SGRC 1.0 Cost/Benefit Models for 20+ Electric Coops and Municipal Utilities
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SGRC established 2008 at Texas A&M University
to provide new smart grid technology and program cost/benefit
analysis for individual utilities.
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Developed by Dr. Jerry Jackson, signature professor at Texas A&M and
transitioned to Jackson Associates management in 2011 when Jackson left
A&M.
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By 2018 field experience with most smart grid technologies and programs
provided utility decision-makers with reliable results to move beyond a model-based
decision process.
Click Here for more detail on SRC 1.0 history.
New SGRC 2.0 Grid Impact Models (GIM) Address 2025 Grid-level Modeling Needs
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Field experience has removed much of the uncertainty around SG technology investments, the focus of SGRC 1.0
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However, recent rapid growth in EV charging loads, increased electricifcation and
extreme weather challenges present uncertain grid impacts that can be a
threat to grid stability at the substation, individual feeder and transformer level.
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SGRC 2.0 Grid Impact Models (GIM):
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Address uncertainty surrounding EV, electrification and climate threats,
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Forecast impacts on specific grid geographic areas, and
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Identify and evaluate programs and policies
to reduce the risk of negative grid impacts.
More specifically, threats addressed by GIM include:
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EV commuter charging typically occurs at times utilities are experiencing peak loads. Even
the addition of one or two level-2 EV chargers on a feeder or transformer can cause low-voltage problems
including flickering lights, reduced transformer lifetimes and even transformer failure.
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New construction is trending towards more electric appliances contributing disproportionately
to loads in critical utility peak periods (think water heaters, ovens).
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Extreme weather can boost AC and space heating load contributions at system peak time, an impact
that becomes more important with increased electrification.
Benefits of the SGRC 2.0 Consortium Membership
The SGRC 2.0 consortium provides forecasting and analysis benefits to
members based on shared objectives and shared financial support. Each member receives
products/services at a fraction of the cost required if
provided in a traditional consulting project.
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Organizations can become members of the SGRC 2.0 consortium by simply paying a membership fee.
No contract negotiations or long-term commitments.
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Members receive a SGRC 2.0 Grid Impact Model (GIM) calibrated to their utility service area or other
geographic region along with
model documentation, and telephone support covering model application.
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Ongoing Model extensions will be identified with input from consortium members
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All model enhancements, will be provided to each Consortium member.
SGRC 2.0 Provides Easy-to-Use Excel-Based Grid Impact Models to Evaluate New 2030 - 35 Grid Threats
Our decade-long SGRC smart grid modeling experience has been applied to
develop Grid Impact Models to forecast and assess hourly load impacts of
EV ownership, electrification and extreme weather on small-area grid reliability.
This section summarizes SGRC 2.0 Grid Impact Model characteristics.
A more detailed description is
provided here.
SGRC 2.0 Grid Impact Model (GIM) characteristics Summary
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The GIM is an AI machine learning agent-based model
that incorporates actual utility customer data drawn from the
7+ million MAISY Utility Customer and Hourly Loads Database. The
AI process integrates dozens of supporting databases.
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The GIM user interface is an Excel workbook providing easy-to-use option selections
and output presentations.
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The GIM provides household hourly load forecasts as a baseline that can be
applied for traditional load forecasts for 2030 or 2035 at the ZIP, neighborhood
and utility service area level.
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Forecasts can include 2030 or 2035 EV ownership and hourly loads, electrification and extreme weather
along with impacts of demand management programs designed to limit peak load impacts. These
forecast options can be evaluated singly or in any combination.
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2030/35 forecasts can be presented for the current household population or
for total forecast housesholds in those years based on historical or user-supplied population
increases.
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Forecast scenarios can include behavioral household response to increasing electric prices.
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Hourly load impact results are available for ZIP code areas and ZIP neighborhoods
with tabular results for all ZIPs and chart presentations for user-selected ZIPs.
Features That Make the SGRC Grid Impact Model (GIM) Utility Applications Unique
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Actual utility customer data drawn from 7 million households MAISY database.
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AI modeling process.
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Easy-to-use Excel interface.
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Traditional residential load forecasts.
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Forecast EV, electrification, extreme weather, and demand management hourly load impacts.
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Jackson Associates modeling and data development
vetted by over 150 organizations.
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