Transcript Assessing Options for Accommodating Electric Vehicles in
POWERING EV GROWTH IN SANTA DELANO VALLEY
The Technology & Policy Group
Ash Bharatkumar, Michael Craig, Dan Cross-Call, & Michael Davidson Prepared for the USAEE Case Competition 2013 Anchorage, AK, July 29
Outline
2
Summary of challenge EV and demand growth projections BAU: Transmission and distribution expansion Alternatives Energy storage Demand response
Controlled charging
Tariff design for equitable allocation of EV costs Technology & Policy Group
The Challenge
3
Growth in electric vehicles (EVs) poses challenges for Santa Delano Electric Company (SDEC) Accommodate new electricity load Maintain affordable and reliable electricity Ensure equitable distribution system upgrade costs While encouraging growth in EV ownership Options and opportunities for a 15 year planning horizon Nissan Leaf Technology & Policy Group Tesla Roadster Images: thecarconnection.com and proetools.com
Electric Vehicle Projections
4
Projected growth with Bass diffusion model Used elsewhere to model EV growth Low, medium and high growth scenarios Split fleet projections proportionally into EV models 1400 1200 1000 800 600 400 200 0 2013 Low Medium High 2015 2017 2019
Year
2021 2023 2025 30% 10% 2027 1% Fleet Penetration, 2027
5
Demand Growth Projections
12000 10000 8000 EV Demand, High Growth EV Demand, Medium Growth EV Demand, Low Growth Base Demand
24-Hour Load Profile with EVs under Each Growth Scenario, 2027
6000 4000 2000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
BAU: T&D Expansion
6
Distribution and transmission network expansion required to serve increased demand from EVs over 15 year horizon Distribution expansion for each 1% increase in load relative to 2012 load Increase substation capacity (transformers + feeders) Transmission expansion for each 5% increase in load relative to 2012 load Add lines Technology & Policy Group
BAU: T&D Expansion Costs
7 Low growth Medium growth High growth
$40.9 m $880/EV $644.5 m $1,460/EV $1,800 m $1,440/EV *Note: Costs will vary with network topology, terrain, selected line voltage, distance of transmission, and reactive power profile of load Technology & Policy Group
BAU: T&D Expansion – Findings
8
T&D network build-out can accommodate projected EV growth Medium Growth cost: $1,460 per EV
Not the recommended course of action
Technology & Policy Group
Summary of Alternatives
9
Energy storage Energy storage is not a viable option Costlier than T&D upgrades, not suitably mature Demand response Real time prices are not reliable alternative to T&D upgrades Controlled charging Controlled charging is preferred solution to accommodate EVs Technology & Policy Group
Alternative 1: Energy Storage
10
Meet additional peak load from EVs with many small installations on distribution network Shifts electricity from off-peak to peak hours Limited technologies are viable for distributed applications Sodium-sulfur (NaS) batteries – commercially available, chosen as a representative battery chemistry Modeled build-out per annual power and energy needs Technology & Policy Group
11
Alternative 1: Energy Storage – NaS Installations (7 MWh/1 MW) 350 300 250 200 150 100 50 0 1 2 3 4 5 6 Low EV Scenario 7 8 Medium EV Scenario 9 10 High EV Scenario 11 Technology & Policy Group 12 13 14 15
Alternative 1: Energy Storage – Findings
12
Costs much more than T&D upgrades Medium Growth: $5,133 per EV Not suitably mature for near-term application
Energy storage is not a viable option
Technology & Policy Group
Alternative 2: Demand Response
13
Engage households in reducing peak load through tariffs that vary with system conditions SDEC pilot used locational marginal price (LMP) Peak demand will be shifted only if: Size of price incentive is sufficiently large (>5x) Households are open and responsive to price signals Price reflects peak system demand
14
Alternative 2: Demand Response – Analysis of Pilot Weak price incentive: only 10 hours with large differential Low opt-in rate (24%) Wide variation/unpredictability in customer response Number of Hrs Single-family Multi-family Average Load Reduction
Peak LMP Hours (Top 5% of Year)
Reduction of Peak Household Demand (%) 95% CI 305 55.5 W 42.1 W 2.25% 1.84% (6.4 , 104.5) (-3.2 , 87.3)
Peak System Demand Hours (Top 5% of Year)
Average Load Reduction Reduction of Peak Household Demand (%) 95% CI 439 34.0 W 23.3 W 1.38% 1.02% (14 , 53.9) (4.6 , 42.1)
15
Alternative 2: Demand Response – Disadvantages of LMPs LMP reflects mostly California wholesale prices: Congestion < 10% of LMP cost in CAISO in 2012 SDEC peak does not align with LMP peak: 600.00
500.00
400.00
300.00
200.00
100.00
0.00
6700
LMP vs. Total System Load During 5% Peak Hours
6800 6900 7000 7100
MW
7200
Avg yearly LMP: $84.33 / MWh
7300 7400 7500 7600
16
Alternative 2: Demand Response – Findings SDEC ’ s DR pilot using real-time prices (RTP) led to small, inconsistent reductions in peak demand The standard price signal – locational marginal price – does not accurately reflect distribution-level congestion
RTP is not reliable alternative to T&D upgrades
Alternative 3: Controlled Charging
17
Two options considered: Utility has full control over charging Delayed charging (4 hours after plug in) Shift EV loads to off-peak hours But at the expense of consumer control Technology & Policy Group
18
Alternative 3: Controlled Charging – Model Modeled load-shifting capability with GAMS Cost-minimization optimization Assumed 90% EV fleet participation Guaranteed all EVs fully charge overnight Minimized total system cost (demand times price) Technology & Policy Group
19
Alternative 3: Controlled Charging – Load Shifting 9000 8000 7000 EV Demand, Medium Growth Base Demand No Control, Medium EV Growth Scenario 6000 5000 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
20
Alternative 3: Controlled Charging – Load Shifting 9000 8000 7000 6000 5000 EV Demand, Medium Growth Base Demand Controlled Charging, Medium EV Growth Scenario, 90% of EVs 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
Alternative 3: Controlled Charging – Costs
21
Costs of program: Smart meters IT and communications infrastructure Annual IT costs Annual savings from less “ dumb ” meter reading T&D upgrades from EVs not in program Costs for Medium Growth Scenario
Item NPV of Cost (Savings)
Reading Old Meters Smart Meters Communications Infrastruc.
IT Infrastruc.
T&D Expansion Total
Total Per EV
($6,040,084) $29,601,080 $465,160 $225,532 $29,833,157 $54,084,845
$125
Technology & Policy Group
22
Alternative 3: Controlled Charging – Findings Off-peak night hours can fully absorb demand from EVs under all growth scenarios Costs less than T&D upgrades Medium Growth: $125 per EV
Preferred solution to accommodate EVs
Technology & Policy Group
Summary of Alternatives
23 EV Growth Scenario EV Fleet Size % of Vehicle Fleet BAU T&D Controlled Charging Energy Storage - NaS Batteries
Total (millions)
$41 $2 $229
Low
46,796 1%
Per EV
$883 $53 $4,893 $54
Medium
447,315 $644 $2,296 10%
Total (millions) Per EV
$1,463 $125 $5,133
High
1,307,855 $1,852 $173 $7,022 30%
Total (millions) Per EV
$1,443 $139 $5,474
Demand Response
No reliable load reduction
24
Tariff Structure – Essential Considerations Goals of differentiated tariffs: Pursue lowest total system cost Allocate costs of system upgrades equitably (avoid cross-subsidization) Demand (capacity) charges more precise than energy charges from T&D perspective Controlled charging infrastructure (e.g., smart meters) furthers other SDEC objectives Technology & Policy Group
Tariff Structure - Recommendations
25
Monthly EV charger fee of $8, effective for 15 years (approx. cost per EV of BAU T&D upgrades) Fee waived if enrolled in controlled charging program Program participants face higher rate when override charging schedule Smart meters paid for by rate base Periodically review tariff (e.g., every 2 years) to ensure accurate cost accounting
Conclusion
26
Large but uncertain demand growth expected from EVs Ideally accommodate load cost-effectively and equitably while encouraging further EV growth BAU T&D expansion costly Of alternatives, only controlled charging accommodates load at reasonable cost Proposed tariff allocates cost equitably Technology & Policy Group
27
Thank You for Your Attention Questions?
Technology & Policy Group
Bass Diffusion Model
28
Three key parameters (low, medium and high): Maximum potential market (m=0.03, 0.25, 0.7) Fraction of purchasers who make decisions independent of others and network externalities ( “ coefficient of innovation ” ) (p=0.01, 0.015, 0.02) Fraction of purchasers who are swayed by decisions of others and network effects ( “ coefficient of imitation ” ) (q=0.3, 0.35, 0.4) Technology & Policy Group
29
Proportions of EV Types in Fleet EV Type PHEV 4.5kWh
PHEV 16kWh EV 24kWh EV 40kWh EV 60kWh EV 85kWh Percentage in Fleet 0.26
0.30
0.15
0.16
0.09
0.04
Technology & Policy Group
Demand Growth Projection Details
30
Split fleet projections proportionally into EV types Accounted for: Fraction of EVs that plug in during peak hours at home Temporal distribution of when EVs plug in Charger level (Level 2 for EVs >40kWh) Daily travel distance (high value (52 mi.) for EVs >40kWh) Duration of charge Technology & Policy Group
31
Demand Growth Projection Details Technology & Policy Group
32
Temporal Distribution of Added Demand
Additional Power Demand from EVs in 2017, 2022 and 2027, Medium Growth Scenario
1000 900 800 700 600 500 400 300 200 100 0 17:00 18:00 19:00 20:00 21:00
Time
22:00 Technology & Policy Group 23:00 0:00 1:00 2017 2022 2027
33
Delayed Charging
9000 8000 7000 6000 EV Demand, High Growth EV Demand, Medium Growth EV Demand, Low Growth Base Demand
24-Hour Load Profile Under 4-Hour Delayed Charging of 90% of EVs
5000 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
34
Controlled Charging under High EV Growth Scenario 9000 8000 7000 EV Demand, High Growth Base Demand 6000 5000 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
Controlled Charging Model Formulation
35
• Cost minimization: • • z = total cost, p(h) = price, B(h) = base demand, D(h) = aggregate EV demand, h = hour, v = vehicle Must fully charge overnight: • • C(v,h) = charging, d(v) = hours required for full charge Charging and plug-in relationship: • L(v,h) = plugs in
36
Controlled Charging Model Formulation •
Charge status:
• • C(v,h) = charging, L(v,h) = plug-in, U(v,h) = unplug Demand from EVs: • • D(h) = aggregate EV demand, P(v) = charging power
Limit number of EVs that plug-in
per hour: • M = max number of EVs that can plug-in per hour Technology & Policy Group
37
T&D Expansion Costs
Technology & Policy Group
38
T&D Expansion
Transmission expansion – add lines Line loadability governed by St. Clair Curve – line loadability vs. line length Capacity of shorter lines limited by conductor thermal capacity, longer lines governed by SIL and voltage stability limits Technology & Policy Group
39
LMP Variation During Pilot Period Only 10 hours during six months with LMP above five times average of $85 / MWh 250 200 150 100 50 0 Price ($ / MWh) Technology & Policy Group
40
DR Household Response
40 30 20 10 0 90 80 70 60 50 Average Single-family Household Reductions During System Load Peak Hours
Values are lower bounds of buckets
kW Technology & Policy Group