Washington Utility-Side Charging Infrastructure Assessment (WUSCIA) Final Report (November 2024)
Summary
Washington Utility-Side Charging Infrastructure Assessment (WUSCIA) Final Report, dated November 2024. The executive summary states that the assessment estimates utility-side costs needed to deliver power to the state's growing electric vehicle population, benchmarked to the Transportation Electrification Strategy (TES), and that the Washington State Department of Commerce (Commerce) was appropriated funds in the 2024 supplemental transportation budget to commission it. It states that ICF analyzed over 1,200 circuits from several utilities. The Findings section states that distribution system capacity will likely need to increase by 4-7 gigawatts (GW) by 2035 and that the needed statewide utility infrastructure upgrades are estimated to cost between $17 billion and $25 billion.
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Washington Utility-Side
Charging Infrastructure
Assessment (WUSCIA)
Final Report
November 2024
Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Table of Contents
Executive Summary........................................................................................................................................................................................................................ 1
Findings............................................................................................................................................................................................................................................. 2
Methodology .................................................................................................................................................................................................................................4
List of Definitions ........................................................................................................................................................................................................................... 6
Acknowledgment ............................................................................................................................................................................................................................ 7
Introduction.........................................................................................................................................................................................................................................8
Transportation Electrification in Washington .......................................................................................................................................................8
Washington Electric Utility Landscape ...................................................................................................................................................................10
Structure Overview ..................................................................................................................................................................................................................11
Methodology .................................................................................................................................................................................................................................... 12
Refine TES EV Charging Results .................................................................................................................................................................................... 12
EV Charging Peak Loads ..................................................................................................................................................................................................... 16
Nameplate Standard ....................................................................................................................................................................................................... 18
Distributed Scenario ....................................................................................................................................................................................................... 18
Managed Scenario ............................................................................................................................................................................................................ 19
Peak Load Comparison ................................................................................................................................................................................................. 21
Utility Data Gathering .......................................................................................................................................................................................................... 22
Load and Capacity Analysis ........................................................................................................................................................................................... 23
Cost Estimates .........................................................................................................................................................................................................................25
Distribution System Upgrade ..................................................................................................................................................................................25
Transmission System Upgrade ...............................................................................................................................................................................26
Results and Findings ..................................................................................................................................................................................................................29
Load Impact from Transportation Electrification ...........................................................................................................................................29
Circuit and Transformer Overload .............................................................................................................................................................................. 31
Discussion .........................................................................................................................................................................................................................................34
Utility Practices ........................................................................................................................................................................................................................34
Financial Impact ......................................................................................................................................................................................................................35
Appendix A: Peak Load Comparison by CBGs .......................................................................................................................................................38
Appendix B: Data Request Guide ...................................................................................................................................................................................... 41
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Project Overview ..................................................................................................................................................................................................................... 41
Utility Data Request............................................................................................................................................................................................................... 41
Data Requested .................................................................................................................................................................................................................42
Data Privacy, Sharing, and Purging .......................................................................................................................................................................42
Project Timeline .................................................................................................................................................................................................................42
Equipment Cost Data ..........................................................................................................................................................................................................43
Asset and Load Data ...........................................................................................................................................................................................................43
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Executive Summary
The Washington Utility-Side Charging Infrastructure Assessment (WUSCIA) estimates utility-side costs
needed to deliver power to the state’s growing electric vehicle population, benchmarked to the landmark
Transportation Electrification Strategy (TES). The TES was developed by the Interagency Electric Vehicle
Coordinating Council (EV Council), published in February 2024, and includes recommended actions the state
can take to ensure the benefits of driving electric vehicles (EVs), charging infrastructure, and market
incentives are accessible and available to all people in Washington. This strategy is part of Washington’s
broader goal of reducing greenhouse gas (GHG) emissions and promoting sustainable energy solutions.
The Washington State Department of Commerce (Commerce) was appropriated funds in the 2024
supplemental transportation budget to commission this study based on the findings of the TES about costs of
installation, maintenance, and operation of electrical distribution infrastructure on the utility’s side of the
meter to commercial customers installing electric vehicle supply equipment. Commerce was required to
gather data from at least five electric utilities serving retail customers in the state, and submit findings and an
explanation of how these findings will support implementation of the TES authorized under RCW 43.392.040
to the governor and appropriate legislative committees.
The transition to EVs will require significant upgrades to the electrical infrastructure, including the installation
of new distribution circuits, transformers, and substations to handle the increased electricity loads. The
assessment provides detailed cost projections for the planning, installation, and maintenance of the
necessary infrastructure through 2035. The projected costs of transportation electrification can be used for
prioritizing distribution planning, and identifying the cost savings due to managed charging and off-peak
charging incentives. The assessment then examines the financial implications for various stakeholders
including utilities, ratepayers, and electric vehicle service providers, and emphasizes the importance of
equitable cost distribution to avoid disproportionate economic burdens on any single group. Understanding
the total utility-side costs associated with reaching Washington’s transportation electrification goals allows
for strategic investment in grid infrastructure that minimizes unnecessary costs.
ICF worked closely with several utilities in the state of Washington to gather vital information about the
distribution system to assess the financial and logistical impacts of increased electrification on the utility grid.
Through this collaboration, ICF analyzed over 1,200 circuits, which provided more accurate projections for
system upgrades and cost estimates for all utilities in the state. Below is a summary of the participating
utilities and the number of circuits provided for the analysis.
Table ES1. Summary of utility data analyzed
Utility Number of Circuits Analyzed
Mason County PUD No. 1 12
Avista 228
Kittitas PUD No.1 12
Seattle City Light 173
Puget Sound Energy 814
Total 1,239
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
1.1 Findings
The analysis finds that the capacity of the distribution system will likely need to increase by 4-7 gigawatts
(GW) by 2035. The needed statewide utility infrastructure upgrades are estimated to cost between $17 billion
and $25 billion, including $8 billion to $12 billion dedicated to building out the distribution system,
considerably less than the alternative of gasoline and diesel energy costs, as indicated by the 2021 State
Energy Strategy. The total costs include high-level transmission capital and operation and maintenance cost
estimates. .
The analysis points to the importance of scaling up the initial utility efforts to manage charging to more evenly
spread electricity needs across different times. This work is essential to lower overall costs, remove financial
barriers to large-scale charging projects, and protect ratepayers who have less access to EVs.
Figure ES1. Statewide high-, mid-, and low-cost scenarios associated with utility-side infrastructure
upgrades to support transportation electrification, maintenance and operation (M&O) included
$30
$25
2.78
Total Costs ($ billion)
2.47
$20 4.63
4.12
1.89
$15 6.29
5.60 3.15
$10 4.29
11.66 10.37
$5
7.95
$0
High-Cost Scenario Mid-Cost Scenario Low-Cost Scenario
Distribution System Capital Distribution System M&O
Transmission System Capital Transmission System M&O
EV-related grid costs can be reduced by more than 30% through carefully planned
managed charging.
With appropriate measures and reinforcement, the implementation of managed charging could save up to $8
billion dollars in infrastructure and operations. The project team recommends that both the state and utilities
examine the full set of options for incentives, rate policies, actively managed charging and demand response
programs to help mitigate the impacts of EV charging costs to utilities and ratepayers. Compared to the
nameplate standard, defined as the maximum possible demand scenario, the distributed and managed
scenarios in Figure ES2 demonstrate a smaller peak load. Peak load is used to determine what grid
infrastructure is needed to meet the electricity demand. Reducing the peak load through programs and
strategic distribution planning by utilities can save unnecessary and costly grid upgrades.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure ES2. Sample peak loads under the nameplate standard, distributed scenario, and managed
scenario
30000
25000
20000
Load, kW
15000
10000
5000
0
Nameplate Distributed Managed
Light-Duty Medium- and Heavy-Duty
The report provides more detail on potential strategies to manage charging loads, such as shifting charging
times to off-peak hours to reduce peak loads and strain on the grid. Part of these strategies include preparing
for disproportionate strain on the grid from different vehicle classes. Larger vehicles will demand greater
charging concentrated along corridors, while light duty vehicles will largely charge at home. These strategies
will optimize the use of existing infrastructure.
Utilities need to plan to prevent project backlogs that risk slowing the EV transition.
The state will need to identify who is coordinating planning work between utilities and fleets and ensure those
efforts are funded. Additionally, utilities will need to carefully plan EV-required upgrade projects with general
system planning upgrades that normally occur throughout the distribution planning process. Due to current
limitations such as supply chain delays for required equipment, general system improvement projects are
experiencing a longer timeline for completion, sometimes taking over a year to energize a new load on the
system. Planning for the increased equipment required to support electrification will need to be included in
the project planning process.
Upgrading utility infrastructure for electric vehicles will cost considerably less than gasoline
and diesel alternatives. However, not all ratepayers have access to electric options. The
state and utilities should structure costs to ensure those who are most able to shoulder
costs and access benefits take on of the cost burden.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure ES3. Overview of the cost analysis undertaken in this study
1.2 Methodology
The project team gathered data from utilities, state agencies, and industry reports to complete the analysis.
By overlaying estimated charging electricity loads over utility grid data, the costs for needed circuit and
transformer upgrades or expansions and corresponding maintenance were then identified.
Utility data: Participating utilities provided circuit and transformer data to understand the loading of their
existing systems. Utilities also provided cost estimates for conductors, transformers, and substation
equipment, which were used to estimate the cost of upgrades for each circuit.
Charging targets: To understand the effect of load on utilities, the project team used the charger estimates
from the TES for 2035 as outlined in the Strong Electrification Policy scenario. This scenario includes both the
state’s requirement that 100% of new passenger vehicles and light-duty truck sales be electric by 2035, and
larger state and federal incentives for zero emission vehicles (ZEVs) and charging infrastructure. This scenario
also assumes considerably faster adoption of zero emission medium- and heavy-duty (MHD) trucks and
buses based on federal incentives from the Inflation Reduction Act.
To use the TES results, the project team developed a specific methodology to distribute heavy-duty charger
counts from the county level to the Census Block Group (CBG) level. Hourly charging loads were then
estimated at each CBG using three charging cases – (1) nameplate standard, (2) distributed scenario, and (3)
managed scenario - which each represent different ways utilities estimate the impacts of EV charging
infrastructure.
Grid analysis: Electricity loads were then applied to the utility grid data to identify the overloaded circuits
and transformers across the three case studies. This data was used to estimate the costs of upgrading this
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
infrastructure for the participating utilities. Then, these costs were projected across the entire state to fill in
the regions of the state the project team did not have access to utility data. Ultimately, the model used utility
data covering 47% of the state’s population, and cost projections to cover the remainder of the state.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
List of Definitions
ACC Advanced Clean Cars
ACF Advanced Clean Fleets
ACS American Community Survey
CBG Census Block Group
CCA Climate Commitment Act
CETA Clean Energy Transformation Act
Commerce Washington State Department of Commerce
CO2e Carbon Dioxide Equivalent
COUs Consumer-Publicly Owned Utilities
DCFC Direct Current Fast Charging
DER Distributed Energy Resources
EIA U.S. Energy Information Administration
EV Electric Vehicle
EV Council The Interagency Electric Vehicle Coordinating Council
EVSP Electric Vehicle Service Providers
GHG Greenhouse Gases
HD Heavy-Duty
ICEV Internal Combustion Engine Vehicle
IOU Investor-Owned Utility
LD Light-Duty
L2 Level 2 Charger
MD Medium-Duty
MFH Multi-Family Housing
MHD Medium- and Heavy-Duty
MHDV Medium- and Heavy-Duty Vehicle
MMT Million Metric Tons
MW Megawatt
MY Model Year
NTD National Transit Database
PUD Public Utility District
TES Transportation Electrification Strategy
TOU Time-of-Use
TWh Terawatt-Hour
UTC Washington Utilities and Transportation Commission
VMT Vehicle Miles Travelled
VPP Virtual Power Plant
V2G Vehicle-to-Grid
WAC Washington Administrative Code
WUSCIA Washington Utility-Side Charging Infrastructure Assessment
ZEV Zero-Emission Vehicle
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Acknowledgment
The project team would like to thank the following individual state agencies, utility partners, and service
providers for their valuable input throughout the development of the Washington Utility-Side Charging
Infrastructure Assessment (WUSCIA).
Washington Interagency Electric Vehicle Puget Sound Energy
Coordinating Council
Danielle Kievit*
Washington State Department of Commerce
Grant Marmion
Emma Wyma*
Chelan County PUD
Steven Hershkowitz*
Andrew Grassell*
Michael Furze
Seattle City Light
Jason Henderson
Uzma Siddiqi*
Glenn Blackmon
Matt Michael
Andrew Rector
Inland Power & Light Co.
Aaron Tam
Kimberly Gentle*
Washington State Department of Ecology
Dustin Bruffett
Joshua Grandbouche
Tesla
Washington Utilities and Transportation
Noelani Derrickson*
Commission
Avista Corporation
Aaron Cahen*
Erik Lee
Andy Sellards*
Rendall Farley
Washington State Office of the Attorney General
Matt Townsend
Stephanie Chase*
Zach Newsom
Office of Superintendent of Public Instruction
Mason PUD
Patti Enbody
Jeremiah Waugh
The Rocky Mountain Institute
Kristin Masteller
Ben Shapiro
City of Ellensburg
Paul Meyer
Kittitas PUD
Ken Edwards
Jordan Smith
* Steering Committee Member
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Introduction
In the state of Washington, the transportation sector represents 39% of economy-wide greenhouse gas
(GHG) emissions.1 In an effort to reduce carbon emissions from the transportation sector, the state has taken
multiple actionable steps, including adopting clean vehicle regulations by reference from California. These
regulations are part of a strong set of policies that will help Washington reach 100% electric sales for
passenger vehicles and light-duty (LD) trucks by model year (MY) 2035, while also accelerating the transition
of medium- and heavy-duty vehicles (MHDV) to zero emission.2 To fulfill Washington’s clean transportation
and climate goals, the Interagency Electric Vehicle Coordinating Council (EV Council) 3, jointly led by the
Washington State Department of Commerce (Commerce) and the Washington State Department of
Transportation (WSDOT), created a comprehensive scoping plan, the Transportation Electrification Strategy
(TES), to facilitate the transition to ZEVs across the state. The Washington Utility-Side Charging Infrastructure
Assessment (hereby referred to as WUSCIA) serves as a follow-up to the TES, providing a comprehensive
utility-side cost evaluation of the charging infrastructure buildout necessary for achieving Washington’s ZEV
goals.
1.3 Transportation Electrification in Washington
The TES reflects Washington’s strong commitment to reducing GHG emissions from transportation through
aggressive policy actions. In recent years, Washington has passed several such regulations that either
indirectly or directly impact the transportation sector. In 2019, Governor Jay Inslee signed into law the
monumental Clean Energy Transformation Act (CETA), which mandates that the state's electricity supply be
100% GHG-neutral by 2030 and 100% free of GHG emissions by 2045. In 2020, the Washington State
Legislature enacted new emissions limits to cut GHG emissions 45% below 1990 levels by 2030, 70% below
1990 levels by 2040, and 95% below 1990 levels with net zero emissions by 2050. In line with these economy-
wide limits, the Legislature established the non-binding target of 100% electric sales of publicly owned and
privately owned passenger and light duty vehicles (LDV) by model year (MY) 2030. This regulation established
the EV Council, a formal interagency council, to coordinate the state's transportation electrification efforts.
The EV Council ensures the state is leveraging state and federal resources to the best extent possible and
makes zero emissions incentives, infrastructure, and opportunities available and accessible to all
Washingtonians.
Multiple ZEV regulations have been adopted since then to reduce transportation-related emissions. Notably,
the Advanced Clean Cars (ACC) I and II programs mandate automakers to incrementally increase the sales of
ZEVs, including battery-electric, hydrogen fuel cell, and plug-in hybrids with a minimum all-electric range of
50 miles, beginning in MY 2025. The sale percentage is projected to increase from 8-9% in MY 2025 to 100%
by MY 2035. ACC I and II also include a provision for environmental justice credits to incentivize automakers
to offer lower-cost ZEVs across the state.4 Similarly, the Advanced Clean Trucks (ACT) regulation was adopted
1
Washington State Greenhouse Gas Emissions Inventory: 1990–2019. Available at:
https://apps.ecology.wa.gov/publications/documents/2202054.pdf
2
Washington State Department of Ecology, Clean vehicles. Available at: https://ecology.wa.gov/air-climate/reducing-
greenhouse-gas-emissions/zev
3
Washington State Department of Commerce, Electric Vehicle Coordinating Council (EVCC). Available at:
https://www.commerce.wa.gov/growing-the-economy/energy/clean-transportation/ev-coordinating-council/
4
Washington State Legislature, WAC 173-423-075: Zero-emission Vehicle Standards. Available at:
https://app.leg.wa.gov/wac/default.aspx?cite=173-423-075
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
in 2021, which requires manufacturers to produce and sell an increasing percentage of zero-emission MHD
vehicles.5 The ACT mandates 40-75% zero-emission MHDV sales, based on weight class, by MY 2035.
In 2024, the EV Council published the final TES for the period up to 2035. The TES provides a thorough
evaluation of the state's infrastructure requirements, including electric vehicle supply equipment (EVSE), to
accommodate the expected increase in ZEVs in the coming years. According to this evaluation, the state of
Washington requires more than 3 million charging ports by 2035, generating an evening peak load of 3.4 GW
under the Strong Electrification Policy scenario.6 An overview of this projected load by 2035 is included in
Figure 1. Given the substantial increase in demand from the accelerated deployment of EV charging
infrastructure, significant upgrades to the electrical infrastructure are inevitable on both the customer and
utility sides of the meter. These enhancements, crucial for maintaining grid capacity and reliability, will
encompass a range of improvements, such as upgrading or adding new distribution circuits, replacing or
augmenting transformers to handle higher loads, expanding or modernizing distribution substations for
increased capacity, and implementing segment-level upgrades in areas heavily impacted by EV charging. In
addition, they also involve upgrading distribution system components downstream from substations and main
feeders, installing or enhancing voltage regulation systems for stable power supply, and strengthening
transmission system components within each utility’s territory.
Figure 1. Projected statewide EV load in 2035 under strong electrification policy scenario (TES)
4
3.5
Statewide Charger Load (GW)
3
2.5
2
1.5
1
0.5
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour of Day
Single-Family L2 Multifamily L2 Workplace L2 Public L2 Public DCFC MHD Trucks Bus Depots
5
Washington Department of Ecology. Available at: https://ecology.wa.gov/blog/april-2023/electric-trucks-to-join-state-
s-clean-transportati
6
This scenario assumes that Washington enacts additional policy to support electrification such as higher incentives for
ZEVs and EVSE, inclusion of the Advanced Clean Fleets (ACF) rule’s adoption rates and education and outreach to
encourage strong consumer interest in ZEVs.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
These necessary upgrades to support EV charging infrastructure will incur significant costs. The WUSCIA is
designed to chart these financial requirements to successfully execute the TES. This encompasses the entire
spectrum of costs related to planning, installing, maintaining, and operating the requisite utility infrastructure,
to ensure efficient powering of all projected EV charging stations, ports, and connectors as outlined in the TES
Strong Electrification Policy scenario, extending through 2035. This initiative is a critical step in managing the
transition to an electrified transportation system in Washington, balancing cost-effectiveness with the
ambitious objectives of the TES.
1.4 Washington Electric Utility Landscape
Washington has roughly 60 electric utilities in total. The Washington Utilities and Transportation Commission
(UTC) regulates the state’s three electric investor-owned utilities (IOUs): Avista Corporation, PacifiCorp, and
Puget Sound Energy (PSE). The remaining utilities are consumer-publicly owned utilities (COUs) and include
public utility districts (PUDs), municipal utilities, and electric cooperatives (Coop), each operating under
unique governance models and an elected commission or city council. Figure 2 provides a map showing each
utility’s service area.
Figure 2. Map of utility service areas in Washington state7
Figure 3 lists the total customers and the ownership type of Washington’s sixteen largest electric utilities. The
diverse profiles of utilities also lead to a variety of practices for grid planning, with multiple actors driving
7 Washington State Department of Ecology, Electric Utility Service Areas. Available at:
https://gis.ecology.wa.gov/portal/home/item.html?id=e62c6fcb7b674f15b8267fe9dc02f34f#
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
decision-making. This makes collective action on transportation electrification challenging. A major objective
of WUSCIA is to enable these diverse stakeholders to work together. As such, several local utilities were
engaged during their development to determine their diverse goals and interests, incorporate transportation
electrification plans, and provide a platform for collective decision-making on EVSE-related grid upgrade
planning in line with the TES.
Figure 3. Sixteen largest electric utilities in Washington by ownership type, and customers served 8
Total Utility Customers
0 400K 800K 1,200K
Puget Sound Energy Inc
Seattle City Light
Snohomish County PUD #1
Avista Corp
Clark County PUD #1
Tacoma Power
PacifiCorp
Benton County PUD #1
Grant County PUD #2
Cowlitz County PUD #1
Chelan County PUD #1
Grays Harbor County PUD #1
Inland Power & Light
Mason County PUD #3
Peninsula Light Company
Lewis County PUD #1
Investor Owned Municipal/PUD Cooperative
1.5 Structure Overview
WUSCIA is a strategic initiative designed to provide a comprehensive estimation of the net present value
costs associated with EVSE-related infrastructure on the utility side of the meter. It serves as a critical step in
managing the transition to an electrified transportation system, balancing cost-effectiveness and diverse
stakeholder interests with the ambitious objectives of the TES. The next section of this report describes the
methodology used to conduct the net present cost estimation for EVSE-related grid upgrades. The following
sections detail the local utility engagement process, key results and findings of the assessment, their
implications for key stakeholders and the broader economy, and actionable recommendations for
policymakers to facilitate utility-side infrastructure development in line with the TES and state climate goals.
8 Northwest Clean Energy Atlas, Washington Electric Utilities Overview. Available at:
https://www.nwceatlas.org/visualization/washington-electric-utilities-overview
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Methodology
1.6 Refine TES EV Charging Results
This analysis utilized the results of the TES, which included projections of EV adoption in the state of
Washington by 2035 and estimates of vehicle miles traveled (VMT) and the electrical load needed to power
them across several different policy scenarios. At the direction of Commerce, the project team used the
Strong Electrification Policy (#3) scenario9 as a basis for this work in estimating the number of charging ports
needed throughout the state. In order to understand the impacts of these vehicles on utilities at the most
granular level, the project team needed to estimate the additional capacity needed at the smallest
geographical level of analysis possible. For this study, Census Block Groups (CBG) were used since it is the
smallest area in which trip data and population data are both available. The TES also used CBG as the unit of
analysis for LD vehicles, so the estimates of LD EVSE port counts can be applied directly. However, the TES
only produced estimates of MHD charging ports at the county level, and thus the project team downscaled
them to the CBG level to allow the analysis to take place at the consistent geographic scale across all port
types. This section describes the techniques used to downscale this data as well as other adjustments made
to the TES MHD results. A summary of this process is described in Figure 4.
Figure 4. Procedure for distributing county-level EVSE port counts to the CBG level
Step 2: Calculate
Step 3: Multiply county
Step 1: Gather trip and weighted allocation
port counts by
population data at factors at CBG level
allocation factors at
CBG level by port type based on data
CBG level
collected
Step 5: Redistribute
Step 4: Adjust for out-
Step 6: Adjust for ports located in CBGs
of-state trucks
Megawatt charging that are lower than the
operating in
needs for HD Public predetermined
Washington
thresholds
First, the project team used a set of variables to determine the allocation factors of ports from each county
that should be distributed to a given CBG. For each of the vehicle and charger type combinations, the
variables shown in
9 This scenario was seen as the most feasible and likely EV adoption scenario based on the state’s current policy
commitments. It considers the effects of Washington’s implementation of California’s Advanced Clean Cars II and
Advanced Clean Fleet policies through its commitments as a Section 177 state, as well as proposed vehicle and
infrastructure incentive policies. More details on this can be found in the final TES.
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Table 1 were used to calculate the allocation factor, which reflected the fraction of that EVSE ports which fell
into each CBG.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Table 1. Variables used to distribute county chargers down to CBG level
Charger
Vehicle Type Input Data Data Source Weight
Type
School Bus Depot School-aged population (5-17 yrs.) US Census 100%
National Transit Database
Revenue-miles by transit agency 100%
(NTD)
Depot
Transit Bus Locations of bus depots by transit
NTD N/A10
agency
Buses in operation by bus depot NTD N/A11
Commercial vehicle trip origins Replica12 30%
Commercial vehicle trips over 50
Public Replica 20%
miles
Medium and Number of truck parking spaces in Washington Department
50%
Heavy Duty truck stops of Commerce
Commercial vehicle trip origins Replica 50%
Depot Area zoned as industrial or Washington State Parcels
50%
warehousing Project13 (2023)
One of the limitations for the assumptions used for transit buses is that it assumes that all charging for buses
will happen at depots – and not along routes. While some transit agencies have expressed interest in
expanding on-route charging, there is currently a lack of commitment from the industry toward this
technology as well as notably higher infrastructure costs compared with depot charging. Thus, all transit
charging was assumed to take place at the depot. This is a fair assumption since a depot is usually the most
cost-effective place to install chargers for the agency and in many cases, charging at a depot is used directly
by the utility which oversees that depot for grid planning purposes.
Given there is not a dataset which covers school bus depots for all school districts in Washington, school bus
depots are assumed to be reasonably distributed along with student populations. An example to calculate the
allocation factor for school bus depot charging ports is given in Equation 1. When calculating the allocation
factor of charging ports, the school-aged population in any given CBG is divided by the total school aged
population of that county.
Equation 1. Example of the allocation factor calculations for the school bus depot ports
𝑆𝑐ℎ𝑜𝑜𝑙 𝐴𝑔𝑒𝑑 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝐶𝐵𝐺
𝑆𝑐ℎ𝑜𝑜𝑙 𝐵𝑢𝑠 𝐷𝑒𝑝𝑜𝑡 𝐴𝑙𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟 𝐶𝐵𝐺 =
𝑆𝑐ℎ𝑜𝑜𝑙 𝐴𝑔𝑒𝑑 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝐶𝑜𝑢𝑛𝑡𝑦
10
Used to identify which CBGs to locate each transit agency’s revenue miles in.
11
Used to allocate revenue miles between depot locations for agencies with multiple depots.
12
Replica data lists every trip taken by commercial trucks which either starts or ends in Washington in Spring 2023 on a
typical Thursday. It includes the census block group in which each trip started and ended, trip purpose, trip length and the
trip start and end times.
13
Washington State Geospatial Open Data Portal. Available at:
https://geo.wa.gov/datasets/a0ddbd4e0e2141b3841a6a42ff5aff46
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
For the public charger data, the locations of existing truck stops were assigned with a highest weight because
those are the most likely sites for future MHD public chargers. These places already show high demand for
truck traffic and often have amenities, which would serve drivers that are staying for extended periods of time
while charging. Truck trips over 50 miles were weighted higher because they are more likely to require public
charging. Given there are more data sources used for this EVSE category, the formula to calculate the
weighing factor, as shown in Equation 2 is more complicated than that for school bus depot.
Equation 2. Example of the allocation factor calculations for the HD public charging ports
𝐻𝐷 𝑃𝑢𝑏𝑙𝑖𝑐 𝐶ℎ𝑎𝑟𝑔𝑒𝑟 𝐴𝑙𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟𝐶𝐵𝐺
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝐷 𝑇𝑟𝑖𝑝𝑠 𝑂𝑟𝑖𝑔𝑖𝑛𝑎𝑡𝑒𝑑𝐶𝐵𝐺
= 30% × + 20%
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝐷 𝑇𝑟𝑖𝑝𝑠 𝑂𝑟𝑖𝑔𝑖𝑛𝑎𝑡𝑒𝑑𝐶𝑜𝑢𝑛𝑡𝑦
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝐷 𝐿𝑜𝑛𝑔 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑇𝑟𝑖𝑝𝑠 𝑂𝑟𝑖𝑔𝑖𝑛𝑎𝑡𝑒𝑑𝐶𝐵𝐺
× + 50%
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝐷 𝐿𝑜𝑛𝑔 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑇𝑟𝑖𝑝𝑠 𝑂𝑟𝑖𝑔𝑖𝑛𝑎𝑡𝑒𝑑𝐶𝑜𝑢𝑛𝑡𝑦
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝐷 𝑇𝑟𝑢𝑐𝑘 𝑃𝑎𝑟𝑘𝑖𝑛𝑔 𝑆𝑝𝑎𝑐𝑒𝑠𝐶𝐵𝐺
×
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐻𝐷 𝑇𝑟𝑢𝑐𝑘 𝑃𝑎𝑟𝑘𝑖𝑛𝑔 𝑆𝑝𝑎𝑐𝑒𝑠𝐶𝑜𝑢𝑛𝑡𝑦
For MHD depot charging, trips over 50 miles were no longer considered because depots can be home to an
assortment of different vocation types with more frequent and shorter trips. However, areas within a given
CBG zoned as industrial or warehousing were accounted for, since these are the types of locations which
already serve as truck depots and are anticipated to host depot chargers in the future.
After calculating the allocation factors for each CBG by EVSE port and vehicle type, county level charging port
data to the CBG level by multiplying the county total by that CBG’s factor. An example of this for the HD
Public chargers is shown below in Equation 3.
Equation 3. Example of the allocation of ports from the county to CBG level for HD public ports
𝐻𝐷 𝑃𝑢𝑏𝑙𝑖𝑐 𝑃𝑜𝑟𝑡 𝐶𝐵𝐺 = 𝐻𝐷 𝑃𝑢𝑏𝑙𝑖𝑐 𝐶ℎ𝑎𝑟𝑔𝑒𝑟 𝐴𝑙𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟𝐶𝐵𝐺 × 𝐻𝐷 𝑃𝑢𝑏𝑙𝑖𝑐 𝑃𝑜𝑟𝑡 𝐶𝑜𝑢𝑛𝑡𝑦
The project team then adjusted the charger counts for trucks operating in Washington that are registered out
of state. Note that the EVSE projections from the TES did not account for the charging demand of trucks not
registered in Washington. The TES, however, has determined that out-of-state registration is roughly 18% to
30% for MD trucks, and 30% to 50% for HD trucks.14 These factors were used to scale up the electricity
demand to reflect charging demands from out-of-state trucks. This adjustment is necessary because it
assesses the energy demand more accurately as trucks operated in the state, are likely to charge. The project
team also confirmed the out-of-state fraction by cross-referencing it with the trip fractions from out-of-state
trucks in the Replica data to ensure that the applied scaling factor is appropriate.
While trip- and population-based data serve as a reasonable proxy to distribute chargers from county to CBG
levels, this methodology could lead to some unreasonably small numbers of chargers in certain CBGs. For
instance, from a profit-generating perspective, it is very unlikely to see one public DCFC port by itself in one
CBG. As a reference, currently in the state of Washington, one public DCFC charging station has four ports on
average.15 Therefore, the project team applied a threshold to regroup chargers from CBGs with small fractions.
14
RMI analysis of FHWA data suggests that in Washington, the percentage of total state highway miles driven by vehicles
registered outside the state is approximately 18% for MD trucks and potentially as high as 50% for HD trucks.
15
Average calculated based on the U.S. Department of Energy Alternative Fuels Data Center Station Locator. Available at:
https://afdc.energy.gov/stations#/find/nearest
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
In the case of depot chargers, any CBG with less than one port for a given type was reallocated into the pool
of total chargers. For public chargers, any CBG with fewer than four chargers were reallocated. This difference
is explained by the fact that one business might have a single charger in a given area. Still, it is not expected
that MHD charger installations be made with only one or two chargers due to the high cost of electrical and
charging infrastructure required to install them. Then, the chargers in the pool were reallocated to CBGs based
on the proportion of chargers in the county that they already received. This follows the principle that the
relative proportion should not change but that these reallocated chargers are more likely to go to places with
very high demand (dozens of chargers) than those which are projected to only have one or two chargers.
Lastly, the project team apportioned some of the charging demand from long-haul trucks to megawatt (MW)
charging stations. Long-haul trucking is expected to rely upon these faster charging options to make
interstate travel possible, which typically use a larger draw than 350kW. The TES assumed that public charging
power caps out at 350 kW, which was determined to be too small for this analysis. For instance, according to
long-haul tractors telematics data, 25% of trips are slip-seat operations, which means the truck is driven for
more than 700 miles or 16 hours without stopping for a break of 4 hours or longer. 16 In such cases, high-power
MW public charging will be necessary. Per communication with HD charging providers, the project team
learned that these providers intend to exclusively use MW-charging compatible chargers at their larger
charger depots since these stations provide the highest hourly revenue per station. This allows the providers
to recoup their upfront investment in charger installation faster and make them a destination for electric
truckers in the future. Knowing this, every CBG with 20 or more HD public chargers was upgraded to host MW
chargers. This leads to a higher peak demand than what was originally estimated in the TES, but this would be
necessary for long-haul fleet applications given this new data. The results of this distribution are illustrated in
Figure 5. Note that not all CBGs are expected to have MHD chargers.
1.7 EV Charging Peak Loads
Having determined the number of chargers at each CBG in Washington, the project team estimated the
amount of additional capacity in the distribution system needed in each CBG. In this study, peak hourly loads
imposed by these chargers were used on the grid as a proxy for capacities required to support EV charging
activities. These loads were then fed into the electrical simulation software (e.g., Windmil, Synergi, and CYME)
that models and analyzes power distribution systems to estimate the excess capacities that need to be built
out by utilities. The project team has defined three different cases for estimating the peak loads of these
chargers across the day, as summarized in Table 2 below.
Table 2. Overview of charging demand cases
Scenario # Charging Case Charging Characteristics
1 Nameplate (Maximum Demand) Assume all chargers’ peaks are concurrent.
Chargers operate at a fraction of peak load
2 Distributed
determined by usage pattern
Distributed curve is shifted away from peak hours to
3 Managed
late-night lull
16
Mishra P, Miller E, Santhanagopalan S, Bennion K, Meintz A. A Framework to Analyze the Requirements of a Multiport
Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles. Energies. 2022; 15(10):3788.
https://doi.org/10.3390/en15103788
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure 5. Medium and heavy-duty chargers by type after distribution to the CBG level
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Nameplate Standard
For the nameplate standard, the number of chargers by type was allocated to each of the CBGs, and the load
was determined by assuming that all charging ports peak at the same time. This assumption is very
conservative and certainly unrealistic, but it can serve as a reference to highlight why nameplate standard
should not be used for future EV demand planning. The nameplate standard should also demonstrate the
benefits of considering real-world vehicle travel patterns and implementing managed charging strategies.
Consequently, this standard will yield an extremely high-cost estimate because it will require the largest scale
infrastructure upgrade. The method to calculate the peak load for each block group in this case study is
demonstrated in Equation 4 where PortCount is the number of ports present at a CBG given an EVSE type and
PortPower is the nameplate capacity of the port type.
Equation 4. Example of the hourly load calculation for their nameplate standard
𝐿𝑜𝑎𝑑𝑃𝑒𝑎𝑘,𝐶𝐵𝐺 = ∑𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒 𝑃𝑜𝑟𝑡𝐶𝑜𝑢𝑛𝑡𝐶𝐵𝐺,𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒 ∙ 𝑃𝑜𝑟𝑡𝑃𝑜𝑤𝑒𝑟𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒
Figure 6 illustrates an example of how peak hour load was calculated under the nameplate standard case in
one CBG.
Figure 6. An example of EVSE peak load under the nameplate standard case
3500 30000
3000 25000
Number of EVSE Ports
2500
20000
Load, kW
2000
15000
1500
10000
1000
500 5000
0 0
EVSE Port Peak Hour Load
LD MDHD LD MDHD
Distributed Scenario
For the distributed scenario, a system hourly load curve was used to calculate the probability of whether a
certain type of charger would be online during a specific time of the day. The hourly load curves for this study
came from the statewide time-of-day load estimates published in the TES under the Strong Electrification
Policy scenario. Given that the TES results aggregated all MHD trucks within a single load profile, the project
team supplemented this data with California’s Electric Vehicle Charging Infrastructure Assessment 17 results to
17
California Energy Commission, Second Assembly Bill (AB) 2127 Electric Vehicle Charging Infrastructure Assessment:
Assessing Charging Needs to Support Zero-Emission Vehicles in 2030 and 2035. Available at:
https://www.energy.ca.gov/publications/2023/second-assembly-bill-ab-2127-electric-vehicle-charging-infrastructure-
assessment
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
estimate the hourly occupancy probabilities for MHD public charging. Realistically, the peaks for residential,
commercial, and fleet charging will not occur at the same time. This scenario is more likely to occur compared
to the nameplate standard because it reflects the time-of-day load estimates based on the TES modeled
results and will correspond to the statewide mid-cost scenario. To calculate the load for this scenario, as
shown in Equation 5, the project team used a similar method to the nameplate standard but added the
utilization factor based on the occupancy probabilities by charger type.
Equation 5. Example of the hourly load calculation for the distributed scenario
𝐿𝑜𝑎𝑑ℎ𝑜𝑢𝑟𝑙𝑦,𝐶𝐵𝐺 = ∑ 𝑃𝑜𝑟𝑡𝐶𝑜𝑢𝑛𝑡𝐶𝐵𝐺,𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒 ∙ 𝑃𝑜𝑟𝑡𝑃𝑜𝑤𝑒𝑟𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒 ∙ 𝑃𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒,ℎ𝑜𝑢𝑟
𝑝𝑜𝑟𝑡 𝑡𝑦𝑝𝑒
In Equation 5, PortCount and PortPower have the same definition as in Equation 4, and the Probability at every
hour represents the charger occupancy probability between zero and one, the latter being the nameplate
value. Moreover, the hourly distribution factor is different for each charger type. For example, the peak load for
single-family house L2 occurs in the evening, while that for workplace L2 occurs during the daytime. An
example of the results from this scenario is shown in Figure 7.
Figure 7. An example of EV charger load under the distributed scenario
30000
25000
20000
Load, kW
15000
10000
5000
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
LD MDHD
Managed Scenario
The managed scenario assumes that the state and utilities will implement policies and programs to incentivize
off-peak charging, encouraging drivers to charge throughout the day to minimize the size of the evening
charging peak. Examples of these policies include free workplace charging, time-of-use (TOU) EV utility rates,
smart delayed charging, and direct utility control. With appropriate control measures, the charging behavior
patterns can be shifted from peak hours to the utility infrastructure valleys, reducing the maximum peak value
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
observed in the distributed scenario. The managed scenario will correspond to the lowest cost estimates
across all three cases.
Managing loads to reduce peaks has been researched extensively in the past. A recent study, published in the
Journal of Energy Storage, found that implementing smart charging in passenger vehicles can reduce peak
loads by 34%.18 Another study, published in the Renewable and Sustainable Energy Reviews, claimed that
altruistic charging, which allows for charge management at ports and considers that vehicles don’t need to
fully charge before starting their next trip, can also lower the peak by about 21%.19 It is also likely for managed
charging to occur in the MHD sector, which may require fleets to adjust their conventional operations. For
instance, in the California AB2127 assessment20, a managed demand scenario of MHD vehicles was modeled
by shifting loads from peak hours to the time period that aligns with renewable energy generation.
Table 3. Peak hours for EV charging by type and redistribute periods
Port Type Peak Hours Redistribute periods
Single Family L2 5 PM – 11 PM 12 AM – 5 AM
Multi Family L2 5 PM – 11 PM 12 AM – 5 AM
Workplace L2 8 AM – 11 PM 9 AM – 5 PM
Public L2 2 PM – 7 PM 9 AM – 5 PM
Public DCFC No change No change
MHD Depot 5 PM – 11 PM 12 AM – 5 AM
MHD Public 11 AM – 5 PM 12 AM – 5 AM
School buses 7 PM – 11 PM 12 AM – 4 AM and 9 AM – 2 PM
In designing the managed scenario for this study, the project team considered that incentives and smart
charging management could operate throughout the day and have the potential to reduce 20% from each
charger’s peak. The loads were then redistributed across the infrastructure’s lower demand periods. Table 3
demonstrates the peak hours observed from the distributed scenario and the hours that peak load was
redistributed under the managed scenario by different chargers and vehicle types. LD DCFC loads are often
unpredictable and associated with specific needs that are difficult to alter through incentives. For instance,
the time to charge for ride-hailing service drivers is greatly limited by breaks between trips and customer-
finding algorithms. Charging breaks during long-distance road trips will also be difficult to mitigate. Therefore,
no adjustment was applied to this port type. For MHD Public charging, knowing the vehicle schedule
beforehand could reduce demand for public charging during the day.
To distribute the load, this scenario uses the same equation as for the distributed scenario (Equation 5), with
the utilization factor adjusted per the redistribution periods shown above. This results in a load curve that is
higher in the early morning when system wide electrical loads are lowest and is lower during peak hours. An
example of this load curve is shown in Figure 8.
18
Giuseppe Rotondo et al.” Evaluating hourly charging profiles for different electric vehicles and charging strategies,”
Journal of Energy Storage, Volume 95, 2024, 112388, ISSN 2352-152X, https://doi.org/10.1016/j.est.2024.112388.
19
B. Williams et al. “Driving change: Electric vehicle charging behavior and peak loading,” Renewable and Sustainable Energy
Reviews, Volume 189, Part A, 2024, 113953, ISSN 1364-0321, https://doi.org/10.1016/j.rser.2023.113953.
20
https://www.energy.ca.gov/publications/2023/second-assembly-bill-ab-2127-electric-vehicle-charging-infrastructure-
assessment
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure 8. An example of EV charger load under the managed scenario
25,000
20,000
15,000
Load, kW
10,000
5,000
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
LD MDHD
Peak Load Comparison
As noted earlier, the actual peak loads will differ across each CBG due to a different combination of ports,
since each EVSE type has its own unique profile. To demonstrate the impact of distributed and managed
scenarios under various circumstances, the project team selected a few example CBGs with distinct charger
type combination profiles, as shown in Figure 9:
R+C+I: Urban CBG that shows charge type diversification, mixing both public and depot charging for
LD and MHD.
R+C: Suburban CBG with moderate MHD traffic and a significant presence of single-family housing
(SFH), and multi-family housing (MFH) L2 chargers.
R: Suburban CBG that has substantial SFH L2 and MFH L2 chargers.
I+Re+R: A combination of industrial zones that shows a significant presence of HD Public chargers and
retail areas that shows some MD Public charger presence, with some residential housing around.
TI: CBG that hosts a major truck stop, surrounded by industrial zones.
TP: CBG that hosts a major transit agency depot.
The peak loads for distributed and managed scenarios were calculated as fractions of those under the
nameplate standard for each corresponding CBG. As shown in Figure 10, CBGs with less variety of chargers
show a small reduction from the nameplate load, while the impact of distributed and managed scenarios is
more significant for CBGs with a more diverse combination of charger types. More details can be found in
Appendix A: Peak Load Comparison by CBGs.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure 9. Charger presence in different CBG profiles. R: Residential, C: Commercial, I: Industrial, Re: Retail,
TI: Truck and industrial, TP: Transit passengers
100%
90%
Composition of Ports by Type
80%
70%
60%
50%
40%
30%
20%
10%
0%
R+C+I R+C R I+Re+R TI TP
CBG profile
HD Public MD Public Public DCFC Public L2 HD Depot MD Depot
MFH L2 SFH L2 HD Public MW Transit Depot School Depot
Figure 10. Fractions of peak loads under the distributed and managed scenarios as compared to the
nameplate standard in various CBGs
1
0.9
Fraction of Peak Loads
0.8
0.7
0.6
(Normalized to Nameplate
0.5
0.4
Standard)
0.3
0.2
0.1
0
R R+C R+C+I I+Re+R TI TP
Distributed Managed
Utility Data Gathering
To understand utility impacts and develop load allocation methodology, the project team worked with utilities
in Washington to gather data about the distribution system. System models, equipment costs, peak loading
data, engineering thresholds were collected to identify underloading or overloading, and geospatial data was
collected to understand the impact of EV charging load on the electric distribution system. A data request
guide was submitted (see
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Appendix B: Data Request Guide) to utilities to initiate data collection. The data request guide was designed
to offer guidance to utilities for what data was required/requested for the study and what format would be
appropriate for submission. Highlights of the data request guide and its relation to the project include:
Cost data for equipment and devices required for grid reinforcement was collected from participating
utilities and averaged to provide an estimate of costs applied to the anticipated system upgrades.
Asset and load data such as circuit, substation transformer, and distribution transformers collected is
required to estimate the amount of headroom available to add additional load to the system and
determine when the load will exceed the equipment ratings and require upgrade.
GIS asset and locational data is required to identify where within the census blocks the load should be
allocated.
Utility design criteria that determines equipment loading thresholds was used to identify limits for grid
devices and assets and determine when grid reinforcement is necessary.
NDAs or any other privacy concerns have been addressed during collaboration with participating
utilities to ensure utilities have the freedom to share as much information as possible to enhance the
study.
To facilitate this process, the project team also met with several utilities and discussed the project goals and
parameters to encourage participation and feedback. Through this engagement, the project team included
several utility models in the system analysis from utilities ranging in size from 9,000 to over a million customer
meters. As shown in Table 4, the project team analyzed over a thousand circuits spanning several hundred
miles across Washington through utility participation, utilizing a comprehensive source of data from which to
draw.
Table 4. Summary of utility data analyzed
Utility Number of Circuits Analyzed Software
Mason County PUD No. 1 12 Windmill
Avista 228 Synergi
Kittitas PUD No.1 12 Windmill
Seattle City Light 173 CYME
Puget Sound Energy 814 Synergi
Load and Capacity Analysis
Once utility model data was received, transformers were extracted from the model and assigned to CBGs to
create a spatial awareness between utility circuits and CBGs. The EV peak load at the CBG level was then
assigned to designated utility transformers in the same CBG. For a CBG with multiple transformers, the load
was distributed based on individual transformer capacities, as shown in
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Equation 6 . The loads by transformers were collected and then grouped by circuits to calculate the total load
added to a feeder circuit. Figure 11 illustrates the load calculation methodology.
Equation 6: Example of the load assignment to individual transformer
𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟,𝑖
𝐿𝑜𝑎𝑑 𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟,𝑖 = ∙ 𝐸𝑉 𝐿𝑜𝑎𝑑𝐶𝐵𝐺
∑𝐶𝐵𝐺 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟
Figure 11. Process for using utility models to quantify EV adoption impact
Utility Data
(Transformers
CBGs with Transformers Circuit Load Applied
Transformers and Grouped by Circuit to Utility Models
EV Load with EV Load
Census Data
(CBGs with EV
Load)
Once the per-circuit loads were identified, they were added to the system models supplied by participating
utilities. The project team extracted circuit level loading data for approximately 1,200 circuits in the state and
added additional EV load to these circuits. Depending on which software the original utility model used, the
project team utilized either Windmil, Synergi, or CYME analysis software to allocate the additional load and run
load flow studies, first identifying overloaded conductor. Figure 12 shows examples of a model output under
normal loading conditions (left) and after additional scenario load is added (right).
Figure 12. An example of load flow model under normal loading (left) vs. overloaded conductor requiring
reinforcement highlighted in red (right)
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Utilizing the substation transformer and circuit loading limits provided by the participating utilities, the project
team aggregated a standard circuit loading limit and identified circuits that exceeded that limit when
additional charging loads were added. For those overloaded circuits, the loads that exceeded their existing
capacities were aggregated to calculate the total number of new circuits and substation transformers needed
in each charging case. The loading limitations were calculated by identifying a typical substation transformer
size and a typical number of circuits that a new transformer would serve based on the supplied utility models
and standard engineering practices. The circuit limitation was calculated by dividing the transformer capacity
by the typical number of circuits. Below is a table summarizing the loading limits of circuits used to determine
new circuits required to serve the additional scenario load.
Table 5. Circuit loading limits
Circuit limitation
Circuit voltage (kV) Transformer size (MVA) Number of circuits (loading in MVA)
26.4 75 5 15
12 25 4 6.25
13.8 20 2 10
For this analysis, the project team assumed the chargers would be distributed evenly along the circuits,
because the specific location of where chargers might be installed is unknown. For some circuits, the location
of a charging station could increase required reinforcements to support the load.
1.8 Cost Estimates
Distribution System Upgrade
Following the load flow modeling, the project team conducted a thorough cost assessment at the distribution
level. This assessment was built upon cost data collected from local utilities, including necessary upgrades to
transformers, substations, and distribution circuits. Working with participating utilities and available industry
cost data, the project team calculated a per circuit average cost of $7.42 million for every new circuit, with
detailed assumptions shown in Table 6.
Table 6. Assumptions used to calculate costs per circuit for new circuit in Washington
Category Value
Average Length per Circuit 55000 ft.
Underground 15% $600/ft.
Overhead 85% $50/ft.
Switches 18 $8,100 (Unit)
Contingency 20%
Total $7,419,000
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Circuits were analyzed individually to find excess EV load based on their configuration. Excess EV load was
summed to the utility level. Circuit and substation transformer counts were calculated from the utility's excess
EV load based on that utility's configurations. Utility configurations correspond to specific costs that were
used to calculate the costs for new circuit buildout and additional substation transformers. The average costs
are shown in Table 7. Finally, circuit buildout and substation transformers are summed to calculate the total
distribution upgrade costs, at utility level.
Table 7. Average costs per additional substation transformer required
Circuit Voltage (kV) Transformer size (MVA) Cost
26.4 75 $ 9,000,000
12 25 $ 6,500,000
13.8 20 $ 5,000,000
Utility data was not available in all of Washington’s CBGs. Filling in these data gaps required the project team
to develop a methodology to estimate distribution upgrade costs at the CBG level. The methodology created
first took utility level total upgrade costs and distributed those costs to the utility's respective circuits. The
per-circuit upgrade costs were then reallocated at the transformer level using a transformer percent of total
circuit transformer capacity. The total distribution upgrade costs per CBG is thus the sum of the upgrade
costs of all transformers contained in the CBG. This process is described in Equation 7.
Equation 7: Calculation of distribution upgrade costs at CBG
𝐶𝑜𝑠𝑡𝑈𝑡𝑖𝑙𝑖𝑡𝑦 × 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟,𝑖
𝐶𝑜𝑠𝑡𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟,𝑖 =
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐹𝑒𝑒𝑑𝑒𝑟𝑠 𝑖𝑛 𝑎 𝑈𝑡𝑖𝑙𝑖𝑡𝑦 𝑆𝑒𝑟𝑣𝑖𝑐𝑒 𝑇𝑒𝑟𝑟𝑖𝑡𝑜𝑟𝑦 × ∑𝐹𝑒𝑒𝑑𝑒𝑟 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟
𝐶𝑜𝑠𝑡 𝐶𝐵𝐺 = ∑ 𝐶𝑜𝑠𝑡 𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟,𝑖
𝐶𝐵𝐺
Through association analysis, the project team found that the distribution system upgrade costs at the CBG
level were well correlated with transportation peak loads, as shown later in this report. For CBGs for which
utility data were not available, the project team used the regression derived from this relationship to fill in the
gaps, and the total system distribution system upgrade costs were then aggregated up to a statewide level.
Transmission System Upgrade
The projected increase in distribution load can potentially impact the transmission system in a significant
way. Transmission lines are sometimes referred to as an “interstate highway system” for electricity, which
moves electricity more efficiently over long distances from power sources to large industries or transmission
substations where the voltage is reduced, and the power is distributed to homes and businesses. In the state
of Washington, PSE21 oversees over 2,700 miles of transmission lines and 353 substations and SCL22 owns 653
circuit miles of high-voltage transmission lines (typically 230,000, or 115,000 volts). While there are other
smaller utilities in Washington that manage or operate their own transmission system, the majority of the
Puget Sound Energy, Transmission Services. Available at: https://www.pse.com/en/pages/transmission
21
22
Seattle City Light, Transmission Services. Available at: https://seattle.gov/city-light/about-us/working-with-
us/transmission-services
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
other high-voltage transmission in Washington is owned and operated by the Bonneville Power Administration
(BPA), with over 15,000 miles of transmission lines across the Pacific Northwest region. 23
Adding new transmission capacity is a complicated process and can require a lead-time of up to a decade.
Because transmission systems often cross state borders, they require strategic planning and coordination
beyond the state level. Jurisdictional and non-jurisdictional entities in the Pacific Northwest and
Intermountain West have formed a single transmission planning association, NorthernGrid,24 to facilitate
transmission planning and compliance with the Federal Energy Regulatory Commission (FERC) requirements
across the region. BPA and major IOUs and COUs in Washington are active members of NorthernGrid, and the
UTC and Commerce are members of the Enrolled Parties and States Committee.
To fully grasp the impact of EV adoption on the transmission system, extensive modeling across multiple
jurisdictions and states will be required. Since no relevant data was available from participating utilities
through the development of WUSCIA, only a high-level cost estimation for transmission system upgrades has
been included. The project team assumed the capital costs to build out the transmission system are
somewhat proportional to that of the distribution system, based on a recent study that was published by the
University of Texas at Austin.25 This study, Trends in Transmission, Distribution, and Administration Costs for
U.S. Investor Owned Electric Utilities, applied more than 200 project records reported by the FERC and
isolated costs associated with each step in the energy delivery process. The costs for distribution,
transmission, and administration are all linearly correlated to the number of customers in a utility’s territory.
The unit costs for transmission and distribution systems derived from this study are summarized in Table 8
and the capital cost to build out the transmission system26 is roughly 40% that of the distribution system.
Table 8. Unit costs for transmission and distribution systems
Category Transmission, $/Customer-Year Distribution, $/Customer-Year
Capital $75 $189
Operation & Maintenance $45 $102
Total Cost $120 $291
To verify this correlation, the project team also explored the latest Annual Energy Outlook (AEO2023) by the
U.S. Energy Information Administration (EIA).27 In the latest AEO projection of power sector trends, as shown in
Figure 13, electricity prices have been broken down by service categories, including generation, transmission,
and distribution. The contributions from transmission and distribution remain steady, with transmission being
approximately half of the distribution.
23
Bonneville Power Administration, Transmission Services. Available at: https://www.bpa.gov/energy-and-
services/transmission
24
NorthernGrid, Purpose. Available at: https://www.northerngrid.net/northerngrid/purpose/
25
Fares, L., Robert, King, Carey W., “Trends in Transmission, Distribution, and Administration Costs for U.S. Investor Owned
Electric Utilities,” White Paper UTEI/2016-06-1, 2016. Available at http://energy.utexas.edu/the-full-cost-of-electricity-fce/
26
Transmission capital costs include the cost of land and land use rights, substation equipment, transmission towers,
conductors, and several other capital costs associated with transmission.
27
Annual Energy Outlook 2023, Table 8: Electricity Supply, Disposition, Prices, and Emissions, available at:
https://www.eia.gov/outlooks/aeo/data/browser/#/?id=8-AEO2023®ion=0-
0&cases=ref2023&start=2021&end=2050&f=A&linechart=&sourcekey=0
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Assuming electricity prices are proportional to the capital expenditure to build out this infrastructure, the
proportion between transmission and distribution shown in the AEO2023 projection is quite consistent with
the cost study discussed earlier. Therefore, the project team applied an adjustment factor of 0.4 to account
for transmission system upgrade costs. Similarly, the system operation and maintenance costs up to 2050
were also estimated based on the capital costs using the relationship derived from Table 8.
Figure 13. Composition of electricity price by service category: transmission, and distribution
7
6
Electricity Price
5
4
(2022 cents/kWh)
3
2
1
0
Calendar Year
Transmission Distribution
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Results and Findings
1.9 Load Impact from Transportation Electrification
Using the given methodology, the peak EV load in each CBG across the three charging cases was calculated.
By comparing the nameplate standard in Figure 14 with the other two charging scenarios as shown in Figure 15
and Figure 16, the peak loads in the managed scenario are typically around 70-80% of those of the nameplate,
while the peak loads for the distributed scenario are typically round 90-95% of the nameplate peaks. As
expected, the areas with high EV charging loads are the ones with the most chargers or more high-powered
chargers. In particular, locations with MD and HD public charging show up as the highest load CBGs, as well as
those with transit depots or high numbers of MD and HD depot chargers. Additionally, high-population CBGs
in urban cores like Seattle, Vancouver, and Spokane also show high loading from residential or multifamily
charging.
Figure 14. Peak charging load in each census block group for the nameplate standard
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure 15. Peak charging load in each census block group for the distributed scenario
Figure 16. Peak charging load in each census block group for the managed scenario
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
1.10 Circuit and Transformer Overload
There were approximately 1,200 circuits analyzed through utility modeling. The service territories covered by
these circuits are home to roughly 47% of Washington’s population. Based on circuit and substation
transformer limitations, as shown in Figure 17, load flow analysis showed existing circuits overloaded by 67% at
nameplate, 61% at distributed and 52% at managed scenario loads. Depending on the excess loads by each
charging case, correcting the overload will require increasing the number of circuits by 70% at nameplate,
60% at distributed, and 40% at managed scenarios. Thus, managed scenarios require fewer upgrades per
overload compared to nameplate or distributed scenarios. The total capacity upgrades of Washington’s
distribution grids due to transportation electrification under the nameplate standard, distributed scenario, and
managed scenario are 7.0 GW, 5.8 GW, and 4.1 GW, respectively.
Figure 17. Percentage of overloaded circuits by charging case
Managed
Distributed
Nameplate
0% 10% 20% 30% 40% 50% 60% 70% 80%
The number of substation transformers and new circuits required to serve the load was calculated based on
the percentage of overloading on each circuit, based on the input from participating utilities and standard
engineering practices. Figure 18 summarizes the number of new circuits and substation transformers required
to serve the load based on the scenario.
Figure 18. Number of substation transformers and new circuits required to serve loads by cases
900 841
Number of Additional Service
800 725
700
600
485
500
400
263 234
300 167
200
100
0
Nameplate Distributed Managed
Total Transformers Total Circuits
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
The total costs to upgrade the distribution grid were summarized at the utility level. On average, the costs to
upgrade under nameplate standard were almost two times higher than distributed, and the distributed
scenario was over one and a half times higher than managed. The same trends were observed at the average
distribution system upgrade cost per circuit allocated to the system, as shown in Figure 19.
Figure 19. Average upgrade costs per circuit by charging scenario
Managed $128,521
Distributed $211,312
Nameplate $402,416
$0 $100,000 $200,000 $300,000 $400,000
Since there are CBGs for which utility data were not available, correlation between distribution upgrade costs
and peak loads for transportation load at CBG level were used to derive stand-in estimates. The correlation
between the two variables based on available utility data is shown in Figure 20.
Figure 20. Correlation between distribution upgrade costs at CBG level vs. the charging peaks from EV
loads
$100,000,000
Distribution Upgrade Costs ($)
$10,000,000
$1,000,000
$100,000
$10,000
$1,000
$100
100 1000 10000 100000 1000000
EV Charging Peak Loads (kW)
Distribution Costs ($) Fitted Result
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Each charging case that was studied corresponded to one cost scenario: the nameplate standard represents
the high-cost scenario for upgrading all utility-side charging infrastructure, the distributed and managed
scenarios correspond to the mid-cost and low-cost scenarios, respectively. Table 9 summarizes the total
costs to upgrade the distribution system for utilities that provided their load flow models, as well as the fitted
statewide total costs after applying the above correlation.
Table 9. Fitted statewide total distribution system upgrade costs by charging cases and corresponding
cost scenarios
Calculated Total Costs
Corresponding Cost Fitted Statewide Total
Charging Case Based on Utility-
Scenario Costs
Provided Data
Nameplate High $5.46 Billion $11.66 Billion
Distributed Mid $4.46 Billion $10.37 Billion
Managed Low $3.01 Billion $7.95 Billion
The project team then used the relationship presented in Table 8 to calculate the total costs across the state.
The results shown in Figure 21 include all costs associated with planning and installation activities up to the
year 2035, as well as the maintenance and operation (M&O) costs anticipated through 2050. The three cost
scenarios are summarized in Figure 21.
Figure 21. Statewide high-, mid-, and low-cost scenarios associated with utility-side infrastructure
upgrades to support transportation electrification
$30
$25
2.78
Total Costs ($ billion)
2.47
$20 4.63
4.12
1.89
$15 6.29
5.60 3.15
$10 4.29
11.66 10.37
$5
7.95
$0
High-Cost Scenario Mid-Cost Scenario Low-Cost Scenario
Distribution System Capital Distribution System M&O
Transmission System Capital Transmission System M&O
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Discussion
Transportation electrification is critical to achieving Washington’s emissions reduction goals. To facilitate this
transition, the WUSCIA serves to better understand the financial impact of the grid upgrades it necessitates.
The circuit-level profile from this study can also assist utilities in identifying overloaded circuits and
prioritizing distribution planning, which may help reduce costs if implemented carefully. The WUSCIA has
estimated the total costs to upgrade the statewide distribution grid is approximately $10.4 billion dollars
(mid-cost scenario), assuming charging activities will be mostly driven by existing driving patterns. Moreover,
the implementation of managed charging programs and policies to incentivize off-peak charging can further
reduce this cost by almost a quarter (low-cost scenario).
Utility Practices
A key takeaway of the WUSCIA is that using the nameplate standard to estimate upgrading costs leaves
utilities with an upper-bound estimation far higher than what is required to serve customer demand. The
nameplate standard assumes that residential, commercial, and fleet charging all occur simultaneously and will
have coinciding peak charging periods. In reality, while residential charging peaks between 5 p.m. and 11 p.m.
commercial and fleet charging patterns can vary. For instance, school and transit buses are usually charged
during business hours or overnight. In addition to coinciding peaks, the nameplate standard assumes a
maximum charging load from all vehicles being consistently charged during the same peak period across each
category. Average daily travel in the United States is estimated to be between 20 to 30 miles, whereas most
available battery electric vehicles offer ranges between 110 and 300 miles, indicating that most drivers will not
need to charge their vehicles on a daily basis.28 By taking a worst-case scenario approach that assumes a
maximum charging load, the nameplate standard vastly overestimates electric demand, and therefore, the
cost of upgrading grid infrastructure to support this demand. Based on the analysis, the costs associated with
upgrading circuits alone under the nameplate scenario could be 90% to 220% greater than in other scenarios.
This work also highlights the importance of managed charging. Prior to WUSCIA, many utilities have launched
pilot programs for fleet electrification and charging to gain customers insights that will guide future strategy
design for managing load increases. These programs focus on load management through demand response
and other incentive-based strategies. That said, workplace and public charging are considered essential for
relieving the burden from at-home charging during evening peak hours and providing access to drivers
without home charging. In the future, utilities may also work with MHD fleets to explore possibilities to
encourage off-peak charging for trucks and buses.
Accounting for vehicle class differences as they relate to charging demand is also critical to effectively
addressing load increases in future grid planning. Though the cumulative system load from LDVs is much
higher than that of the MHD sector, this load is also well distributed across most of the state’s electrical
infrastructure. When new LDVs are added to the grid, the increase in demand usually does not necessitate
any major upgrades and can sometimes be absorbed by residential and small-scale generation, such as solar
photovoltaic. On the other hand, MHD load tends to be concentrated in fewer CBGs, primarily along trucking
corridors and major transit routes. This concentration effect, along with MHD chargers having higher rated
capacities, leads to much higher energy demand.
28
At a Glance: Electric Vehicles, Department of Energy, 2023. Available at:
https://afdc.energy.gov/files/u/publication/electric-drive_vehicles.pdf
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
In turn, the MHD charging demand increases the likelihood of upgrades being needed in the distribution
system, including upgrading an existing substation or adding a new one. LDV charging typically uses L1 or L2
chargers, which have ranges at or below 19.2 kW. On average, CBGs in Washington have around 1,600
residents. If half the residents purchase an EV and install a L2 kW at-home charger, the additional load to the
grid is about 15 MW per CBG, which may necessitate a substation upgrade or new addition that could take
anywhere between $3 million to $35 million dollars.29 In a populated residential area, this may be an extreme
high-usage case as normally L2 residential chargers are installed at much lower density. A HD truck stop with
15 trucks using MW chargers all at once requires the same amount of additional capacity. The latter scenario is
more likely to occur due to the nature of truck operations and the design blueprint of MHD charging hubs, and
could therefore trigger more substantial grid upgrades than residential charging.
Utilities must also consider investing in infrastructure upgrades soon because of extended project lead times.
Substation upgrades can take over a year, whereas a substation addition can take anywhere from 2-4 years
and transmission can take up to a decade. If utilities hope to timely comply with state regulations related to
MHD fleets, infrastructure upgrade planning should receive prompt attention. This applies particularly to cases
involving land siting for new installations, which tend to have the longest lead times. Since land siting and
purchasing is often done by service providers depending on installation type, identifying and building out
these cross-collaborations and partnerships should also be emphasized. On the customer side, make-ready
programs across the U.S. have proven efficient and effective to install EVSEs for residential and commercial
customers. Similar streamlined practices should be considered for utility-side infrastructure upgrade.
Financial Impact
An important question when planning for grid upgrades is how investments will impact ratepayers. Because of
how regulated utilities are structured, costs resulting from improvements in service may be borne largely by
ratepayers through higher electricity bills. If not managed properly, EVSE investments could pose a
considerable burden on ratepayers and the broader economy as EVSE-related infrastructural development
scales. Opportunities are available to utilities to mitigate some of this burden. Significant (more than 30%)
cost reduction was observed for this study under the statewide low-cost scenarios, assuming a large-scale
implementation of managed charging programs. Such efforts will make the overall impact on ratepayers more
manageable and justifiable given the long-term benefits. Several state agencies and utilities are exploring
these strategies through pilot programs, laying the foundation for future improvements based on data-driven
insights. For example, in 2017, the UTC issued a policy and interpretive statement regarding the regulation of
electric vehicle charging stations. This policy strongly encourages measures such as time-of-use or dynamic
pricing to promote off-peak charging.30 Since then, PSE launched its Flex EV program in 2023, which allows EV
29
National Renewable Energy Laboratory (NREL), Perspectives on Charging Medium- and Heavy-Duty Electric Vehicles,
2021. Available at: https://research-hub.nrel.gov/en/publications/perspectives-on-charging-medium-and-heavy-duty-
electric-vehicles
30
Washington Utilities and Transportation Commission, Policy and Interpretive Statement Concerning Commission
Regulation of Electric Vehicle Charging Services, 2017. Available at:
https://apiproxy.utc.wa.gov/cases/GetDocument?docID=147&year=2016&docketNumber=160799
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
owners to adjust their charging schedules during high demand periods.31 Clark Public Utilities implemented the
Electric Vehicle Managed Charging Program to manage electric load and optimize grid efficiency.32
The eventual impact on individual ratepayers will vary greatly depending on the investments made by each
individual utility to integrate and serve EV load. Utilities can mitigate ratepayer impacts by promoting policies
and incentives to move EV charging off-peak, such as managed charging, and by investing in EV infrastructure
in a manner that is roughly commensurate with the anticipated revenue EV charging will generate. It is also
noteworthy that the electric utility grid investments discussed in this study are long-term investments that
will be paid over 30 years through utility rates. Some of these investments can be incorporated into regular
grid improvement and maintenance. For example, PSE reported in 2022 that approximately $3.1 billion was
spent on reliability and service upgrades over a four-year period.33
Another way to relieve burdens related to infrastructure upgrade is the integration of distributed energy
resources (DER). Utility operations in Washington are driven by two main regulations. CETA, passed in 2019,
requires all utilities to eliminate carbon emissions from their energy resources by 2045. 34 It includes a
requirement to ending use of coal-fired power generation after 2025 and achieving carbon neutrality by
2030. The Energy Efficiency Resource Standard (EERS) is another mandatory standard that requires qualifying
utilities to meet some portion of their electricity demand through energy efficiency.35 As such, current utility
planning revolves around integrating more DERs, with a particular focus on residential and commercial solar in
Washington and meeting the state’s increasing electricity demand by augmenting pre-established practices
related to energy efficiency. Due to limited DER-related information during the development of WUSCIA, DER
forecasting was not accounted for in utility load flow modeling. As the adoption of distributed energy
resources such as residential and commercial solar, battery energy storage systems (BESS), and wind
generation, the availability of generation on the distribution grid will increase and can be utilized to provide
load relief when those resources are operating. Utilities could also leverage virtual power plants (VPPs) to
create a network of medium-scale power units, supporting overall distribution and transmission planning.36 A
Department of Energy study suggests that deploying 80 to 160 GW of VPPs by 2030 could enhance grid
capacity for rapid electrification, reduce reliance on peaking power plants, and lower overall grid costs.37
In addition, state and public agencies in Washington could secure federal funding and leverage incentive
programs or private investment to offset these costs. For instance, as part of the Bipartisan Infrastructure Law,
$10.5 billion is available through the Grid Resilience and Innovation Partnerships (GRIP) Program to enhance
31
Puget Sound Energy, Flex EV. Available at: https://www.pse.com/en/rebates/PSE-flex/flex-ev
32
Clark Public Utilities, Electric Vehicle Managed Charging Program. Available at:
https://www.clarkpublicutilities.com/residential-customers/reduce-energy-waste-and-lower-your-bill/all-rebates-
incentives-and-low-interest-loans/electric-vehicle-managed-charging-program/
33
Puget Sound Energy, Puget Sound Energy Files Three-year Rate Proposal, 2022. Available at:
https://www.pse.com/en/press-release/details/Puget-Sound-Energy-files-three-year-rate-proposal
34
Washington Utilities and Transportation Commission, Clean Energy Transformation Act. Available at:
https://www.utc.wa.gov/regulated-industries/utilities/energy/conservation-and-renewable-energy-overview/clean-
energy-transformation-act
35
Washington State Legislature, RCW 19.285.040: Energy Conservation and Renewable Energy Targets. Available at:
https://app.leg.wa.gov/RCW/default.aspx?cite=19.285.040
36
Evergreen Collaborative, Five Ways States Can Unlock Virtual Power Plants for Grid Flexibility and Decarbonization, 2024.
Available at: https://collaborative.evergreenaction.com/memos/five-ways-states-can-unlock-virtual-power-plants-for-
grid-flexibility-and-decarbonization
37
U.S. Department of Energy, The Pathway to: Virtual Power Plants Commercial Liftoff, 2023. Available at:
https://liftoff.energy.gov/vpp/
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
grid flexibility and improve the resilience of the power system against growing threats of extreme weather and
climate change.38 The Title 17 Clean Energy Financing Program is also available for transmission developers to
provide efficient electrical generation, transmission, and distribution technology. Industrial and large
commercial customers are expected to contribute more than residential customers, particularly those with
low incomes. Payments from the Climate Commitment Act (CCA) could be reinvested in communities to help
ease financial burdens for low- and medium-income households. This market-based cap-and-invest program
requires the state's largest polluters to reduce GHG emissions. The CCA is already expanding the state’s
weatherization program for low-income families to improve energy efficiency and reduce utility bills and
providing $200 electric utility credits to eligible households in a separate program.39
While the costs associated with utility infrastructure upgrades may seem substantial, the return on
investment from transportation electrification cannot be neglected. Electrifying Washington’s trucks alone is
expected to result in $1.3 billion in health-related savings and $2.4 billion in annual net societal benefits
stemming from reduced emissions, improved public health, and fuel savings.40 By 2050, net societal benefits
could amount to $24.9 billion, cumulatively. Moreover, populations living closer to heavy traffic roadways and
having exposure to mobile source emissions experience a disproportionate share of environmental health
burdens. 41 The statewide transportation goal will especially benefit residents in the overburdened
communities. Customers directly affected by these upgrades will also benefit from lower driving costs with
EVs. For instance, a battery electric vehicle in Washington can save $0.16 per mile, totaling over $1,000
annually for an average driver.42 The Washington State Energy Strategy also projects that strong electrification
and efficiency improvements could save the average energy customer about $132 annually by 2050. 43
Finally, the cost estimates focused on the transportation sector, while the factors that drive utility-side
infrastructure upgrades are more complicated. The AEO2023 projected that the transportation sector will
only account for 3% of the total electricity sales in the US by 2035, and most of the demand will be driven by
the industrial, commercial and residential sectors. Therefore, the actual incremental need for generation and
capital upgrades will be impacted by electrification activities in other sectors. It is critical for the state to
consider the aggregated impact from all activities when planning for transportation electrification.
The WUSCIA is structured to facilitate and support the involvement of local electric utilities in EVSE-related
grid upgrade planning. The insights garnered from these engagements are intended to guide policymakers,
including entities such as the Governor’s Office, the State Legislature, the Department of Commerce, and the
Utilities and Transportation Commission, on the allocation of resources for the necessary buildout and
maintenance of EV infrastructure. By equipping these entities with robust and actionable data, the WUSCIA
aims to align long-term transportation electrification with the state’s sustainability goals.
38
Grid Deployment Office, Grid Resilience and Innovation Partnerships (GRIP) Program. Available at:
https://www.energy.gov/gdo/grid-resilience-and-innovation-partnerships-grip-program
39
Washington Climate Action, Climate Commitment Act: Polluters Pay, Communities Benefit. Available at:
https://climate.wa.gov/washington-climate-action-work/climate-commitment-act-polluters-pay-communities-benefit
40
What the Advanced Clean Truck Rule Will Do for Washington, Union of Concerned Scientists, 2021. Available at:
https://www.ucsusa.org/sites/default/files/2021-12/wa-clean-trucks-fact-sheet.pdf
41
Washington State Department of Health, Washington Environmental Health Disparities Map. Available at:
https://doh.wa.gov/data-and-statistical-reports/washington-tracking-network-wtn/washington-environmental-health-
disparities-map
42
U.S. Department of Energy, Local Fuel Savings. Available at: https://www.energy.gov/local-fuel-savings
43
Washington State Department of Commerce, Washington State Energy Strategy, 2021. Available at:
https://www.commerce.wa.gov/energy-policy/state-energy-strategy/
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Appendix A: Peak Load Comparison by CBGs
Six CBG profiles were selected to display how charger type contributes to the overall load at the peak hour
(20 h) within the distributed scenario and managed scenarios.
Figure A1 — residential profile
1
0.9
0.8
0.7
Charger presence
School Depot
0.6
0.5 SFH L2
0.4 MFH L2
0.3 Public L2
0.2
Public DCFC
0.1
0
Nameplate Distributed Managed
R
Figure A2 — residential and commercial profile
1
0.9
0.8
0.7
Charger presence
SFH L2
0.6
MFH L2
0.5 MD Depot
0.4 HD Depot
0.3 Public L2
Public DCFC
0.2
MD Public
0.1
0
Nameplate Distributed Managed
R+C
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure A3 — residential, commercial, and industrial profile
1
0.9
0.8
0.7 SFH L2
Charger presence
0.6 MFH L2
MD Depot
0.5
HD Depot
0.4
Public L2
0.3 Public DCFC
0.2 MD Public
0.1 HD Public
0
Nameplate Distributed Managed
R+C+I
Figure A4 — industrial, retail, and residential profile
1
0.9
0.8
0.7 SFH L2
Charger presence
0.6 MFH L2
MD Depot
0.5
HD Depot
0.4
Public L2
0.3 Public DCFC
0.2 MD Public
0.1 HD Public
0
Nameplate Distributed Managed
I + Re + R
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Figure A5 — Truck hotspot profile
1
0.9
0.8
0.7
Charger presence
HD Public MW
0.6 SFH L2
0.5 MFH L2
0.4 MD Depot
HD Depot
0.3
Public DCFC
0.2
MD Public
0.1
0
Nameplate Distributed Managed
TI
Figure A6 — Major transit agency depot profile
1
0.9
0.8
0.7
Charger presence
Transit Depot
0.6 SFH L2
0.5 MFH L2
MD Depot
0.4
HD Depot
0.3
Public L2
0.2 Public DCFC
0.1
0
Nameplate Distributed Managed
TP
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
Appendix B: Data Request Guide
1.11 Project Overview
To fulfill statewide clean transportation and climate goals, the Interagency Electric Vehicle Coordinating
Council (EV Council), jointly led by the Washington State Department of Commerce (Commerce) and the
Washington State Department of Transportation (WSDOT), developed the State's Transportation
Electrification Strategy (TES) for the period up to 2035 (as outlined in RCW 43.392.040). This strategy
involves a thorough evaluation of the state's infrastructure requirements, including electric vehicle supply
equipment (EVSE), to accommodate the expected increase in zero-emission vehicles (ZEVs) on the roads
over the coming decade. According to the final TES published in November 2023, under the Strong
Electrification Policy scenario, the State of Washington requires more than 3 million charging ports by 2035
generating an evening peak load of 3.4 GW.
Given the substantial increase in load demand from the accelerated deployment of EV charging infrastructure,
significant upgrades to the electrical infrastructure are inevitable on both the customer and utility sides of the
meter. The Washington Utility-Side Charging Infrastructure Assessment (WUSCIA) is a strategic initiative
designed to provide a comprehensive estimation of the net present value costs associated with EVSE-related
infrastructure on the utility side of the meter. The WUSCIA focuses on projecting costs for planning and
installation activities such as adding new distribution circuits, augmenting transformers to handle higher loads,
and expanding or modernizing distribution substations for increased capacity, up to the year 2035.
Additionally, it extends to evaluating the operational and maintenance costs anticipated through 2050. A key
aspect of WUSCIA is to analyze the potential financial impacts on a diverse set of stakeholders, including
utilities, ratepayers, electric vehicle service providers (EVSPs), and their customers. The outcomes of this
project also aim to serve as the foundation to support an evidence-based decision-making process for
funding necessary infrastructure buildout and maintenance for the State of Washington.
1.12 Utility Data Request
A critical component of the WUSCIA evaluation is to understand the typical costs associated with planning
and installation activities and current assets and load information. Current load data will be combined with EV
charging load projected by TES at Census Block Group (CBG) level to estimate the upgrades needed to
support the statewide transportation electrification efforts. The project team, led by Commerce and the ICF
consultant team, would like to invite utilities across the State to participate in this project to inform the
development of WUSCIA. Participation of utilities will ensure that the evaluation can best reflect the EVSE-
related grid upgrade needs for the State, and to support utility planning efforts in the next decade.
There are two types of data that the project team is requesting from the participating utilities: equipment
costs and asset and load data, and the project team will try to accommodate different data sharing policies of
each individual utilities throughout the process. As detailed in the Data Privacy, Sharing, and Purging section
below, data shared by utilities will be labeled as Proprietary Information, accessible to the ICF consultant team
only, and not be subject to the State of Washington Public Records Request.
When utilities submit cost data for equipment, the values can be directly input into a workbook that will be
provided by the consultant team or can be submitted in existing file formats such as
spreadsheets/workbooks or standards documentation used as reference when pricing system reinforcements
and providing new service if that is more efficient. ICF will be able to extract data from multiple sources for
aggregation purposes. Details of equipment cost data sharing instructions can be found in the Equipment
Cost Data section. If pricing data is not readily available or the collection of said data would result in an
©ICF 2021 41
Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
excessive time or resource commitment, ICF will aggregate available pricing from other Washington state
utilities and/or market data to estimate costs.
Utilities are also asked to provide asset data that identifies equipment at its spatial location in the field. We
must know the spatial location so that the transportation load data can be tied to Census block groups.
Utilities will also need to provide a load profile for each feeder/circuit on the day that feeder/circuit hits its
peak load. More details are available in the Asset and Load Data section.
ICF will work with each participating utility to answer questions and provide support for data collection in an
effort to obtain and parse the data efficiently and with minimal impact on the utility.
Data Requested
Equipment cost data with loaded costs identified (categories and instructions included in the
Equipment Cost Sheet)
o Transformers, conductors, transmission, substation, DMS, other devices, and long-term costs
Asset and load data
o Circuit level 15-minute interval SCADA data (including load and power factor) for circuit peak
day (24 hours)
o GIS (geographic information system) asset data for all circuits (additional discussion can be
found in the GIS Data section of this guide)
o Utility Boundaries (preferably in a vector polygon GIS file)
o Standard circuit capacity limitations at feeder head (loading and power factor)
o Substation transformer loading capacity with ID corresponding to GIS data
o If available, aggregated circuit level DER capacity at nameplate. (If available, individual DER 15-
minute export data.)
o Hosting capacity maps/analysis (if available)
Data Privacy, Sharing, and Purging
If needed, ICF will work with utilities to establish a non-disclosure agreement (NDA), which will be signed by
both parties (ICF and the affected utility) to protect unauthorized data dissemination and outline restrictions
on use of utilities data. Raw data collected from utilities will be stored on a secured Microsoft Teams site, set
up by the ICF Information Security team. Each participating utility will receive a distinct link that will point to
the folder to upload their data directly (the folder will only be accessible to the designated utility and the ICF
consultant team). The unprocessed data will be stored only on the ICF domain and available to ICF consultant
team members only, and not be shared with any outside parties, including Commerce. Any data shared under
an NDA will be treated as proprietary information and not be subject to the State of Washington Public
Records Request. Data collected from utilities will be purged and removed from the ICF site six months after
the project close-out (expected December 2024).
Project Timeline
The initial data request will go out to utilities in April 2024. ICF expects to receive final confirmation from
utilities whether they would participate in this project by the end of April. Over the course of May-June 2024,
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
ICF will work with utilities to acquire and parse the required data. Data processing and analysis are expected
to take place starting late June 2024, and the initial draft report will be available late July 2024.
April 2024 April - May 2024 May - June 2024 June - July 2024
Utilities to Upload Costs
ICF to Provide Inforamtion (either as ICF to Categorize Costs
Equipment Cost Sheet the workbook or utilities Data and Develop
and Instructions preferred format) to the Three Costs Scenarios
Utilities to Confirm Secured Folder
Participation; ICF to
Initiate NDA Process
with Utilities ICF to Parse and
ICF to Confirm Utilities to Upload Asset
Process Load Data and
Availability and Format and Load Data (in .csv
to Apply Transportation
of Utilities Asset and or geodatabases) to the
Load from TES to
Load Data Secured Folder
Utilities Data
1.13 Equipment Cost Data
As part of resource planning and cost assessment, ICF understands that each utility calculates operation,
maintenance, and reinforcement costs differently. When compiling cost estimates for new services, utilities
may include labor, expected maintenance, operating costs, or any combination of those categories folded into
the per unit cost of equipment. When submitting the cost data, please indicate what costs are included in the
per-unit or per-foot costs and include any maintenance, operating, or labor costs that are not included.
Additionally, please indicate annual and lifetime costs for maintenance and operations. The Long-Term Costs
tab in the Equipment Cost Sheet can be used to discuss these costs and describe equipment cost
methodology if salient. If pricing data is not readily available, ICF will aggregate available pricing from other
Washington state utilities and/or market data to estimate costs.
Each equipment tab has section to indicate what costs are included in the per unit cost of the equipment
with a pull-down check box option as illustrated below:
What costs are included in the per unit equipment costs?
Please check all that apply
Maintenance
Operation
Labor
Other (Please describe other costs below)
1.14 Asset and Load Data
When creating data sets for GIS data, it is preferred the data is processed to CSV files or geodatabases. A
consistent file type will help mitigate data parsing and data extraction issues and increase efficiency. If it is
not possible to extract data in the form of a CSV or geodatabase, an alternative data type would be an Excel
spreadsheet or distribution model such as CYME, Synergi, or Windmil. If all the data is not available, or not all
the equipment listed below is modeled in the GIS database, ICF can make assumptions based on aggregated
data from other Washington State utilities as well as standard industry practice when appropriate. ICF can
assist in GIS data collection in order to minimize the impact of the request.
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Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
The following equipment list represents the optimal data we aim to receive. The ICF team prefers a
comprehensive data submission of the distribution system to ensure the data is complete. For substation
data, ICF understands that the substation may not be modeled in the GIS system. If that is the case, the
circuit origin location will be adequate.
Once the initial data request has been fulfilled and processed successfully ICF, with input from each utility
participating, will identify high value feeders for more in-depth load flow analysis. ICF will request a distribution
model, such as CYME, Synergi, or Windmil for that feeder’s peak load. These high value feeders will be used to
assess the accuracy of the methodology as well as make refinements.
Transformers: • Voltage
• Transformer ID • Circuit ID
• Feeder/ Circuit ID • Status (open/closed)
• Size kVA • Latitude/Longitude
• Phase Switches:
• # of customers • Switch ID
• Customer type (residential, commercial, or • Voltage
mixed) • Phase
• Latitude/Longitude • Circuit ID
Conductors: • Status (open/closed)
• Conductor size • Latitude/Longitude
• Conductor capacity (preferred but not • Type: (UG, PTS, Multi-way, etc)
required) Voltage regulators:
• Phase • Regulator ID
• Feeder/ Circuit ID • Regulator size
• Latitude (segment start/end) • Voltage
• Longitude (segment start/end) • Phase
Substations and Circuits: • Feeder/ Circuit ID
• Substation ID • Latitude/Longitude
• Substation transformer ID Capacitors:
• Substation transformer capacity (mVA) • Capacitor ID
• Connected circuit(s) ID • Capacitor size
• Latitude/Longitude • Voltage
Distributed Energy Resource (DER) (if available) • Phase
• DER and Circuit ID • Feeder/ Circuit ID
• Voltage • Latitude/Longitude
• Inverter size Transmission (if applicable)
• Type (solar, BESS, combo, etc) • Conductor size
• Feeder/Circuit ID
Reclosers • Latitude (segment start/end)
• Recloser ID • Longitude (segment start/end)
©ICF 2021 44
Washington Utility-Side Charging Infrastructure Assessment (WUSCIA)
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