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Visualization of the Eastern Renewable Generation Integration Study

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The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the widespread adoption of wind and solar photovoltaic (PV) resources in the U.S. Eastern Interconnection and Québec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI could balance the variability and uncertainty of high penetrations of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.
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Visualization of the Eastern Renewable Generation Integration Study
Kenny Gruchalla, Joshua Novacheckand Aaron Bloom
Computational Science Center
Strategic Energy Analysis Center
National Renewable Energy Laboratory
Golden, CO
kenny.gruchalla@nrel.gov, joshua.novacheck@nrel.gov, aaron.bloom@nrel.gov
Abstract—The Eastern Renewable Generation Integration
Study (ERGIS), explores the operational impacts of the
widespread adoption of wind and solar photovoltaic (PV)
resources in the U.S. Eastern Interconnection and Qu´
ebec
Interconnection (collectively, EI). In order to understand some
of the economic and reliability challenges of managing hun-
dreds of gigawatts of wind and PV generation, we developed
state of the art tools, data, and models for simulating power
system operations using hourly unit commitment and 5-minute
economic dispatch over an entire year. Using NRELs high-
performance computing capabilities and new methodologies
to model operations, we found that the EI could balance the
variability and uncertainty of high penetrations of wind and
PV at a 5-minute level under a variety of conditions. A large-
scale display and a combination of multiple coordinated views
and small multiples were used to visually analyze the four large
highly multivariate scenarios with high spatial and temporal
resolutions.
1. Introduction
The U.S. Eastern Interconnection and Qu´
ebec Intercon-
nection (collectively, EI) is the largest power system in
North America (see Figure 1) and one of the most complex
power systems in the world. Wind and solar photovoltaic
(PV) generation are the fastest growing electricity resources
in the United States. The Eastern Renewable Generation In-
tegration Study (ERGIS), a scenario-based study of multiple
potential wind and PV futures – up to 30% on an annual
energy basis with instantaneous penetrations over 50% –
was designed to understand the operational impacts of wind
and PV on the transmission system and thermal and hydro
generators [1]. Renewable generation sources, like wind and
PV, add significant variability and uncertainty to a system
that requires that demand and generation be balanced. Using
high-performance computing capabilities [2], ERGIS ad-
vanced the state-of-the-art by conducting the most detailed
and complex simulations of power system operations ever
run. The project explores variable and uncertain conditions
caused by wind and solar forecast errors, seasonal and diur-
nal patterns, and weather and system operating constraints.
Building off and extending prior research [3], [4], [5], this
Figure 1. Base transmission network of the Eastern Interconnection mod-
eled by ERGIS.
study models the operational impacts of high renewable
penetrations at a 5-minute resolution. The study finds it
is technically feasible for the EI to operate when variable
generation regularly exceeds 200 GW, and meets 30% of
annual load, translating to more than a 30% reduction in
power system operating costs and CO2 emissions.
Four power system future scenarios were simulated. A
low variable generation (lowVG) represented a future with
no new wind or PV generation installations and minimal
transmission expansion. A moderate-penetration scenario
(RTx10) with intra-regional transmission expansion and ap-
proximately 10% variable generation penetration designed
to align to meet state renewable portfolio standards. A high-
penetration scenario (RTx30) with identical transmission
expansion to RTx10 with approximately 30% combined
wind and PV generation within each region. And a high-
penetration scenario (ITx30) with interregional transmission
expansion that included several high-voltage direct current
lines and 30% combined wind and PV, utilizing the best
wind and solar resources in the EI.
By using high performance computing (HPC) and ad-
vanced visualization techniques, we show that wind and PV
Figure 2. Single frame designed to be viewed on large-scale display wall, showing three coordinated views of four energy future scenarios.
are viable options for significantly reducing carbon dioxide
emissions from the electricity sector. We also show that
large-scale coordination across the US and Canada may
be necessary to enable the most economical transition to
a cleaner electricity future. Without HPC and the advanced
visualization capabilities developed for this project, it would
not have been possible to study the system in this level
of detail. Furthermore, the complexity of the power system
model and volume of data made the static statistical plot-
ting techniques, traditionally used to visualize transmission
studies, inadequate.
2. Modeling & Simulation
The ERGIS study joins a growing list of variable gen-
eration integration studies that have examined part or all of
the EI. One of the goals of ERGIS was to add enhanced
simulation methods to increase confidence in the ability to
integrate increased amounts of variable generation onto the
electrical transmission system. We compared our assump-
tions to five previous studies of the EI [3], [5], [6], [7], [8]. In
aggregate, the improvements in the ERGIS study represent
an increase in temporal, geographic, and technical fidelity.
First, ERGIS expands the range of resources analyzed by
simulating large-scale adoption of PV in addition to wind
in the EI. This increases the number of generators on the
system considerably from previous studies, with correspond-
ing increases the complexity of the unit commitment and
economic dispatch models. Next, the study narrows the
temporal resolution to five minutes to understand the sub-
hourly impact of these resources on system operations. This
time resolution reflects the dispatch interval of existing
regional transmission organizations and independent system
operators. ERGIS also increases the spatial resolution of
the model to include all synchronous components of the
EI, increasing the number of transmission facilities and
generators in the model significantly.
The model was executed using PLEXOS, including
over 5,600 generating units, 60,000 transmission nodes,
and 70,000 transmission lines and transformers. As formu-
lated by PLEXOS, each day-ahead optimization problem
has about 73,000 integer variables, 1.2 million continuous
variables, and 23 million non-zeros in the constraint matrix.
Because of the size of the problem, runtimes would be
intractable if the model were run consecutively from January
1 through December 31 of the study year.
To address the extreme computational challenge pre-
sented by large unit commitment and economic dispatch
models, previous work at NREL developed methods to
decompose these types of annual simulations into shorter
time partitions while preserving the accuracy of simulation
results [2]. The effort resulted in a method for time-domain
decomposition and parallel simulation of production cost
models. ERGIS used the time domain partitioning method
to parallelize unit commitment and economic dispatch sim-
ulations using NRELs HPC system, Peregrine [9] into 73 in-
dependent simulation horizons. The parallelization provided
an approximately 30x speedup, enabling annual simulations
that were projected to take in excess of 545 days to be
completed in roughly 19 days.
3. Visualization
We used a large-scale display with a combination of
multiple coordinated views [10] and small multiples [11] to
visually analyze the four large, highly multivariate scenarios.
We employed three types of visualization as multiple coor-
dinated views: a geographic diagram, a chord diagram, and
dispatch charts. These three views were duplicated for each
of the scenarios as a set of small multiples (see Figure 2).
Figure 3. Geographic view provides qualitative view of the generation
distribution and net regional interchanges.
A large-scale power-wall display provided the visual real
estate for all twelve views to be visualized simultaneously,
allowing analysts to step through time to contemplate the
dynamics of the system and the differences between scenar-
ios.
The geographic diagram provides a qualitative view of
the study domain representing individual generator output
and interregional transmission flows (see Figure 3). The
output of every generator is plotted for every five min-
utes as semi-transparent bubbles centered at the generators
actual location with areas proportional to their associated
output, and colored by generation type (e.g., coal, natural
gas combined cycle, and photovoltaic). This approach was
adopted from a visualization created for the Renewable
Electricity Futures Study [12]. The generator bubble glyphs
were sorted by generation size, drawing smaller generation
over larger generation to better illustrate the generation dis-
tribution in dense areas. A single frame provides an overall
understanding of the geographic distribution of generation,
and when animated, the dynamics of that distribution. The
dynamics include both the changing output and cycling
of the generators. Arrows overlay the generation bubbles,
representing regional transmission flows and provide a sense
of the direction and magnitude of power flow.
The chord diagrams [13] provide a more quantitative
view of the net interchange between each of the regions (see
Figure 4). Chord diagrams were designed and are primarily
used for comparative genomics [14], but their ability to
show directed relationships among groups of objects makes
them well suited to show interchange between regions. We
represent each region as an arc on the perimeter of a circle;
the length of the arc is proportional to that regions total
Figure 4. Chord view provides a quantitative visualization of the net
interchange between regions, e.g., this image shows 5GW moving from
SERC to PJM and 2.5GW moving from PJM to NYISO.
interchange in GW. Directional ribbons are drawn between
two regions to represent the direction and magnitude of the
interchange. To the extent practicable, regions that share a
common border were positioned on opposite sides of the
circle to separate the flow ribbons. The colors of the chords
match their source. The width of each chord end-point
reflects the interchange magnitude; wider chords represent
greater interchange. Finally, the aggregate generator output
for each region and scenario is displayed as bar charts or
grouped stacked bar charts. We developed the visualizations
in the R programming language and used the visualizations
in multiple ways. We created stills of individual time steps
for each scenario, compiling these into desktop movies for
analysis and communication. We created high-resolution
stills for each time step representing all four scenarios and
sized for NREL’s 14 MPixel display wall (see Figure 5).
Using this display, analysts could step forward and back-
ward in time to compare the generation and flows. Finally,
we visualized the individual scenarios as interactive web
applications using the R shiny package [15].
4. Discussion
Efficient operation of the power system requires oper-
ators to commit and dispatch the system under a variety
of challenging conditions. We analyzed the results of the
simulations to identify potentially challenging conditions for
the EI in the RTx30 and ITx30 scenarios. By visualizing
the results as shown in Figure 5, we were able to make
cross scenario comparisons that were not previously possible
in the literature. For example, the normalization of the
chord view to the largest transmission build in the study
provided an understanding of the substantial differences in
Figure 5. ERGIS Visualization as viewed and analyzed on a large-scale
14 MPixel display wall, showing three coordinated views of four energy
future scenarios.
interchange capability across the scenarios. Additionally,
statistical analysis of forecast errors and net load ramps
identified a period of particularly challenging conditions.
Using this visualization, we were able to make comparisons
across the scenarios with respect to how the variability and
uncertainty are managed across the system, under these
challenging conditions. Finally, the geographic view enabled
us to understand the breadth of coordination utilized to
balance electricity supply and demand at least cost to the
system. Previous attempts to visualize net interchange be-
tween the regions focused on one region, and its immediate
neighbors. Through the use of this set of tools, we were able
to understand how generation availability could impact not
only regions that shared a common border but could impact
operations across many regions, from Florida to Qu´
ebec.
These additional insights matter for system operators
and regulators. ERGIS showed the total EI operating costs
decreased by $30-31 billion and carbon dioxide emissions
decreased by 31-33% in the high wind and PV penetration
scenarios (RTx30 and ITx30). The visualization described
here told the story of how these reductions in costs and
emissions were achieved. The visualization increased the
credibility of the results and identified pathways forwards
for operators and regulators to achieve high penetrations of
wind and PV. Using HPC, we were able to analyze the EI
at an unprecedented fidelity. This resulted in spatially and
temporally complex results which could not be adequately
analyzed using traditional visualization techniques. By ani-
mating these results and analyzing them on our 14 MPixel
display wall we were not only able to see results buried
within the data, but we were also able to communicate these
results to key audiences [16].
Acknowledgments
The research was performed using computational re-
sources sponsored by the Department of Energy’s (DOE)
Office of Energy Efficiency and Renewable Energy (EERE)
and located at the National Renewable Energy Laboratory.
Funding for the modeling and visualization of ERGIS was
provided by the DOE EERE Wind Energy Technologies
Program, EERE Solar Energy Technologies Office and DOE
Office of Electricity Delivery and Energy Reliability, Na-
tional Electricity Delivery Division.
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... A chord diagram represents directed interrelationships between groups of objects, where these objects are arranged along a circle and connected with Beźier curves [KSB * 09]. Chord diagrams can be used to represent data flow on a directed graph [GNB16] by grouping vertices into regions and representing the net flow between regions in the chord diagram. The chord diagram provides a quantitative view of net flow, but abstracts that flow away from the toplogy of the network. ...
... The visualization of large transmission networks more typically aggregate the line flows to the net flow or interchange between regions of the network. These aggregated flows have been represented as ribbons in a chord diagram [GNB16] (see Figure 6). Net interchange visualizations provide critical information on power transfer between large regions in aggregate but fail to show how that interchange occurs. ...
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GE Energy Consulting, "PJM Renewable Integration Study Executive Summary Report, Revision 05," Tech. Rep., 2014. [Online]. Available: http://www.pjm.com/ ⇠ /media/committees-groups/ subcommittees/irs/postings/pris-executive-summary.ashx
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  • J Bakke
  • Z Zhou
  • S Mudgal
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