ETA 2021 Strategic Plan - Flipbook - Page 122
Medium and Heavy-Duty Electric Vehicle
Infrastructure Load Operations and Deployment
(HEVILOAD): A new software tool to project charging
infrastructure needed to decarbonize trucking and to
reduce the impact of diesel air pollution by on-road
medium- and heavy-duty (MDHD) vehicles; provide a
quantitative assessment of optimal charging infrastructure
planning, operation, and deployment with high spatial and
temporal resolution; and evaluate grid impacts based on
MDHD mobility demands.
V2G-Sim: Models the driving and charging behavior of
individual plug-in electric vehicles to generate temporal
and spatial grid-scale impact/opportunity predictions.
Python Grid Discretization Helper (PyGDH [“pigged”]):
A highly flexible package aimed at helping domain
scientists solve arbitrary time-dependent nonlinear
discretized equations on 0D, 1D, and simple 2D spatial
domains. A modular battery simulation package built on
PyGDH will be available in the near future.
Battery Sizing, Testing, and Costing Model (BSTC
Model): A model that incorporates a battery use profile
from an actual use database and combines it with a
battery life model to properly size the battery to optimize
for life, and thereby indicate the allowable cost of the
battery system for a targeted levelized cost of storage. The
model also can prescribe a simplified test protocol in the
place of the anticipated use profile that will result in the
same degree of battery degradation in the same amount
of time.
Utility and Microgrid
Optimization and Planning Tools
Interruption Cost Estimate Calculator (ICE Calculator):
Designed for electric reliability planners at utilities,
government organizations, or other entities that are
interested in estimating interruption costs and/or the
benefits associated with reliability improvements in the
United States.
Distributed Energy Resources Customer Adoption
Model (DER-CAM): A powerful and comprehensive
decision support tool that primarily serves the purpose
of finding optimal distributed energy resource (DER)
investments in the context of either buildings or multienergy microgrids. This widely accepted and extensively
peer-reviewed model has been developed by Berkeley Lab
since 2000, and can be used to find the optimal portfolio,
sizing, placement, and dispatch of a wide range of DERs,
while co-optimizing multiple stacked value streams that
include load shifting, peak shaving, and power export
agreements, or participation in ancillary service markets.
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Integrated Modeling Tool (IMT): A model that captures
the dynamic between consumers’ adoption of distributed
energy resources, distribution grid planning, and rate
design, providing a unique modeling framework to
support utility and regulatory decisions around electricity
rate structures and cost recovery.
Risk-controlled Expansion Planning with Distributed
Resources (REPAIR): A model that is building the
foundational capabilities enabling risk-controlled decisions
in utility grid planning to prevent and mitigate the impact
of outages caused by regular equipment failures or
by high-impact low-probability events, such as storms,
earthquakes, or wildfires that may cause longer-term
interruptions of service from the transmission system.
Distributed Optimal and Predictive Energy Resources
(DOPER) Controller: An open-source model predictive
controller for distributed energy resources. It optimally
coordinates DERs and controllable loads, such as
photovoltaic with smart inverters, battery storage, electric
vehicles, as well as building components such as lighting
and heating, ventilation, and air conditioning to minimize
the total energy cost for the asset owner and increase
building occupant comfort, while providing additional
services to the grid.
Building and Microgrid Technology
and Performance
Building Efficiency Targeting Tool for Energy Retrofits
(BETTER): Winner of an R&D 100 Award and a Berkeley
Lab Director’s Award for Technology Transfer, BETTER
uses minimal computing resources and data inputs to
benchmark a building’s or portfolio’s energy use against
peers; quantify energy, cost, and greenhouse gas savings
potential for investors; and recommend energy efficiency
improvements, targeting specific energy savings levels.
COMFEN (Commercial Fenestration): A tool to analyze
and optimize façade options for commercial buildings and
capabilities, including evaluation of energy consumption,
daylighting, glare, and thermal comfort.
Demand Response Quick Assessment Tool (DRQAT):
Predicts the energy and demand saving, the economic
saving, and the thermal comfort impacts for various
demand responsive strategies.
International Glazing DataBase and Complex Glazing
DataBase (IGDB/CGDB): Berkeley Lab’s industry standard
comprehensive database for optical properties of over
5,000 glazing and shading solutions available worldwide.
MPCpy: A Python package that facilitates the testing and
implementation of occupant-integrated model predictive
control for building systems.
