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CITY LIGHT 2020 INTEGRATED RESOURCE PLAN: DEMAND FORECAST DEEP-DIVE & SCENARIO DISCUSSION
| 2| 2| 2| 2
HIGH-LEVEL INTEGRATED RESOURCE PLAN TIMELINE
IRP Draft review and
updates
2020 Plan presented to City Council
Creating the framework
Conduct Analysis
10/24/2017 1/16/2018 3/7/2018 5/2/2018
Q3/Q4
2019
Q4 2019/
Q1 2020Q1/Q2
2020
Q3
2020
Demand
Forecast &
Scenarios
(12/13)
Portfolio Results &
Review Draft
Recommendations
(April/May)
IRP
Process &
Scenarios
(1/10)
Resource
Adequacy
& Climate
Change
(Feb)
Review
scenarios
and
Portfolios
(March)
| 3| 3| 3| 3
GOALS OF DEEP DIVE
1 Understand the Baseline Demand Forecast
2 Discussion on scenario planning
- Methodology overview
- Walkthrough baseline forecast results
- What alternative futures to consider
- Crafting demand scenarios with some illustrative examples
- How to prioritize future development work
Methodology Overview
| 5| 5| 5| 5
Why did we move from econometric to
end-use based demand forecasting?
| 6| 6| 6| 6
End-Use Forecast
Adjustments
System forecast
for IRP
Residential & Commercial delivered sales that includes: economic
drivers, stock turnover, codes & standard and naturally occurring
efficiency
Industrial, electric vehicles, distributed generation & large transit
electrification but no programmatic efficiency
Losses + Own
UseGross up from energy delivered at the meter to delivered at the system
Annual system load which requires additional shaping
| 7| 7| 7| 7
Core Loads
EVs
DG
Spot Load
New Residential
Cooling
An
nu
al
aM
W
Fo
recast
s
Shaping
Models
(Monthly,
Hourly)
System
Forecasts for
IRP
Weather SensitiveB
roken
ou
t o
f
en
d-u
se m
od
el
Weath
er
sen
siti
ve
ho
url
y f
ore
cast
s
SHAPING ANNUAL TO HOURLY
| 8| 8| 8| 8
DEMAND FORECAST DEVELOPMENT WORK
Leverage more City Light specific data to better
calibrate end-use model
Reflect new state and city legislation
Incorporate load shape impacts from changes in end-
use saturations
1
3
2
Baseline Forecast
| 10| 10| 10| 10
End-Use Forecast (Annual aMW)
| 11| 11| 11| 11
BASE YEAR (2019) DELIVERED LOAD BY CUSTOMER CLASS & SEGMENT
58
6 a
MW
34
8 a
MW
Commercial Residential
| 12| 12| 12| 12
BASE YEAR (2019) DELIVERED RESIDENTIAL LOAD BY END USE
HVAC
Plug Loads
Appliances
Water
Heating
Lighting
Oth
er
34
8 a
MW
| 13| 13| 13| 13
BASE YEAR (2019) COMMERCIAL DELIVERED LOAD BY END USE
HVAC
Lighting
58
6 a
MW
| 14| 14| 14| 14
END-USE STOCK TURNOVER EXAMPLE: RESIDENTIAL SINGLE FAMILY FREEZERS
Weighted average intensity of freezers
declines by ~10% over time with
efficient equipment replacement
| 15| 15| 15| 15
THE ECONOMY IS COOLING
*Employment & Housing Forecast based on IHS Seattle Metro economic forecast
Assume that commercial floorspace generally
moves inline with employment
~90% of new premises are multi-family
| 16| 16| 16| 16
RESIDENTIAL DELIVERED LOADS
Zoomed In
AAGR: -0.3% AAGR: +0.4%
AAGR: +0.1%
| 17| 17| 17| 17
HVAC efficiency driven by Electric
Resistance to Heat Pump conversion
Incr
ease
s Lo
ad
Decr
ease
s Lo
ad
RESIDENTIAL YEAR-OVER-YEAR CHANGES
2020 EISA lighting standard, 2014 Appliance Standards & 2015
Water Heater standards driving near-term efficiency gains
Load Decline Load Growth
| 18| 18| 18| 18
COMMERCIAL DELIVERED LOADS
Zoomed In
AAGR: +0.4% AAGR: +0.3%AAGR: -0.1%
AAGR: +0.2%
| 19| 19| 19| 19
COMMERCIAL YEAR-OVER-YEAR CHANGES
Efficiency in lighting driven by adoption of high-performance
fluorescents and EISA standards for screw-in bulbs
Incr
ease
s Lo
ad
Decr
ease
s Lo
ad
| 20| 20| 20| 20
Adjustments (Annual aMW)
| 21| 21| 21| 21
INDUSTRIAL FORECAST
2019 Industrial Sales are
down ~10% from 2018
Long-term Industrial sales
expected to decline ~0.4% per
year with manufacturing
employment
Industrial Customers
ARDAGH GLASS
ASH GROVE CEMENT
BOEING
CERTAINTEED
DARIGOLD INC
LAFARGE CORPORATION
NUCOR
PORT OF SEATTLE
STEVEDORING
VIGOR
| 22| 22| 22| 22
*From
CORE LOADS BY CUSTOMER CLASS
Residential
Commercial
Industrial
AAGR -0.1%
Zoomed Out Zoomed In
AAGR: +0.1%
AAGR: +0.3%
| 23| 23| 23| 23
ELECTRIC VEHICLES FORECAST
Same forecasts used for RMI study. We adopt BAU for the baseline forecast.
Light Duty Electric Vehicle Forecast Electric Vehicle Energy (aMW) Impact
| 24| 24| 24| 24
DISTRIBUTED GENERATION
From 2020 Cadmus Solar PV Potential Study. We adopt Extended WA Incentive for the baseline forecast.
Residential Expected Generation (aMW) Commercial Expected Generation (aMW)
| 25| 25| 25| 25
LARGE TRANSIT ELECTRIFICATION
*From
| 26| 26| 26| 26
Apply Shapings (Annual to Hourly) and
Weather Sensitivities
| 27| 27| 27| 27
Annual Forecast Component Shaping Model Description
Core Loads (RES + COM + IND)Hourly level model fit to historical system load data that
accounts for weather, day of week effects and holidays
Solar NREL System Advisor Model (SAM)
New Residential CoolingResidential building simulation model: Simplified Energy
Enthalpy Model (SEEM)
Electric Vehicles DOE EV Project data for Washington State
Large Transit Engineering studies
Weather Sensitive Shapes
Bro
ken
ou
t o
f
en
d-u
se m
od
el
| 28| 28| 28| 28
*From
TYPICAL WEEKDAY 24 HR NON-COINCIDENT LOAD SHAPES
Dual peak
winter shape
Evening peaks grow by
100 MW from EVs
Summer peaks grow by ~150
MW compared to 2020 from
increased AC saturationSingle peak
summer shape
| 29| 29| 29| 29
*From
CRITICAL WEEKDAY NON-COINCIDENT 24 HR LOAD SHAPES
New AC ~50 MW higher
on critical day
Core loads ~ 200 MW higher on
critical winter day and ~140MW
higher on critical summer day
P90 event in 2040 looks like
2020 p95 type of event200 MW increase in
critical summer loads
relative to 2020
Demand Scenarios
| 31| 31| 31| 31
What are they key themes to consider for demand scenarios?
Policies & Regulation Market Transformations
Technology Adoption Climate Change
• Taxes & incentives
• CETA, Clean Buildings Act, OSE
Benchmarking…etc
• Deep decarbonization proposals
• Equipment efficiency improvements
• Load from new end-uses
• Equipment adoption under
electrification
• Energy as a service
• Micro grids & consumer aggregators
• Large customer exits
• Which GCM scenarios to use
• Weather data coverage
• Socioeconomic impacts
What Else?
The Economy
• Will Seattle continue to boom?
• Could Seattle have a struggling
economy?
| 32| 32| 32| 32
EXAMPLE SCENARIOS
All buildings electrify with high EV adoption
New buildings electrify with high EV adoption
Sustained economic growth
Deep recession with slow recovery
Energy as a service, microgrids & customer aggregation
3
4
1
2
5
HIGH GROWTH
DEMAND
DESTRUCTIONDR
AFT
| 33| 33| 33| 33
All buildings electrify with high EV adoption:
• No new natural gas in all new construction
• Existing building stock is converted to 100% electric
• Rate of conversion is non-linear (backloaded)
o Assume high efficiency heat pump conversion for Residential
• Commercial based on existing end-use equipment assumptions
• High EV adoption scenario from RMI Study
CRAFTING THE SCENARIO: ALL BUILDINGS ELECTRIFY
WITH HIGH EV ADOPTION
1D
RA
FT
| 34| 34| 34| 34
EXAMPLE SCENARIO RESULTS
+340 aMW (+30%)
+65 aMW (+6%)
+27 aMW (+2%)
-29 aMW (-3%)DR
AFT
| 35| 35| 35| 35
HIGH-LEVEL INTEGRATED RESOURCE PLAN TIMELINE
IRP Draft review and
updates
2020 Plan presented to City Council
Creating the framework
Conduct Analysis
10/24/2017 1/16/2018 3/7/2018 5/2/2018
Q3/Q4
2019
Q4 2019/
Q1 2020Q1/Q2
2020
Q3
2020
Demand
Forecast &
Scenarios
(12/13)
Portfolio Results
& Review Draft
Recommendatio
ns (April/May)
IRP
Process &
Scenarios
(1/10)
Resource
Adequacy
& Climate
Change
(Feb)
Review
scenarios
and
Portfolios
(March)