Results ............................................................................................................... 40
4.5 Assessing the Benefit of Smart Inverters to Reliability (Distribution
Modeling) ...................................................................................................................... 43
4.5.1 Study Purpose ................................................................................................... 43
4.5.2 Assumptions and Data ...................................................................................... 43
4.5.3 Methodology ..................................................................................................... 43
4.5.4 Results ............................................................................................................... 44
5.

Conclusions ............................................................................................................... 46

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Docket No. AD18-10-000

Executive Summary
Traditionally, distributed energy resources (DERs) referred to small,
geographically dispersed generation resources, such as solar or combined heat and power
(CHP), installed and operated on the distribution system at voltage levels below the
typical bulk power system levels of 100kV. In recent years, DER installations have
increased significantly in some regions of the United States due in part to technology
advances and state energy policies. This report considers how the increasing penetration
and integration of DERs in specific regions may affect bulk power system reliability.
This report focuses primarily on the technical considerations for DERs as they are
currently operated, and does not necessarily address how DERs may participate in the
markets operated by the regional transmission organizations and independent system
operators (RTOs/ISOs).
To this end, FERC staff performed a series of technical assessments using industry
power system models and commercially available power system simulation software to
identify the potential reliability issues and likely benefits to the bulk power system
resulting from an increased penetration of DERs.
Staff’s work identified, at a high level, several key topics that are addressed in this
report and can be summarized as follows:
• The impact of the current common industry modeling practice of netting DERs
with load, 1 which may mask the effects of DER operation;
• DER capabilities for voltage and frequency ride through during contingencies;
• The potential for improved customer-level voltages due to the unloading of the
bulk power system associated with the location of DERs at or near customer
loads;
• Potential effects on system-wide transmission line flows and generation
dispatch due to changing load patterns; and
• The sensitivity of voltage or power needs to different types of DER
applications (i.e., the provision of energy, capacity, or ancillary services).
Overall, the results of this analysis suggest that increasing DER capacity, if not
properly accounted for, could cause reliability concerns for the bulk power system. 2
Further industry discussion is needed to improve and refine the data that is available for
1

Such as described in NERC Reliability Standard MOD-032-1 — Data for Power
System Modeling and Analysis, requiring Load Serving Entities to aggregate Demand at
each bus.
2

DER capacity modeling was based on current trends for technology types,
operational capabilities, and deployment distributions.
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Docket No. AD18-10-000

DERs that will be incorporated into planning and operating models. Collecting and using
the most current and accurate data is key to getting a complete picture of how DERs
affect the bulk power system.
In addition, further discussion and study is needed regarding other issues, such as
sensitivities with higher DER penetration levels, changes in siting patterns, and potential
impacts to the system’s response to events, disruptions and outages, including frequency
events. Further exploration in these areas will help the Commission to track and assess
the impact of changing conditions on the bulk power system to identify emerging trends
and address potential future reliability challenges.

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Docket No. AD18-10-000

1. Background
DER adoption is growing in the United States, due in part to state, local, and
federal policies. In 2016, DERs accounted for about two percent of the installed
generation capacity in the United States, but distributed solar photovoltaic (PV)
installations alone represented over 12 percent of new capacity additions. 3 Certain
regions have experienced disproportionately greater growth in the installed capacity of
DERs. For example, California currently has over 7,000 MW of installed DER capacity 4
as shown in Figure 1, and has set a target to integrate 12,000 MW 5 of DERs by 2020. 6

Twenty-four gigawatts of new utility-scale generating capacity and 3.4 gigawatts
of new distributed small scale photovoltaic were added in 2016 according to the U.S.
Energy Information Administration. See Renewable Generation Capacity Expected to
Account for Most 2016 Capacity Additions, the U.S. Energy Information Administration,
(January 2017), available at https://www.eia.gov/todayinenergy/detail.php?id=29492 and
Electric Power Monthly – Chapter 6: Capacity, the U.S. Energy Information
Administration, (February 2016 with data for December 2016), available at
https://www.eia.gov/electricity/monthly/current_year/february2017.pdf.
4

See Electric Power Sales, Revenue, and Energy Efficiency - Form EIA-861, the
U.S. Energy Information Administration, Release Date: October 6, 2016 with final 2015
data, Next Release date: October 2017, available at
https://www.eia.gov/electricity/data/eia861/index.html and Form EIA-861M (formerly
EIA-826), the U.S. Energy Information Administration, Release Date: February 2017 for
December 2016 data, available at https://www.eia.gov/electricity/data/eia861m/.
5

The 12,000 MW goal does not include energy storage. The energy storage
procurement target is set in Assembly Bill 2514 (California’s investor owned utilities
must procure 1,325 MW of energy storage by 2020) and Assembly Bill 2868
(California’s investor owned utilities must procure up to 500 MW of additional
distributed energy storage). See Energy Storage Systems, A.B. 2514, Skinner. (20092010), available at
http://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=200920100AB2514
and Energy Storage, A.B. 2868, Gatto. (2015-2016), available at
https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201520160AB2868.
(2015-2016), available at
https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201520160AB2868.
6

See Clean Energy Job Plans, Office of the Governor Edmund G. Brown Jr., at 3
(September, 2011), available at https://www.gov.ca.gov/docs/Clean_Energy_Plan.pdf.
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Docket No. AD18-10-000

Further, even without regional policies encouraging DER growth, factors such as
customer desire for self-supply, environmental considerations, and declining acquisition
costs of DER technologies suggest continued DER growth, and the experience in other
countries illustrates the rapid pace at which deployment can occur. 7
Figure 1 – U.S. DER Deployments

Source: The U.S. Energy Information Administration 8
Figure Figure 2 below illustrates the estimated and projected annual installed DER
capacity additions for the United States during 2015-2024. With several states setting
high renewable energy procurement targets, installed capacity could rise rapidly.

Germany added 7,400 MW of solar PV on its low-voltage distribution grid in
one year. See Martin Braun, Integrating PV in Local Distribution Systems – Germany,
(December 2010), available at http://ieapvps.org/index.php?id=9&eID=dam_frontend_push&docID=423.
8

Docket No. AD18-10-000
Figure 2 – U.S. Annual Installed DER Power Capacity Additions by DER Technology, 2015-2024

Source: Navigant analysis 9
2. Defining DERs
Although “distributed energy resource” is a common term in the energy industry,
no uniform DER definition exists. Traditionally, DERs referred to small, geographically
dispersed generation resources, such as solar or CHP, located on the distribution
system. 10 Depending on their size and configuration, distributed energy generation
resources could partially or completely offset consumer electrical demand. They could
also feed surplus energy back into the distribution system or, in some cases, the
transmission system. 11 However, the definition of DERs has evolved to include not only
9

See Navigant, Take Control of Your Future, Part II: The Power of Customer
Choice and Changing Demands, May 9, 2016, available at
https://www.navigantresearch.com/blog/take-control-of-your-future-part-ii-the-power-ofcustomer-choice-and-changing-demands.
10

See NARUC, Distributed Energy Resources Rate Design and Compensation
(Nov. 2016), https://pubs.naruc.org/pub.cfm?id=19fdf48b-aa57-5160-dba1-be2e9c2f7ea0
(NARUC DER Manual) at 44.
11

PJM has been facing reverse power flows to the transmission system as a result
of DER output for some time. In 2012, the Net Energy Metering Task Force reported
that 20 out of the 8,096 load buses had negative loads of 10 MWh or more in more than
350 instances during the Jan-Mar 2012 period. See Net Energy Metering Senior Task
Force, 1st Read - Final Report and Proposed Manual Revisions at 4-5, (June 2012),
available at http://www.pjm.com/~/media/committees-groups/task7|Page

Docket No. AD18-10-000

generation resources, but also energy storage, energy efficiency and demand response
resources. Indeed, distributed generation resources are often co-located with, for
example, demand response resources, and may be bundled into net demand such that a
utility may not be able to measure nor have specific information on the characteristics
and/or performance of DERs in its service area.
In a recent proposed rule on electric storage and DER participation in wholesale
markets, the Commission proposed to define a DER as:
A source or sink of power that is located on the distribution system, any subsystem
thereof, or behind a customer meter. These resources may include, but are not limited to,
electric storage resources, distributed generation, thermal storage, and electric vehicles
and their supply equipment. 12 NERC’s working definition of DER, as provided in a
report from the NERC DER Task Force, is “any resource on the distribution system that
produces electricity and is not otherwise included in the formal NERC definition of the
Bulk Electric System.” 13 Some entities, such as the California Public Utility Commission
(CPUC), have a more narrow definition of distributed generation that includes only
renewable resources. 14
NARUC uses a broad DER definition:

forces/nemstf/postings/20120628-first-read-item-04-nemstf-report-and-proposed-manualrevisions.ashx. This trend has continued into 2016. See Ken Schuyler, Net Energy
Injections at Load Busses at 3, (May 2016), available at
http://www.pjm.com/~/media/committees-groups/committees/mrc/20160617special/20160617-item-02-pjm-net-energy-injections-quarterly-review.ashx.
12

See Electric Storage Participation in Markets Operated by Regional
Transmission Organizations and Independent System Operators, 157 FERC ¶ 61,121, at
P 1 (2016) (Storage NOPR). The Commission received several comments on this
proposed definition. Staff cites this definition as an example and notes that the instant
report does not choose a specific definition for DERs.
13

See NERC, Distributed Energy Resources: Connection Modeling and
Reliability Considerations (Feb. 2017),
http://www.nerc.com/comm/Other/essntlrlbltysrvcstskfrcDL/Distributed_Energy_Resour
ces_Report.pdf (NERC DER Task Force Report) at 1.
14

See California Public Utilities Code § 769 (a) (2015), CPUC, available at
http://leginfo.legislature.ca.gov/faces/codes_displaySection.xhtml?lawCode=PUC§i
onNum=769.
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A resource sited close to customers that can provide all or some of their
immediate electric and power needs and can also be used by the system to
either reduce demand (such as energy efficiency) or provide supply to
satisfy the energy, capacity, or ancillary service needs of the distribution
grid. The resources, if providing electricity or thermal energy, are small in
scale, connected to the distribution system, and close to load. Examples of
different types of DER include solar PV, wind, CHP, energy storage,
demand response (DR), electric vehicles (EVs), microgrids, and energy
efficiency (EE). 15
NARUC’s report further argues that defining DERs should be a collaborative
effort between utilities and state and federal entities because of the potential applications
across the entire electric power system and energy markets.
While it is possible to define DERs as a single class of assets, it is also important
to recognize differences within this asset class. For example, bulk power system
reliability issues associated with DERs may differ depending on whether DERs
participate directly in the RTO/ISO markets, or participate in retail compensation
programs, such as net metering. DERs that participate directly in the RTO/ISO markets
provide greater visibility of the resources to system operators because they generally
provide their physical and operational characteristics to the RTO/ISO and are modeled
and dispatched as part of the market’s economic clearing mechanism. 16 As discussed
further below, while it is possible for DERs that are participating in retail compensation
programs to be modeled, dispatched and metered, we understand that the reporting of
such information to bulk power system operators is limited, which in turn limits the
operational awareness about those DERs that are not participating directly in the
RTO/ISO markets.
DERs also comprise a number of different technologies, and the operational
characteristics of those different technologies and how they are modeled, dispatched and
metered must be considered when evaluating their potential reliability impacts on the
bulk power system. Some DER technologies, like electric storage, are completely
controllable, and their controllability offers opportunities for resolving operational
constraints on the transmission and distribution systems. Variable DERs, like solar and
15

NARUC DER Manual at 45.

See, e.g., Docket No. ER16-1085-001, 155 FERC ¶ 61,229 (Order conditionally
accepting CAISO’s tariff revisions to facilitate participation of aggregations of DERs in
CAISO’s energy and ancillary services markets); and ER16-1085-001 (Letter order
accepting CAISO’s filing to comply with 155 FERC ¶ 61,229).
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Docket No. AD18-10-000

wind generation, require operators to forecast accurately their output to identify their
potential effects on system constraints and other operational challenges. However, the
advent of smart inverters, as discussed below, and the aggregation of DER technologies
with complementary capabilities, can help mitigate some of the operational limitations
posed by certain technologies.

3. Bulk Power System Reliability Considerations for DERs
The electric industry has recently conducted several analyses to better understand
the unique characteristics of DERs, how they respond to system conditions, and how they
may be deployed as compared to bulk power system generators. This section presents a
survey of several of these findings and conclusions on how those unique characteristics
may translate into potential reliability issues and benefits as DER penetration increases.
3.1 Potential DER Reliability Issues
The potential impact of DERs, in aggregate, on the bulk power system has
captured the electric industry’s attention in recent years. 17 NERC has asserted that
greater levels of DERs highlight the “need to ensure reliability of the bulk power system
during both normal operation and in response to disturbances.” 18 While industry has
identified several potential reliability issues such as impacts to operations and planning
including modeling, ramping and load forecasting, 19 many of these issues can be
managed with adequate DER data and visibility. As the ISO/RTO Council’s (IRC)
Emerging Technology Report explains, “data is a common theme running through the
DER issue.” 20 However, as discussed below, ensuring the provision of appropriate data
to bulk power system planners and operators can be complicated.

See NERC, Special Report: Potential Bulk System Reliability Impacts of
Distributed Resources (Aug. 2011), http://www.nerc.com/docs/pc/ivgtf/IVGTF_TF-18_Reliability-Impact-Distributed-Resources_Final-Draft_2011.pdf (2011 NERC Report)
at 1.
18

NERC DER Task Force Report at 3.

2011 NERC Report at 19-20.

ISO/RTO Council, Emerging Technologies (Mar. 2017), http://www.isorto.org/Documents/NewsReleases/PUBLIC_IRC_Emerging_Technologies_Report.pdf.
(Emerging Technologies Report) at 11.
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In this section, staff presents the following potential reliability issues identified by
industry that may arise from increased DER penetration:
• The lack of DER data and the resulting implications for the operation,
planning, and design of the bulk power system;
• The need for coordination between the settings and capabilities of resources
connected to the bulk power system and DERs;
• The need for improved modeling practices and capabilities for DERs;
• The effect of DER daily generation profiles on system unit commitment and
ramping needs; and
• The effect of distribution connected variable PV and wind output on day-ahead
load forecasts.
3.1.1 The Lack of DER Data and the Implications for the Bulk Power System
Without adequate data, many bulk power system models and operating tools will
not fully represent the effects of DERs in aggregate. 21 For example, the IRC has argued
that North American ISOs and RTOs should have access to basic data about DERs in
their respective territories, and that the location, size, and technological capabilities of
DERs are examples of critical and reliable data needed to formulate a “comprehensive
strategy for managing an increasingly distributed electricity system.” 22 For example, in
projecting the reliable and efficient management of an increasingly distributed grid,
ERCOT highlights the need for the detailed collection of static DER data 23 from
distribution service providers and transmission service providers to support various
ERCOT grid monitoring functions. 24
In most regions, there is no process in place to provide static DER data to bulk
system operators and planners. 25 In many states with net metering programs, certain
21

NERC DER Task Force Report at 3.

Id. at 11.

Data which is set, typically upon installation, such as the physical and electrical
location of the device as well as its capacity, type and capabilities.
24

ERCOT, Distributed Energy Resources: Reliability Impacts & Recommended
Changes (Mar. 2017),
http://www.ercot.com/content/wcm/lists/121384/DERs_Reliability_Impacts_FINAL.pdf
(ERCOT DER Impacts Report) at 5.
25

Id. at 20.
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Docket No. AD18-10-000

static DER data may be collected through the customer registration process, but
additional effort would be needed for operators and planners to obtain that data. NERC
has identified the need to further study what specific, static DER data is needed for
operators and planners and whether the data to be shared can be standardized or are
subject to regional variation. 26
3.1.1.1 DER Visibility
In its 2016 Long-Term Reliability Assessment, NERC states that many utilities
lack “sufficient visibility” of DERs. 27 This lack of visibility could present certain issues
for bulk power system reliability, including a lack of situational awareness. 28 NERC has
defined situational awareness as “ensuring that accurate information on current system
conditions is continuously available to operators.” 29 This information should include the
potential impact of contingencies and must be comprehensive enough for operators to
“rapidly and fully understand actual operating conditions and take corrective action when
necessary to maintain or restore reliable operations.” 30
In addition to the need for static DER data noted above, DER telemetry data (such
as output) can allow transmission system operators to gain real-time visibility and
situational awareness of behind-the-meter generation. Today, this visibility is limited

NERC, DER Data Collection Guideline Presentation (Aug. 2017),
http://www.nerc.com/comm/Other/essntlrlbltysrvcstskfrcDL/ERSWG_Meeting_Presentat
ions_-_August_2-3_2017_Atlanta_GA.pdf at 13.
27

NERC, 2016 Long-Term Reliability Assessment (Dec. 2016),
http://www.nerc.com/pa/RAPA/ra/Reliability%20Assessments%20DL/2016%20LongTerm%20Reliability%20Assessment.pdf at viii.
28

CAISO, Coordination of Transmission and Distribution Operations in a High
Distributed Energy Resource Electric Grid (June 2017), http://morethansmart.org/wpcontent/uploads/2017/06/MTS_CoordinationTransmissionReport.pdf at 8.
29

See NERC, Real-Time Tools Survey Analysis and Recommendations (Mar.

2008),
http://www.nerc.com/comm/OC/Realtime%20Tools%20Best%20Practices%20Task%20
Force%20RTBPTF%2020/RealTime%20Tools%20Survey%20Analysis%20and%20Recommendations.pdf at 9.
30

Id.
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Docket No. AD18-10-000

because DERs are generally not required to supply telemetry data. 31 PJM explains that,
while the telemetry data for some DER units may be available, “the process for obtaining
the data varies based on the local distribution company.” 32 Furthermore, PJM asserts
that, depending on the level of penetration, DERs could require increased decommitment/re-dispatch of centrally dispatched resources to meet balancing
obligations. 33 The IRC supports the development of a framework by which “increasingly
comprehensive operational data from the distribution system is provided as DER
penetrations reach different thresholds.” 34 A counter-balancing consideration when
assessing the need for more DER information, including the granularity of the data, is the
associated cost that DER owners will incur to provide the information. Requiring
metering or telemetry equipment will impose a cost on DER resources, and that cost will
need to be considered against the benefit of providing the additional information.
Further, the degree to which statistical methods could use static data and telemetry data
from a sample of DER may offer a cost effective real-time visibility without burdening
every DER resource with the cost of telemetry equipment.
The CAISO region provides an example of how a lack of DER data can affect
bulk power system operations such as unit commitment and dispatch. In 2016,
distributed PV totaled 4,903 MW and represented over 10 percent of CAISO’s peak
load. 35 Behind-the-meter DERs are not typically metered unless participating in a

See PJM, PJM’s Evolving Resource Mix and System Reliability (Mar. 2017), ,
http://www.pjm.com/~/media/library/reports-notices/special-reports/20170330-pjmsevolving-resource-mix-and-system-reliability.ashx (PJM Reliability Report) at 21.
32

Id.

Emerging Technologies Report at 11.

NERC DER Task Force Report at 33.
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wholesale market program, 36 and can have the effect of reducing the measured load. 37 In
CAISO, for example, a distribution circuit with a 10 MW load may see 5 MW of load at
the circuit breaker, assuming a 50 percent penetration of solar PV. However, the
underlying 10 MW load is still present, and as solar production declines in the late
afternoon and evening, or as a result of cloud cover, this underlying load will remain
high. 38 From the perspective of the bulk power system operator, the net load translates
into lower than expected loads during the day with much faster increases of load through
the late afternoon and evening than would be the case without DERs. 39 This results in
low bulk power system unit commitment during the day, but very fast resource and
ramping requirements in the late afternoon and evening. 40 These conditions may
challenge the operational capacity of the system during some operating hours. 41
As a result of netting DERs with load, CAISO has stated that it only becomes aware
of the impact of rooftop solar when clouds block the sun and the demand previously
served by rooftop solar suddenly appears. 42 On a clear sunny day, solar PV systems
exhibit consistent energy output; however, when solar panels experience passing clouds,
the solar PV exhibits intermittent energy production, as illustrated in Figure 3.
Transmission operators have identified cloud cover as an issue in areas that have a large
penetration of rooftop solar. It can cause a need for sudden ramping of other generation
36

A behind-the-meter DER is “metered” if an electric meter collects data for the
DER generation separately from the total net customer load. Usually this is not the case,
and a single electric meter collects data for both the load and any DER generation behind
the meter (for example small roof top PV have a single meter with the local load). This
translates to an aggregate of all loads and DERs on a distribution circuit as a single net
load from the perspective of the bulk power system. See ERCOT, ERCOT Concept Paper
on Distributed Energy Resources in the ERCOT Region (Aug. 2015), ,
https://energy.gov/sites/prod/files/2016/02/f29/ERCOT_DER_Whitepaper_082015.pdf
(ERCOT Concept Paper on DERs) at 34.
37

Id. at 33-34.

Id. at 34.

Id.

Larson, How are Distributed Energy Resources Affecting Transmission System
Operators (May 2016), http://www.powermag.com/distributed-energy-resourcesaffecting-transmission-system-operators/?printmode=1.
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Docket No. AD18-10-000

resources to balance the system load, as shown by the staff study summarized in Section
4.1 of this report.
Figure 3 – One-minute PV Generation during a Cloudy Day 43

3.1.2 Coordination between the Bulk Power System and Distribution System
On November 4, 2006, one of the largest and most severe disturbances in Europe
led to a blackout for more than 15 million European households. The Union for the
Coordination of Transmission of Electricity (UCTE) prepared a Final Report 44 on the
event, which contains information and analysis on the underlying causes of the
November 4 disturbance, as well as lessons learned and recommendations to avoid a
43

See EPRI, Distributed PV Monitoring and Feeder Analysis,
http://dpv.epri.com/feeder_j.html.
44

The UCTE is the association of Transmission System Operators in continental
Europe. It aims at providing a reliable market place through the co-ordination of the
operation of electric “power highways” over the entire European mainland. Union for the
Co-ordination of Transmission of Electricity, Final Report – System Disturbance on 4
November 2006 (Jan. 2007),
https://www.entsoe.eu/fileadmin/user_upload/_library/publications/ce/otherreports/FinalReport-20070130.pdf (UCTE Report) at 12.
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Docket No. AD18-10-000

similar event in the future. The report discusses the contributions of DERs to the event,
and offers DER-specific recommendations.
Analysis of the event showed that the proliferation of generating units connected
to the distribution system increased the event’s severity. During the event, cascading
outages and tripped lines caused the UCTE grid to split into three separate systems.
Without imports from the east, the western area of the split faced a supply-demand
imbalance of about 8,940 MW. 45 This imbalance caused the frequency to drop to 49 Hz
from the normal 50 Hz. 46 Immediately following the frequency drop, a significant
amount of DERs, mostly consisting of wind and CHP units, tripped offline, which
exacerbated the supply-demand imbalance and, by increasing the frequency deviation, led
to further outages which increased the size of the event. 47 Furthermore, a lack of
sufficient situational awareness meant that the transmission system operators did not have
access to real-time data for DERs, preventing a better evaluation of system conditions. 48
Ensuring the visibility and situational awareness of DERs, as well as accurately modeling
their response to events to avoid unforeseen tripping, could help prevent similar events in
the United States as DER penetration levels increase. Further, new revisions to the
Institute of Electrical and Electronics Engineers (IEEE) 1547 Standard for
Interconnecting Distributed Resources with Electric Power Systems are expected to
leverage recent technology updates by requiring ride through capabilities in newly
interconnecting DERs, which would help to avoid a parallel event in the United States. 49
The final UCTE Report recommended several steps be taken to address the
different disconnection requirements between generators connected to the transmission
system and those connected to the distribution system, in light of the role of DERs in the
November 4 event. Specifically, the UCTE Report recommended that “requirements to
45

Id. at 25.

Since DERs are connected to the distribution grid, the relevant standards for
their performance during a frequency drop are less constraining than those connected to
the transmission grid. At the time of the event they typically would have to withstand a
frequency drop to 49.5 Hz. A significant amount of DER units tripped during the event
because the frequency dropped below the predefined threshold of 49.5 Hz. Id. at 25.
48

Id. at 7.

Staff notes that while the IEEE 1547 provides a uniform standard for the
interconnection of distributed resources, it must be adopted by a jurisdiction to have
effect.
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be fulfilled by generation units connected to the distribution grid should be the same in
terms of behavior during frequency and voltage variations as for the units connected to
the transmission network…these requirements should be applied also to units already
connected to transmission and distribution grids.” 50 The UCTE Report also
recommended that transmission system operators receive on-line data of generation
connected to the distribution provider 51 grids (in at least one-minute increments). 52
In the U.S., the topic of interconnection requirements has received attention as
well. In a 2013 report, NERC found that a lack of coordination between small generating
facilities and the bulk power system can lead to events where system load imbalance may
increase during frequency excursions or voltage deviations, due to the disconnection of
DERs, which in turn may exacerbate a disturbance on the bulk power system. 53 Relevant
to that issue, in Order No. 828, 54 the Commission revised the pro forma Small Generator
Interconnection Agreement (SGIA) to harmonize voltage and frequency ride through
requirements for newly interconnecting small generating facilities (no larger than 20
MW) with those already in place for large generating facilities (larger than 20 MW).
Order No. 828 requires newly interconnecting small generating facilities to meet the
same requirements as large generating facilities to ride through abnormal frequency and
voltage events (i.e., to not disconnect during such events). 55 While Order No. 828 applies
only to generating facilities interconnecting to Commission-jurisdictional facilities
through an SGIA, the Commission communicated its hope that the rule would be helpful
to states when updating their own rules for interconnection to the distribution system,
50

Id. at 62.

As defined by the NERC Glossary of Terms (Aug. 2017),
http://www.nerc.com/files/glossary_of_terms.pdf.
52

Id. at 62.

See NERC, Integration of Variable Generation Task Force Draft Report:
Performance of Distributed Energy Resources During and After System Disturbance
(Dec. 2013),
http://www.nerc.com/comm/PC/Integration%20of%20Variable%20Generation%20Task
%20Force%20I1/IVGTF17_PC_FinalDraft_December_clean.pdf.http://www.nerc.com/c
omm/PC/Integration%20of%20Variable%20Generation%20Task%20Force%20I1/IVGT
F17_PC_FinalDraft_December_clean.pdf.
54

Requirements for Frequency and Voltage Ride Through Capability of Small
Generating Facilities, 156 FERC ¶ 61,062 (year) (Order No. 828).
55

Id. at P 21.
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while acknowledging that states are under no obligation to adopt the provisions of the
Commission’s proposal. 56 As discussed below, technical DER interconnection standards,
such as the IEEE 1547 Standard, are increasingly incorporating advanced features and
grid friendly services such as ride through capabilities. However, in regions where
clusters of DERs have already been installed without ride through requirements, NERC’s
2013 observation remains relevant.
3.2 Potential Reliability Benefits of DERs
As DER penetration increases, there may be several associated reliability benefits
to the bulk power system. For example, by providing power close to the customer, DERs
can serve to reduce grid losses and reduce system peak load. 57 Several efforts are
underway to better understand the full range of potential reliability benefits associated
with DERs. 58
3.2.1 Communication and Technological Capabilities of DERs
New revisions to the IEEE 1547 Standard for Interconnecting Distributed
Resources with Electric Power Systems are expected to mandate communication
capability from all DERs and standardize the related communication interfaces,
protocols, and information models. NERC has commented that the revisions to IEEE
1547, coupled with smart inverter technology, could have substantial benefits for
operations of distribution and transmission grids. NERC stated:
Current work […] on enhancements to the IEEE 1547 interconnection
requirements and how capabilities of DER are used will present
opportunities for improving [bulk power system] reliability. Technology
advances have the potential to alter DER from a passive “do no harm”
resource to an active “support reliability” resource. From a technological

Id. at P 12.

See NYISO, A Review of Distributed Energy Resources, (Sep. 2014),
http://www.nyiso.com/public/webdocs/media_room/publications_presentations/Other_Re
ports/Other_Reports/A_Review_of_Distributed_Energy_Resources_September_2014.pdf
at 18.
58

See, e.g., EPRI, The Integrated Grid, A Cost-Benefit Framework (Feb. 2015),
http://www.epri.com/abstracts/Pages/ProductAbstract.aspx?ProductId=00000000300200
4878.
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perspective, modern DER units will be capable of providing ERS [essential
reliability services] and supporting [bulk power system] reliability. 59
These revisions, once effective, would apply to new but not to existing DERs.
However, the U.S. Department of Energy (DOE) estimates that the average life of small
inverters is seven years, and thus inverter turnover will bring these new capabilities to an
increasing proportion of deployed DERs. If the new revisions to IEEE 1547 mandate
communication capability from all DERs, it would be the responsibility of the utility to
build the required communication infrastructure to make use of this capability. 60 While
transmission system operators may not presently be able to leverage all of these new
features due to a lack of infrastructure, a great deal of work is underway at the Electric
Power Research Institute (EPRI), the National Labs, NERC, and the National Institute of
Standards and Technology’s Smart Grid Interoperability Panel to develop ways to
harness these new technical capabilities of DERs.
3.3 Developments at the Transmission-Distribution Interface: The DSO Model
Distributed System Operators (DSOs) are one of several different operational and
business models that have been proposed and analyzed as a structure for distribution
utilities in the future, especially with higher DER deployment. 61 DSOs have been
proposed as a means to address the parallel needs of an efficient and reliable distribution
system and an intermediate entity between the RTO/ISO and DER owners due to the
limited visibility and control of DERs. 62 Paul De Martini of Newport Consulting Group
and Lorenzo Kristov of CAISO outlined the potential functions of a “distribution system
operator,” including the ability to coordinate the interchange of power to other markets,
physically coordinate DER schedules, aggregate DERs for wholesale market
participation, and control resource output. 63 The DSO could be the medium by which
RTOs/ISOs are provided with net load forecast and dispatchable DER products,
59

NERC DER Task Force Report at 4.

Id.

DER Task Force Report at vi.

See Distribution Systems in a High DER Future: Planning, Market Design,
Operation and Oversight, Paul De Martini and Lorenzo Kristov, Lawrence Berkeley
National Laboratory, October 2015, (De Martini and Kristov).
63

De Martini and Kristov at 21-23; see also, Apostolopoulou, et al., The Interface
of Power: Moving Toward Distribution System Operators (May 2016),
http://ieeexplore.ieee.org/document/7452714/ (Apostolopoulou) at 3.
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schedules and bids, metering, and telemetry. In turn, the RTO/ISO would send the DSO
schedules, dispatch instructions, prices, and settlements for individual DERs or DER
aggregations. 64 To enable these functions, the current distribution system may require
certain upgrades to provide for better modeling, including upgrades to the data
measurement and collection schemes to model existing DERs, as well as upgrades
providing the capability to switch protection settings online and to communicate with
DER resources. 65
While a fully developed DSO as outlined by DeMartini and Kristov has yet to be
implemented, several states are exploring regulatory and policy changes to overhaul the
distribution system. Through its Reforming the Energy Vision (REV) initiative, the New
York Public Service Commission has implemented changes through a series of orders to
the structure of its electric system, including the development of distribution system
platform (DSP) providers, 66 and has required distribution utilities in the state to file
distribution system implementation plans. Other states, such as California, New
Hampshire, Maryland, Massachusetts, and Ohio are also examining reforming the role of
distribution utilities, particularly distribution system planning, during grid modernization
proceedings, but not at the level being conducted in New York. Still other states, such as
Rhode Island, are examining distribution system planning in much greater detail.
In addition, to explore the expanded role and responsibilities of DSOs and
distribution utilities, DOE, in collaboration with the CPUC and the New York Public
Service Commission, is developing a comprehensive set of functional requirements for a
next-generation distribution system platform to enable participation of DERs in the
provision of electricity services. 67 The project intends to engage key stakeholders to
obtain a critical review of its efforts and aspires to provide guidance for the development

Apostolopoulou at 3.

Id. at 3.

The DSP providers will be tasked with modernizing electric distribution systems
to create a flexible platform for new energy products and services, and incorporating
DERs into planning and operations to achieve the optimal means for meeting customer
reliability needs. See The Energy to Lead, New York State Energy Planning Board, at 49
(2015), available at
https://static1.squarespace.com/static/576aad8437c5810820465107/t/5797fc52f5e231d94
2a2d79b/1469578322990/2015-state-energy-plan-pf.pdf.
67

See Overview of DSPx, DOE-OE, http://doe-dspx.org/.
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of future planning, operations, and market tools needed to support distribution system
platform implementation.
4. Technical Studies and Results
The need to study both the transmission and distribution systems becomes more
important as DER penetration increases, because increasing DER penetration changes
how the two systems interact. To assess the impacts of increasing penetration levels of
DERs, Commission staff performed several technical studies using power flow,
production cost, and distribution models to evaluate the potential reliability issues and
benefits associated with DERs.
The power flow models provide information on the DER impacts to bus voltages
and changes in power flows across the bulk power system following a contingency (such
as the loss of bulk power system generation or DER generation). Production cost
modeling offers information on the changes to dispatch and production costs of
generation given various DER penetrations. OpenDSS 68 allows modeling of the
distribution system and facilitates the analysis of the distribution system for a period of
time such as a day. Several sources of data were used to reach consistent levels of DER
penetration across the different study types and models to allow for comparison of results
despite differences in modeling tools.
This section describes these studies, including the assumptions, methodology, and
conclusions.
4.1 Role of Distribution Models in Planning Studies (Distribution Modeling)
Unlike typical power flow studies, this study uses the OpenDSS modeling tool to
analyze the effects of DER installations on the distribution system over a period of a day
and allows for extrapolation of potential impacts to the transmission system. Typical
power flow studies assume a balanced three phase system, while distribution models
typically portray individual phases 69 because many DER installations and distribution
68

OpenDSS is a publicly available software modeling tool provided by EPRI.
EPRI provides the tool and related distribution feeder models and sample data sets at no
cost as part of their ongoing analyses of the impact of the variability of solar generation.
This software has also been used for other industry studies, including multiple studies
published with IEEE.
69

Alternating electrical current circuits typically have three phases to efficiently
move power. To minimize losses on bulk power system facilities these phases are
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loads are single phase. It is important to consider the effects of DERs over a period of 24
hours to capture the influence of DER generation on feeder performance because DERs
and load vary independently.
4.1.1 Study Purpose
The objective of the distribution feeder model study is to compare the potential
impact of different types of feeder modeling on the effectiveness of planning studies, and
therefore grid reliability. Feeders with DERs can be modeled three different ways: (1) as
net demand (so the generation from the DER is cancelled by the load of customers); (2)
as the aggregated generation of the DER independent of the aggregated load at the feeder
connection; and (3) as a detailed model of the feeder. This is shown in Figure 4 below.

Net
Demand

Aggregated
Generation

Detailed Model

Figure 4: Types of DER Modeling 70

In this study, staff evaluated the real and reactive power and voltages at the
transmission and distribution interconnection points using the different types of DER
models to assess whether different model types such as netted load or aggregated load
and generation provide sufficient detail to assess reliability. Review of detailed models
also provides insight into how DERs may behave during a variety of system conditions.

balanced, i.e. each phase carries the same amount of power. But on a lower voltage
distribution circuit loads can be connected to single phases which often results in
unbalanced power flow across the three phases.
70

See Reliability Guideline Distributed Energy Resource Modeling DRAFT,
NERC, Page 3 and 4, available at
http://www.nerc.com/pa/RAPA/rg/ReliabilityGuidelines/Item_14._Reliability_Guideline
_-_DER_Modeling_Parameters_-_2017-05-09_-_FINAL_DRAFT.pdf.
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4.1.2 Assumptions and Data
For the distribution feeder modeling, the distribution feeder models provided by
EPRI were used in combination with OpenDSS. This was not an attempt to model a
full distribution system. The Feeder J1, 72 located in the northeastern United States, was
selected because 1.7 MW of customer-owned PV systems already exist on the feeder.
With a peak load of approximately 6 MW, this 12 kV feeder serves approximately 1,300
residential, commercial, and light industrial customers. While not a heavily loaded
feeder, it requires the use of a load tap changer, voltage regulators, and switched
capacitor banks to provide voltage regulation. Volt-Volt-Ampere Reactive (VAR)
control was added to all PV units to assess the potential impact of the smart inverter
functionality on both distribution and transmission operations.
71

The J1 feeder model used in the analysis consists of all primary and secondary
power delivery elements from the substation transformer to the individual customers.
Control elements such as load tap changers, capacitors (aqua marks in Figure 5) and
voltage regulators (red marks in Figure 5) are included with fully implemented control
algorithms using set-points, delays, and bandwidths. Load is allocated to each individual
customer. The feeder peak load is about 6 MW and the substation peak load is 11 MW.
Solar PV units (yellow marks in Figure 5) are interconnected at the customer service
level (0.416 kV and 0.24 kV). Installed solar PV capacity is 1.7 MW or 28 percent of the
peak feeder load and 15 percent of the substation load.

Since 2010, EPRI has been conducting analyses to assess the variability of solar
generation and its potential impact on utility operations and planning. As a part of the
project, EPRI provides OpenDSS distribution feeder models and sample data sets at no
cost. This software has also been used for other industry studies, including multiple
studies published with IEEE.
72

See Distributed PV Monitoring and Feeder Analysis, EPRI, available at
http://dpv.epri.com/feeder_j.html.
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Figure 5: Feeder J1 – location of voltage regulators, capacitors and PVs

The J1 feeder model includes one year of the substation hourly real and reactive
power measurement data and nine days of the measured solar PV generation data. Solar
PV generation data is given for one-second, one-minute, fifteen-minute and one-hour
time intervals.
4.1.3 Methodology
The study included models both with and without assumed distribution system
voltage controllers, i.e., load tap changers, line regulators and capacitors. Staff also
conducted a power flow analysis for both cases, and assessed the results using loading
and voltage analyses.
Then, for the time series analysis results were generated for every minute during a
24-hour period, and the study considered three different cases of the feeder model: a full
detailed model, an aggregated model, and a netted model. In each case, load was
modeled using SCADA data and PV data was based on one minute EPRI data before
being aggregated as needed to create the three different feeder models.
Figure 6: Hourly PV Diagrams

a) One-minute PV Generation Data

b) Hourly average PV generation data
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First, for the full detailed model both load and PV generation were modeled
separately. For load, staff generated an hourly daily load diagram from the substation
SCADA measurements by selecting a day when the peak demand occurred. Since the
substation meters measure hourly net load, staff modified the measured values by adding
an hourly solar PV generation profile. The hourly PV generation profile was calculated
averaging one-minute PV data provided by EPRI over one hour (Figure 6). PV reactive
power was neglected because a very small amount (less than 50 kVAr) was generated.
Second, staff aggregated the same load as a single load in the substation and
aggregated the solar PV units as a single solar PV installation interconnected in the
substation. In this case, staff derived the normalized hourly load data from multiple load
profiles to represent “typical” hourly load data using statistical methods and incorporated
it by replacing the entire feeder model with one aggregated demand and one aggregated
solar PV installation in the substation.
Finally, both load and solar PV installations were netted as one load located in the
substation. The case used the normalized hourly SCADA data for the peak day to
represent the net demand and solar PV generation as already included.
For all three cases, staff ran the time series analysis for every minute during a 24hour period.
4.1.4 Results
The analysis found that DERs will modify the feeder load such that the variability
of the load (both magnitude and frequency of change) will significantly increase relative
to having no DER resources. However, this is only fully captured in the detailed model
and partially captured in the aggregated models. It further found that based on the time
series analysis results, the peak load change due to DERs may not be proportional to the
installed capacity of DERs because the maximum DER generation may not be coincident
with the feeder peak load. This demonstrates the need to develop planning processes that
capture more detailed models of DERs and allow for modeling of the interface between
the transmission and distribution systems to enable information exchange and more
accurate calculations of the DER impact. The following figures illustrate how the current
practice of netting DERs with load rather than using more detailed models may result in
inaccurate estimates of power flowing on the system.

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Figure 7: Substation Real Power

As shown in Figure 7, when the feeder is modeled as a net load, information about
solar PV generation variability is not captured because the net load is usually an hourly
average of the feeder load. The yellow line, representing the detailed model, shows
significant variation. The grey line, representing aggregated load and solar PV data,
shows less variation. The orange line, representing the net load model, shows none of the
variation caused by the solar PV generation.
Therefore as shown here, when the solar PV aggregation is modeled separately
from the load aggregation, the variability of the solar PV generation can be preserved.
For the given feeder, when net load modeling is used, information on variability of PV
operation is lost, causing a 12-percent difference in modeled load in comparison with the
full feeder model. Because the load and generation data is combined when the feeder is
modeled as an aggregated load and aggregated solar PV generation, the difference is
much smaller (about 3 percent) or “smoother” as shown in Figure 6.
Figures 7 and 8 illustrate the difference between the detailed, aggregated and
netted models and the limitations of the netted models.

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Figure 8: Substation Reactive Power

4.2 DERs and System Performance Following Generator Outages (Power
Flow Study)
4.2.1 Study Purpose
The objective of the power flow study was to assess how DERs, in a system with
high DER penetration, may impact system power flows and bus voltages following a
contingency. As DERs proliferate throughout the system, outages of DERs could have
increasing impacts on the bulk power system, comparable to an outage of conventional
generation. For example, a system disturbance causing DERs without ride through
capabilities to automatically disconnect may exacerbate the initial system disturbance.
4.2.2 Assumptions and Data
The study utilized the FERC Form 715 planning cases for WECC and ERCOT. 73
Staff adjusted the 2017 peak load and low load cases for both regions to represent, as
closely as possible, current DER penetration levels as reported by publicly available data
73

These cases were used because they provide perspective on both
interconnections, and their content and development process are familiar to most in the
electric industry.
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(approximately 12 percent penetration level in WECC and 0.02 percent in ERCOT). 74
However, because DER definitions vary and DERs are not yet explicitly modeled in
WECC’s FERC Form 715 power flow cases, staff made a few key assumptions and
estimates regarding the amount and location of existing DER installations to identify load
points for probable sites for the additional DER capacity to reach consistent penetration
levels.
First, using commercially available data as a basis, 75 staff determined that the
DER penetration in the WECC power flow case should be increased by approximately
four percent (about 2,265 MW) over the amount determined to be included in Form 715
data to reflect a total of about 9,400 MW of DERs as currently reported within
California. 76 Second, to determine where to place the additional DER capacity in the
WECC power flow case, staff assumed that buses which included “aggregated generation
and load models,” 77 also known as “complex loads,” would constitute reasonable DER
locations. These complex loads are modeled throughout the California electric system,
and roughly match the location of DERs found in the PROMOD models. Therefore, staff
added a total of 2,265 MW of DER capacity (as compared to the amount determined to
be in the Form 715 data) to 1,010 load points throughout California in the WECC 2017
peak and low load planning cases to bring estimated modeled DER generation in line
with capacity estimates prepared by the California Energy Commission. 78

Data sources, such as existing commercially available production cost and
power flow models, and data collected by relevant public utility commissions and
reported to the EIA were used to approximate both capacity and location of current DER
facilities.
75

This data was provided as part of the PROMOD databases developed by ABB.

In WECC, the most detailed public DER data is collected by the California
Energy Commission, which defines DERs as projects that are 20 MW or smaller,
including both self-generation and projects for market participation. See Renewable
Energy Tracking Report 2016, California Energy Commission, (last updated on
December 22, 2016), available at
http://www.energy.ca.gov/renewables/tracking_progress/documents/renewable.pdf.
77

See Renewable Energy – Overview, California Energy Commission, available at
http://www.energy.ca.gov/renewables/tracking_progress/documents/renewable.pdf.
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Figure 9: Modeled Change in Generation in WECC

The location of these load points is shown in Figure 9. To maintain the generation
and load balance across the entire WECC system, the team performed a production cost
modeling study with similar levels of DER penetration to adjust generation.
In ERCOT, DERs are defined as an electrical generating facility that is located at a
point of common coupling, 10 MW or less, connected to a bus voltage level less than or
equal to 60 kV. 79 ERCOT has locational information for DERs with installed capacity
greater than 1 MW that export energy into the distribution system because they are
required to register with ERCOT, but it does not have detailed information for DER
installations that do not meet that threshold. Based on this definition, and to match other
data sources, staff determined that a total of 179 MW of DER capacity had to be added in
the ERCOT 2017 peak and low load planning cases, as compared to the Form 715 data,
to bring estimated modeled DER generation in line with the capacity estimates prepared
by ERCOT. 80 To maintain the load and generation balance, an equivalent amount of
generation from several large generating units was scaled down.
In order to determine the location of the DER installations, staff leveraged data
from commercially available databases to site the DERs in the ERCOT power flow
model based on their geographical proximity to the nearest distribution generator bus.
79

See Distributed Generation, ERCOT, (2017), available at
http://www.ercot.com/services/rq/re/dgresource.
80

See Distributed Generation, ERCOT, available at
http://www.ercot.com/services/rq/re/dgresource.
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The data for the unregistered component of the DER installations in ERCOT is available
on an aggregate level by primary fuel type and load zone. 81 Staff divided the total
capacity value of unregistered DERs proportionally among the buses identified by staff as
probable DER locations. Table 1 shows the unregistered DER capacity as reported by
ERCOT.
Table 1: Unregistered DER Totals 82

Aggregate by Primary Fuel Type (MW) for Reporting Quarter 2016 Q4
Load Zone
Total
Solar
Wind
Other
Other NonRenewable Renewable
13.91
0.00
0.00
0.00
13.91
AEN
7.14
0.00
0.23
0.00
7.37
CPS
8.03
0.39
0.11
4.33
12.86
Houston
0.64
0.00
0.00
0.00
0.64
LCRA
68.46
1.66
0.00
0.63
70.74
North
0.00
0.00
0.00
0.00
0.00
Rayburn
11.27
0.67
0.00
0.00
11.94
South
5.93
0.82
0.00
0.33
7.08
West
115.37
3.54
0.34
5.28
124.53
Total
In additional sensitivity studies, staff also scaled DER generation by factors of two
and three to test the effects of higher penetrations. To accommodate this additional
generation, the existing generation fleet was re-dispatched based on dispatch results from
a production cost modeling study with similar levels of DER penetration.
4.2.3 Methodology
The power flow study considers two fundamental system loading conditions: (1)
high load, which typically occurs in the hot summer months; and (2) low load, which
81

Unregistered DER Capacity Quarterly Report, ERCOT (last updated Quarter 1
2017) available at
http://mis.ercot.com/misapp/GetReports.do?reportTypeId=13544&reportTitle=Unregister
ed%20DG%20Installed%20Capacity%20Quarterly%20Report&showHTMLView=&mi
micKey.
82

Docket No. AD18-10-000

typically happens during the spring or fall. The studies monitored for transmission
facility loadings above 100 percent of Rating Set A (used for normal operations) and for
bus voltages below 90 percent, below 95 percent, and above 105 percent of the standard
operating voltage.
Finally, staff performed a selective contingency analysis to determine any
violations to the thermal and voltage criteria. The contingencies examined included the
loss of DER capacity, the loss of a large generating facility, and a combination of both.
Staff also evaluated these contingencies at different DER penetration levels. The
following contingencies were analyzed:
• Loss of bulk power system generation equal to one or two nuclear units
• Loss of levels of DER generation equal to one or two nuclear units
• Loss of both the one or two nuclear units on the bulk system and DER
generation
4.2.4 Results
As shown in Figure 10 below, analysis of the WECC system found that in most
cases, higher DER penetrations resulted in fewer buses with low voltages and thermal
overloads but a greater number of buses with high voltages when compared to the base
case. The increased voltages may be helpful on buses that tend to have low voltage
issues, but potentially challenging to those with voltages that are already high. Bus
voltages can in some cases increase with DER generation because it reduces loads and
relieves loading on some transmission facilities.
Figure 10: Change in California Voltage Levels in WECC Cases

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Voltages changed throughout WECC, with voltages generally increasing in load
pockets closest to the additional DER capacity and varying in direction and magnitude of
change elsewhere. Figure 11 shows that the most significant changes are close to the new
DER capacity, but due to changes in power flows, there are smaller voltage changes
throughout the system. Voltage changes are also influenced by the ability of some
transformers to adjust their voltage output based on system conditions. 83
Figure 11: Significant Voltage Changes Concentrated near DER Resources 84

The small changes in voltage can ripple through the entire WECC interconnection
in response to a change in any part of the system (for example, the loss or addition of
generation) that might affect the voltage at a transformer. The resulting changes in
voltage highlight the need for additional study to define and articulate: ride-through
requirements for deviations in voltage; voltage support required from DER at the point of
interconnection or appropriate point on the system; voltage support strategies throughout
the interconnections to define steady state and dynamic reactive resources that may be
needed; and the need for detailed/accurate/validated modeling of the behavior of DER.

Transformers with tap adjustors can change the number of core windings that
determine the primary to secondary voltage relationship, in order to maintain a more
consistent voltage output. Typically, the tap position on the primary side will adjust
based on the voltage delivered there so that the secondary voltage remains constant.
84

The analysis also observed effects in Canada, which are not reported here.
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Docket No. AD18-10-000
Figure 12: Changes on the 500kV System 85

As shown in Figure 12, the large number of small changes in voltage that occurred
in the modeled scenarios (between 0 and five percent) throughout the 500 kV system
likely resulted from changes in flow patterns due to variations in load levels and
generation re-dispatch to accommodate DERs. Due to the increase in DERs, staff
decreased generation imports from the Northwest as well as load in California in the
WECC power flow model to mimic the changes in dispatch identified in production cost
modeling studies. As a result, in the model voltages on the 500 kV buses increased and
smaller voltage shifts on lower voltage lines and buses also occurred. Power flow
changes are also influenced by the ability of some transformers to adjust 86 their power
output based on system conditions. The results shown in Figure 6 indicate that a closer
look at the dispatch of reactive resources is needed to assess whether these changes in
reactive support will need to be addressed in the future, e.g., with operating procedures or
additional reactive equipment. The results mimic those identified in the production cost
study below in Section 4.3, with similar levels of DER penetration. These effects are
further shown in Figure 13 below.

The analysis also observed effects in Canada, which are not reported here.

Transformers with phase shifters are able to change the phase displacement
between the input and the output voltage in order to control the active power passing
through.
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Figure 13: Buses with Large and Small Voltage Changes (Voltage Level Less than 100 kV) 87

By comparison, analysis of the ERCOT system, with its lower levels of DER
penetration, showed no significant variation in reliability impacts for voltages and
thermal overloads under different contingencies. There was a slight increase in the
number of thermal overloads, likely as a result of the clustering of DER capacity in a
smaller number of locations on the system. Appropriate interconnection studies,
curtailment procedures, and DER models will be needed to resolve these overloads in
order to integrate large amounts of DER reliably into the ERCOT system.
After making changes to the settings as part of the power flow analysis, such as
locking tap changers and switched shunt adjustments, 88 the percent change in bus
voltages across the DER buses was no greater than 6 percent as increasing DER
penetration levels were studied. This is due to the overall low penetration levels of DER
capacity in ERCOT. However, while the average bus voltage increased at higher DER
penetration levels similarly to the percentage changes found in WECC, increasing the
DER penetration levels beyond a factor of three to a total penetration level of 0.05
percent at the identified set of DER buses prevented the case from converging, making
further analysis impossible without broadening the electrical location of DERs
throughout the model. Further studies taking into account alternative variables, such as
changes in siting, may need to be conducted on the system to determine the impact of
increasing DER penetration levels beyond a factor of three.

The analysis also observed effects in Canada, which are not reported here.

These are types of settings used in the power flow model to control how
different devices respond to changes in voltage.
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4.3 Impact of DERs on Dispatch (Production Cost Modeling)
4.3.1 Study Purpose
Staff performed production cost studies for WECC and ERCOT at both current
and future DER penetration levels to evaluate the impact of DERs on generation dispatch
and transmission constraints. Production cost modeling can simulate the operation of an
electric system, within or outside of a market, as a least-cost optimization of unit
commitment and dispatch to serve load while accounting for generator, system, and
transmission constraints. This allows for the assessment of some high level reliability
implications.
This analysis allowed staff to monitor the impact of different levels of DER
penetration on generator dispatch, and congestion, to help identify common conditions
that may create system stress.
4.3.2 Assumptions and Data
The study modeled both WECC and ERCOT using the most recent nodal
PROMOD databases. The models were prepared for a 2017 study year using escalations
and recent forecasts included in the model for variables such as prices and load and set up
to track emergency energy deployment and key generator characteristics, such as reserve
participation and LMPs. 89
Assumed DER capacity was increased by a total of 4,855 MW in the WECC
model and 55 MW in the ERCOT model, as compared to the original models developed
by ABB for the PROMOD production cost mode. These changes result in a penetration
level of 12.5 percent for WECC in the updated model, rather than the three percent level
in the original model.

Staff notes that LMPs in this case are a proxy for the values associated with
relieving transmission constraints, even though LMPs are not used throughout the WECC
region.
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Figure 14: Net Metering as a Percentage of State Peak Load 90

This penetration level matches the 12.1 percent penetration level for California
shown in Figure 14, which was calculated based on EIA data. Staff also evaluated a
second future scenario with a 25-percent penetration level. More capacity could be
incorporated into the system, but additional supporting infrastructure or other changes,
such as new DER locations, may be needed.
For the ERCOT system, where there is a much lower amount of existing DER
capacity, the original model included a penetration level of 0.01 percent. The updated
model increased this penetration level to 0.02 percent, and two future-case scenarios were
developed to evaluate penetration levels of 0.13 percent and one percent.
In both interconnections, the assumed DER capacity was sited and proportionally
assigned hourly profiles to match existing installations in the models. Staff simulated
randomized forced outages of both traditional and DER generators to assess the impact of
different DER penetrations and dispatch capabilities on total system costs, LMPs,
congestion, and loss of load expectation.
4.3.3 Methodology
Staff performed a one-year simulation for each scenario. Results were then
reviewed on a monthly, and where possible, hourly basis. Results assessed included:
generation dispatch changes, increases and decreases in production costs at the unit and
regional level, variation in LMPs throughout the year, changes in congestion costs at flow
gates over the year, monitoring of excess generation or any instances of unserved load to
90

Data Source: EIA - Form EIA-826 detailed data files - Net Metering (December
2016) and Velocity Suite – Estimated State Load (Hourly).
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test for deliverability issues, and finally monitoring of reserve participation. Staff also
reviewed these results at the nodal and area levels.
4.3.4 Results
In ERCOT, the scenario with 0.01 percent DER penetration level resulted in
minimal changes in the dispatch of generation over the modeled year. In WECC,
however, changes in LMPs, congestion costs, and therefore generator dispatch occurred
frequently throughout the simulated year. The magnitude of these changes was limited
due to the level of DER penetration and did not result in any loss of load hours or
deployment of emergency energy.
As shown in Figure 15 below, increased DER capacity in WECC offset existing
generation in the dispatch throughout the year, with the most significant changes
occurring in late spring and fall. Increased DER capacity primarily replaced combined
cycle gas generation, which is typically on the margin in WECC. However, it also
caused minor increases in the dispatch of some steam coal and natural gas units, and
affected the timing of the hydro dispatch. It is important to note that the PROMOD
production cost model does not model forecast errors for either load or renewable
generation. Therefore, the results do not provide insight into the impact of daily forecast
uncertainty caused by variation in output from DERs such as variations in daily weather.
Figure 15: Monthly Generation Results for WECC Comparing Base Case and Additional DER
Capacity Models

While the maximum and minimum LMPs changed slightly in the spring, the
average LMP did not show a significant change overall, consistent with the other results
and suggesting that the changes, while numerous, remain limited in magnitude at this
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time. These changes were consistent with the relative increases and decreases in the
dispatch of different generators.
In addition to the frequent dispatch variations, the effects were widespread
throughout the WECC system even though the DER installations were largely located
within California. The effects also changed depending on system conditions within the
model for a given hour. This was particularly noticeable in generation dispatch, line
flows, and congestion. Units were offset by DERs throughout WECC, and these changes
caused both increases and decreases in congestion during the year.
Overall, transmission lines outside of California saw a decrease in congestion
while those within California, especially near high concentrations of DERs, saw both
increases and decreases. The increases in congestion could be caused by increased
imports to areas with diminished use of some combined cycle units. However, given that
the changes in congestion and dispatch were spread throughout the system and occurred
at a wide variety of load levels and hours, additional sensitivities may need to be assessed
in other studies to examine specific system conditions. 91 Because the model assumes the
existing transmission system, effective planning for DER integration using accurate
models could address any increases in congestion, though further study would be needed
to confirm this conjecture.
4.4 Ancillary Services Provided by Energy Storage (Distribution Modeling)
4.4.1 Study Purpose
The energy storage study evaluates the impact of ancillary services provided by
energy storage devices, such as regulation services, on markets, and transmission and
distribution systems. Energy storage may be able to provide grid level services such as
regulation, reserves and voltage support. However, the provision of these services from
energy storage devices can result in sudden variations in output, affecting voltage and
power quality on the distribution system, and potentially on the transmission system as
well.
This study assesses whether a storage resource needs to be modeled separately
from other DER installations due to the possibility of different impacts from the
operation of a storage resource. The study also assesses what specific operational
characteristics of the storage resource may be necessary in specific operational situations.
If the storage resource has the potential to provide grid level services at a location
valuable to the bulk energy system, but the distribution infrastructure is unable to
91

For example, power flow studies typically focus on particular seasonal
conditions such as peak summer conditions or a winter dispatch.
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accommodate the resource reliably, this may have market implications at the bulk energy
system level if the operator is forced to procure that service elsewhere. Accurate studies
during the interconnection process could help to identify and mitigate such concerns.
4.4.2 Assumptions and Data
This study continues to use the Feeder J1 model, as previously described. Staff
analyzed two applications of energy storage: (1) using energy storage for frequency
regulation services and (2) using energy storage for load leveling.
In each case, staff added one energy storage device to the model. Adding a single
energy storage system instead of several distributed units does not significantly change
the results from the transmission operator standpoint because transmission system
operators only see the impact of aggregated energy storage, such as a change in
substation power flows and voltages. The difference in the results is mostly due to
different patterns of distribution system losses.
In order to compare the impact of similar size aggregated DERs with different
applications, staff selected the energy storage size (1.7 MW and energy of 6.8 MWh)
based on the installed capacity of the existing solar PVs. The location of the largest solar
PV units was selected as the energy storage system location. To model the operation
(charging and discharging intervals) of the energy storage system for the regulation
service, staff used one day of PJM RegD 92 (a fast regulation signal that is sent every two
seconds to the devices participating in regulation service).
For the load leveling application, staff developed a 24-hour charging/discharging
energy storage profile such that the energy storage system charges during the night and
discharges during the day. 93 Since the efficiency of an energy storage system is not 100
percent, the amount of energy charged is larger than energy discharged.
4.4.3 Methodology
Staff added one energy storage system to the detailed feeder model. For the
frequency regulation application, staff performed a time series analysis over a 24-hour
92

See Ancillary Services: Market-Based Regulation - RTO Regulation Signal
Data, PJM, available at http://www.pjm.com/markets-and-operations/ancillaryservices.aspx.
93

See Energy Storage Projects in AEP, Ali Nourai, page 7, (October 2009),
available at https://energy.gov/sites/prod/files/ESS%202009%20Peer%20Review%20%20Energy%20Storage%20Projects%20in%20AEP%20%20Ali%20Nourai%2C%20AEP.pdf.
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period with a two-second time step in order to simulate the frequency of the regulation
signal. For the load leveling application, staff ran the time series analysis over a 24-hour
period with a 15-minute time step. To focus only on the impact of energy storage, the
model disconnected existing solar PV units from the system. Staff assessed changes in
the real and reactive power in the substation and changes in voltage on the high voltage
side of the substation transformer.
4.4.4 Results
When an energy storage system is used to provide frequency regulation service,
peak demand on the affected feeder may increase if the charging of the energy storage
system is coincident with the occurrence of the feeder peak load. If this happens, the
increase in the peak load on that affected feeder may be larger than the installed storage
capacity (in MW) because of the increase in the feeder power losses. Since the regulation
signal is volatile with very frequent changes, the probability that this may happen is high.
Energy storage is a very specific technology because it can consume and generate power,
meaning that it may increase or decrease the feeder loading.
Figure 16: Substation Real Power

Figure 16 illustrates substation real power as seen by the transmission operator
during a 24-hour period. The feeder peak demand increased from 11,558 kW to 13,241
kW. The substation load change ranged from a 30 percent decrease to a 27 percent
increase compared to the substation load without the storage. Hence, additional load on
the feeder due to the operation of the storage system may reduce the overall available
supply from resources on the feeder. If a DER owner is planning to participate in the
ancillary services market, the distribution system operator may want to be informed
because the distribution feeder elements are sized based on the estimated peak demand,
and any additional loading can cause an overloading of the lines. In addition to changes
in the substation/feeder load, using an energy storage system located on a distribution
system for regulation service will cause sudden changes in the voltage and potential
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issues with power quality. Some of these effects may also impact the transmission
system.
Figure 17: Substation Voltages - Phase A

Figure 17 illustrates the substation voltage (light blue and yellow lines), the feeder
voltage (dark blue and orange lines), and the frequent changes caused by the energy
storage system. In the given example, the change on the high voltage side of the
substation transformer ranges from a 0.4 percent decrease to a 0.3 percent increase
compared to the voltage without energy storage, which ranges from a 1.6 percent
decrease to a 1.5 percent decrease on the low voltage side. Depending on the energy
storage system power capacity (in MW) participating in the market, these changes can be
higher or lower.
In the case of load leveling, the changes introduced are much smoother. Figure 18
illustrates substation real power over 24 hours. Since the energy storage system is
charging during the night, off-peak load increases, and since the energy storage system is
discharging during the peak time, the peak load is reduced. The energy storage system,
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charges/discharges with constant power. This profile can be changed based on the
feeder/substation load profile. Voltage changes (Figure 19) are also much smoother
because there is no sudden change in the load.
Figure 18: Substation Real Power – Load Leveling

Figure 19: Substation Voltage – Phase A – Load Leveling

As demonstrated above, when DER resources provide services such as frequency
regulation, and if the distribution infrastructure is unable to accommodate this type of
operation, there could be potential market and reliability impacts. This potential impact
to reliable operation of the distribution system infrastructure could affect distribution
resources participating in wholesale markets by providing energy, capacity or ancillary
services if these services cannot be provided with a reasonable assurance of expected
performance. The distribution system operator may need to be allowed to assess the
impact on its system of the participation of energy storage systems or any other DERs in
wholesale markets, and may need to provide feedback on upgrades to the infrastructure
necessary to support this wholesale participation. The distribution provider may also be
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able to provide recommendations on the resource size (in MW) during the installation
process so that the reliability of the distribution system remains intact.
4.5 Assessing the Benefit of Smart Inverters to Reliability (Distribution
Modeling)
This study assesses whether smart inverters on the distribution system provide
greater benefits than regular inverters used in some DER installations. Smart inverters
have controls that provide additional capabilities, such as allowing DERs to provide
voltage and frequency control. This study examines the potential impacts of smart
inverters providing volt-VAR control; it does not include frequency control.
4.5.1 Study Purpose
The smart inverter study assesses whether smart inverters on the distribution
system provide significant benefits compared to regular rooftop solar inverters. Smart
inverters have the potential not only to provide real power, but also to assist in providing
reactive power and voltage regulation, which increases the number of PVs that can be
installed reliably on a distribution feeder. Therefore, smart inverters may be able to
address some of the operational issues associated with increased DER penetration. The
study assesses their impact on reliability using line loading, voltages, and voltage control
equipment. It focuses primarily on the distribution system, and also explores the
potential for a transfer of benefits to the transmission system.
4.5.2 Assumptions and Data
Staff used Feeder J1 for the simulation and analysis. All existing solar PVs were
equipped with smart inverters that could provide volt-VAR control. The volt-VAR
control function allows each individual solar PV system to provide a unique VAR
response according to the voltage at the point of connection (0.416 kV and 0.24 kV). All
the solar PVs were set to use the same volt-VAR curve such that the inverter provided the
maximum possible reactive power if the voltages were smaller or larger than 0.95 and
1.05, respectively, and slightly less if the voltage was within that range. Staff conducted
a time series analysis on a 30-minute interval.
4.5.3 Methodology
To examine the impact of smart inverters, staff modeled two cases with rooftop
solar installations: (1) one with regular inverters and (2) one with smart inverters. The
impact on reliability was assessed by monitoring variability in line loading, voltages, and
voltage control equipment operation. While this study focused primarily on the
distribution system, it also reviewed the data to determine whether benefits can be
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transferred to the transmission system by analyzing voltages and real and reactive power
at the transmission-distribution interconnection point.
4.5.4 Results
EPRI previously showed that using smart inverters can increase the amount of
solar PVs that can be reliably installed on the feeder (i.e., increase the hosting capacity of
the feeder) 94 and can potentially lead to higher penetration levels of PV DERs in the
future. Adding smart inverters with volt-VAR control capability to the PV installations
improved the reactive power and voltage at the local and substation level in this analysis.
Based on the volt-VAR curve, the maximum voltage at the PV interconnection point was
reduced from 1.032 down to about 1.025 pu (as shown in Figure 20) by absorption of
VARs from the grid (as shown in Figure 21) following the volt-VAR curve and control
algorithm. Voltage levels at the substation also dropped but by a much smaller amount
(about 0.2 percent).

See Distributed PV Monitoring and Feeder Analysis – Hosting Capacity
Method, EPRI, available at http://dpv.epri.com/hosting_capacity_method.html.
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Figure 20: Voltage at PV location and at Substation – Phase A

Figure 21: PV Generation of Reactive Power with and without Smart Inverter

This case illustrates a situation in which the local and substation voltage controls
have opposite objectives. If the local voltage were 1.03 pu, the objective would be to
bring this voltage closer to 1.0 pu or below so that additional PVs could be installed on
the feeder. In contrast, if the substation voltage level were about 0.965 pu, the objective

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would be to increase it. However, by decreasing the local voltage, the substation voltage
decreases as well.
If solar PV with smart inverters were used to support voltage at the substation
level, this control would need to be coordinated between the market operator, the
transmission system operator and the distribution system operator. Similarly, as in the
energy storage system analysis, smart inverters may be used to support the operation of
the transmission power system. However, use of smart inverters to support the operation
of the transmission system without consideration of distribution system requirements
would be unwise because the operation of PVs or any other DER technology with a smart
inverter could impact distribution system reliability or power quality.
5. Conclusions
As demonstrated by this technical assessment, given the growing adoption of
DERs in the United States, there are a number of key bulk power system reliability topics
to explore, including:
• The impact of the current common industry modeling practice of netting DERs
with load, which may mask the effects of DER operation;
• DER capabilities for voltage and frequency ride through during contingencies;
• The potential for improved voltages due to the unloading of the bulk power
system associated with the location of DERs at or near customer loads;
• Potential effects upon system-wide transmission line flows and generation
dispatch due to changing load patterns; \
• The sensitivity of voltage or power needs to different types of DER
applications (i.e., providing energy, capacity, or ancillary services); and
• The need to develop planning processes that capture more detailed models of
DERs and allow for modeling of the interface between the transmission and
distribution systems to enable information exchange and more accurate
calculations of the DER impact on the bulk power system.
• The advantages and disadvantages of allowing DERs to participate directly in
the organized wholesale electric markets.
Further discussion also is needed on potential means to improve modeling
practices with respect to DERs, including options for improving available data and the
incorporation of detailed DER models into existing industry models. In addition, further
dialogue is needed to identify other areas for additional analysis, such as additional study
types and sensitivities which could provide further insight into the potential local and
system-wide impacts of future growth in DER capacity. Efforts such as these could help
track and assess the impact of changing conditions on the bulk power system to identify
emerging trends and address potential future reliability challenges.
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File Type	application/pdf
File Title	istributed Energy Resources - Technical Considerations for the Bulk Power System Event
Subject	istributed Energy Resources - Technical Considerations for the Bulk Power System Event
Author	FERC
File Modified	2018-02-15
File Created	2018-02-14