Transcript Slide 1

Electricity Load Profiles
and Load Management
Guenter Conzelmann
Center for Energy, Environmental, and Economic Systems Analysis
Decision and Information Sciences Division (DIS)
Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439
Electricity Demand/Load Analysis is part of a Multi-Step
Long-term Energy Planning Process
Economic
Analysis
Energy
Demand
Analysis
Supply
Demand
Balance
Energy
Resource
Evaluation
Impacts
Analysis
Review
Evaluate
Energy
Technology
Definition
ITERATION
2
The Analysis Typically Starts with Developing Macroeconomic
Projections and Translating them into Projections of Future Demand/Load
Macro-Economic
Information
Energy Demand
Time-series extrapolation
Input/output model
Econometric model
Other models
Final Energy (simple)
Useful Energy (advanced)
600
3,000
Baseline
2,500
High Growth
2,000
1,500
1,000
High Growth
400
300
200
500
100
0
0
2008 2012 2016 2020 2024 2028
Baseline
500
Demand [TWh]
GDP [US$billion]
3,500
2008
2012
2016
2020
2024
2028
Besides overall macroeconomics, drivers include sectoral shifts, absolute and
relative price trends, technology/efficiency trends, behavior, etc.
3
In Addition to Total Annual Demand, it is Important to Look at
the Patterns/Profile of the Load (1)
 Typically, we see a distinct daily profile of consumption that often varies by season
Week 1 (Mo – Sun)
Week 2 (Mo – Sun)
4
In Addition to Total Annual Demand, it is Important to Look at
the Patterns/Profile of the Load (2)
 We also usually observe an annual or seasonal variation in loads; may vary by region
5
Hourly Load (GW)
Example of Hourly Load Profile: Illinois (1)
40
40
35
35
30
30
25
25
20
20
15
15
10
10
5
5
0
0
Jan
Mar
May
Jul
Sep
Nov
Jan
6
Example of Hourly Load Profile: Illinois (2)
 Location of the load matters, particularly if transmission is congested; will impact
benefits of smart-grid implementation
2
Hourly Loads - Location A
1.5
1
0.5
0
0
2
4
6
8
10 12 14 16 18 20 22 24
8
Hourly Loads - Location B
6
4
2
0
0
2
4
6
8
10
12
14
16
18
20
22
24
7
Example of Hourly Load Profile: Illinois (3)
50
50
Load
Installed Capacity
45
45
Capacity / Load (GW)
40
The system is
typically sized
to reliably meet
this peak
demand
35
30
40
35
30
25
25
20
20
15
15
10
10
5
5
0
0
Jan
Mar
May
Jul
Sep
Nov
Jan
8
Example of Hourly Load Profile: Illinois (4)
50
Planned Outages
Installed Capacity
Capacity / Load (GW)
45
Forced Outages
Online Capacity
50
Load
45
40
40
35
35
30
30
25
25
20
20
15
15
10
10
5
5
0
0
Jan
Mar
May
Jul
Sep
Nov
Jan
9
Understanding the Load Profile is Important for Generation
System Expansion, or Investment Planning
 The pattern/shape of the demand has a significant impact on the technology selection
 Different technologies have different technical and economic characteristics and
14
14
12
12
Hourly Load [GW]
Hourly Load [GW]
operational capabilities and limitations
10
8
6
4
10
8
6
2
0
0
Mar
May
Jul
Sep
Nov
Jan
Served by medium-cost flexible
generators (e.g., coal, combined cycles)
4
2
Jan
Served by high-cost generators
(e.g., gas turbines), also peaking hydro
or pumped storage
Served by low-cost base load generators
(e.g. nuclear)
0
1460
2920
4380
5840
7300
8760
10
10
Example of Hourly Load Profile: New England
(New Hampshire Electric Cooperative, 2008)
180
160
Hourly Load (MW)
140
120
100
80
60
40
20
0
0
1460
2920
4380
5840
7300
8760
11
In Order to Better Understand the Overall Load Pattern, it
Helps to Decompose the Load into Different Components
Residential
Agriculture
Commercial
Industry
Transport
12
Example of Hourly Load Profile: Residential
3.5
3.5
Single Family - January, w/o Elec Heat
3
3
2.5
2.5
2
2
1.5
1.5
1
1
Single Family - July, w/o Elec Heat
0.5
0.5
Peak Day
Weekday
Peak Day
Weekend
0
0
2
4
6
8
10
12
14
16
18
20
Weekday
Weekend
0
0
22
3.5
2
4
6
8
10
12
14
16
18
20
22
3.5
Multi Family - January, w/o Elec Heat
3
2.5
2.5
2
2
Peak Day
1.5
Weekday
Peak Day
Weekend
1
0.5
0.5
0
0
2
4
6
8
10
12
14
16
18
20
Weekday
Weekend
1.5
1
0
Multi Family - July, w/o Elec Heat
3
22
0
2
Source: comed.com
4
6
8
10
12
14
16
18
20
22
13
Example of Hourly Load Profile: Residential
3.5
3.5
Single Family - January, w/o Elec Heat
3
3
2.5
2.5
2
2
1.5
1.5
1
1
Single Family - July, w/o Elec Heat
0.5
0.5
Peak Day
Weekday
Peak Day
Weekend
0
0
2
4
6
8
10
12
14
16
18
20
Weekday
Weekend
0
0
22
3.5
2
4
6
8
10
12
14
16
18
20
22
3.5
Multi Family - January, w/o Elec Heat
3
2.5
2.5
2
2
Peak Day
1.5
Weekday
Peak Day
Weekend
1
0.5
0.5
0
0
2
4
6
8
10
12
14
16
18
20
Weekday
Weekend
1.5
1
0
Multi Family - July, w/o Elec Heat
3
22
0
2
Source: comed.com
4
6
8
10
12
14
16
18
20
22
14
Example of Hourly Load Profile: Residential (2)
10
10
Single Family - January, with Elec Heat
Multi Family - January, with Elec Heat
8
8
6
6
4
4
2
Peak Day
Weekday
2
Weekend
Peak Day
0
Weekday
Weekend
0
0
2
4
6
8
10
12
14
16
18
20
22
0
2
Source: comed.com
4
6
8
10
12
14
16
18
20
22
15
Example of Hourly Load Profile: Commercial
120
120
Medium-Size Customer - January
Medium-Size Customer - April
90
90
60
60
30
30
Peak Day
Weekday
Weekend
0
Peak Day
Weekday
Weekend
0
0
2
4
6
8
10
12
14
16
18
20
22
120
0
2
4
6
8
10
12
14
16
18
20
22
120
Medium-Size Customer - July
Medium-Size Customer - October
90
90
60
60
30
30
Peak Day
Weekday
Weekend
0
Peak Day
Weekday
Weekend
0
0
2
4
6
8
10
12
14
16
18
20
22
0
Source: comed.com
2
4
6
8
10
12
14
16
18
20
22
16
Example of Hourly Load Profile: Industrial
16000
16000
Very Large Customer - January
Very Large Customer - April
12000
12000
8000
8000
4000
4000
Peak Day
Weekday
Weekend
0
Peak Day
Weekday
Weekend
0
0
2
4
6
8
10 12 14 16 18 20
22
16000
0
2
4
6
8
10 12 14 16 18 20
22
16000
Very Large Customer - July
Very Large Customer - October
12000
12000
8000
8000
4000
4000
Peak Day
Weekday
Weekend
0
Peak Day
Weekday
Weekend
0
0
2
4
6
8
10 12 14 16 18 20 22
0
Source: comed.com
2
4
6
8
10 12 14 16 18 20 22
17
Example of Hourly Load Profile: Street Lighting
3.5
3
Jun-21
2.5
Dec-21
2
1.5
1
0.5
0
0
2
4
6
8
10
12
14
16
18
20
22
18
Example of Hourly Load Profile: New Emerging Load Profiles
(e.g., Electric Vehicles)
 Must consider how much and how quickly the
load evolves
– Rate of PHEV penetration
 Must consider locational considerations
– Where is new load concentrated
– Will impact transmission congestion, as well as
system operations, electricity prices, and carbon
emissions
Baseload
Base + PHEV Moderate
180,000
120,000
150,000
90,000
15,000
PHEV Aggressive
120,000
0
24
48
72
96
25,000
150,000
Base + PHEV Aggressive
144
20,000
15,000
90,000
15,000
60,000
10,000
30,000
5,000
10,000
0
120
25,000
PHEV Aggressive Smart
Baseload
Base + PHEV Aggressive Smart
20,000
5,000
60,000
0
30,000
WECC April 2020 Aggressive PHEV Case:
Smart Charging
120,000
90,000
30,000
Baseload
180,000
10,000
Total Load [MW]
60,000
30,000
20,000
WECC April 2020 Aggressive PHEV Case:
Charge When Arriving @ Home
PHEV Load [MW]
PHEV Moderate
Western Interconnect
Model Representation
25,000
[MW]
LoadLoad
TotalPHEV
[MW]
150,000
Total Load [MW]
30,000
WECC - April 2020 Moderate:
Charge When Arriving @ Home
PHEV Load [MW]
180,000
168
30,000
5,000
0
0
0
24
48
72
96
120
144
168
19
019
0
0
24
48
72
96
120
144
168
Example of Hourly Load Profile: New Emerging Load Profiles
(e.g., Electric Vehicles)
180,000
30,000
WECC April 2020 Aggressive PHEV Case:
Charge When Arriving @ Home
150,000
PHEV Aggressive
Baseload
25,000
Base + PHEV Aggressive
20,000
Total Load [MW]
PHEV Load [MW]
120,000
90,000
15,000
60,000
10,000
30,000
5,000
0
0
0
24
48
72
96
120
144
168
20
20
Example of Hourly Load Profile: New Emerging Load Profiles
(e.g., Electric Vehicles)
180,000
30,000
WECC April 2020 Aggressive PHEV Case:
Smart Charging
150,000
20,000
PHEV Load [MW]
120,000
Total Load [MW]
25,000
PHEV Aggressive Smart
Baseload
Base + PHEV Aggressive Smart
90,000
15,000
60,000
10,000
30,000
5,000
0
0
0
24
48
72
96
120
144
168
21
21
Example Residential Electricity Consumption: What Happens
behind the Socket in the Wall…
22
Example Residential Electricity Consumption: When was the
Last Time you Looked at your Utility Bill?
May need to be a
rocket scientist...
(and actually understood it….)
14 different fees,
charges, taxes
…or an Einstein
23
For Residential Sector, Do you Know How Much Electricity
You Consume per Month?
1,400
Average Monthly Consumption (kWh)
U.S. Average Monthly Consumption (kWh)
1,200
U.S. Average:
920 kWh
1,000
800
Virginia:
1,173 kWh
600
400
200
E
M
R
I
C
A
VT
A
N
H
N
Y
H
I
M
M
I
AK
N
M
N
J
W
I
C
O
IL
D
C
C
T
IA
PA
M
N
M
N
U
T
O
H
W
Y
N
V
D
E
KS
IN
O
R
N
E
SD
ID
W
A
M
D
O
AZ
M
FL
N
C
O
K
N
D
AR
TX
G
A
W
V
KY
VA
S
SC
M
AL
LA
TN
0
24
24
2008 Average Monthly Residential Electricity Consumption (kWh) by State
For Residential Sector, Do you Know How Much Electricity
You Consume per Month? (2)
1,400
Conzelmanns' Average Monthly Electricity Consumption
(kWh) 1997-2007
1,200
1,000
800
600
400
200
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
25
For Residential Sector, Do you Know How Much Electricity
You Consume per Month? (3)
2,500
Conzelmanns' Monthly Electricity Consumption (kWh)
1997-2007
2,000
1,500
1,000
500
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Sept
Oct
Nov
2007
0
Jan
Feb March April
May
June
July
Aug
Dec
26
For Residential Sector, Do you Know How Much You Pay for
Electricity?
35.0
Average Retail Price (Cents per Kilowatthour)
30.0
U.S. Average Retail Price (Cents per Kilowatthour)
25.0
U.S. Average:
11.3 c/kWh
20.0
Virginia:
9.6 c/kWh
15.0
10.0
5.0
0.0
HI CT NY MA RI AK ME NH NJ VT DE MD CA TX DC NV FL WI PA IL
MI AL MS LA AZ CO OH NM GA SC MN VA NC IA AR MT OK TN KS IN OR SD UT WY MO KY NE WA ND WV ID
(2008 Average Residential Electricity Price (c/kWh) by State)
27
Example of Hourly Load Profile: Conzelmann Household
Hourly Consumption [kW]
9.0
0.50
Mon-Sun (June 9 - 15, 2008)
0.45
8.0
0.40
7.0
0.35
6.0
0.30
5.0
0.25
4.0
0.20
3.0
0.15
2.0
0.10
1.0
0.05
0.0
0.00
-1.0
(0.05)
-2.0
(0.10)
Negative price:
-21 c/kWh
-3.0
-4.0
Hourly Energy Price ($/kWh)
-5.0
0
24
48
72
(0.15)
(0.20)
Hourly Consumption (kWh)
96
120
Hourly Energy Price [$/kWh]
10.0
144
(0.25)
168
28
Example of Hourly Load Profile: Conzelmann Household
10.0
0.50
Mon-Sun (October 27 - November 2)
9.0
0.45
0.40
Hourly Energy Price ($/kWh)
Hourly Consumption [kW]
7.0
Hourly Consumption (kWh)
0.35
6.0
0.30
5.0
0.25
4.0
0.20
3.0
0.15
2.0
0.10
1.0
0.05
0.0
0.00
-1.0
(0.05)
Negative
25 cents/kWh
-2.0
Hourly Energy Price [$/kWh]
8.0
(0.10)
-3.0
(0.15)
0
24
48
72
96
120
144
168
29
Even More Detail Can be Added to Improve Understanding of
Load Pattern and Identify Efficiency and DSM Potential
Cooking
Air Conditioning
Lighting
Appliances
Space
heating
Water
heating
30
The Role of Demand Side Management (1)
 Opportunities for demand side management drive investments in smart-grid and
advanced metering infrastructure
 Goal is to shift load to reduce peak loads
– Flattens demand curve
– Reduces generation cost by shifting to low-cost base-load generation
– Reduces maintenance costs
– Avoids/delays infrastructure investments (generation, transmission, distribution)
– Can reduce overall consumption
 Early DSM program (starting in 1980s) have primarily focused on commercial and
industrial consumers
– Mostly direct load control and tiered pricing
 Smart-grid technology will impact DSM program focus
– Shift from direct load control to dynamic pricing
– Inclusion of residential and small-to-medium businesses
31
The Role of Demand Side Management (2)
 Direct load control or incentive-based approaches
– E.g., interruptible/curtailment rates
 Allows utilities to control specific loads (e.g., air
conditioning)
– Consumer receives billing discount (e.g., fixed monthly
payment for peak months)
 Direct load control is offered by many utilities
– One-third of utilities offer direct load contol for
residential AC
• Average participation 15%
– About two-thirds offer direct load control to industrial
and commercial costumers
 Programs have proven cost-effective with
substantial savings
– 29% average peak load reduction across a sample of
24 programs (Source: eMeter Strategic Consulting,
2007)
32
The Role of Demand Side Management (3)
 Dynamic Pricing
– Almost 1/3 of utilities offer some form of dynamic pricing
– Time of use, critical peak pricing, real-time pricing
– Current pilot programs show significant variation in
residential peak load reduction with an average of about
22%
– Impact on overall consumption may be very small
 Consumption information and transparency
– More frequent billing: Weekly/daily billing estimated to
reduce consumption by 10-13%
– In-home displays, estimated to save 4-15%
– Smart-appliances and building automation may lead to
peak reductions of over 40% and a decrease in
consumption of about 11%
– Where is my dishwasher control app, my real-time price
app???
33
Example of Hourly Load Profile: Conzelmann Household
Before and After Real-time Price Response (BEFORE)
Hourly Consumption [kW]
9.0
0.50
Mon-Sun (June 9 - 15, 2008)
0.45
8.0
0.40
7.0
0.35
6.0
0.30
5.0
0.25
4.0
0.20
3.0
0.15
2.0
0.10
1.0
0.05
0.0
0.00
-1.0
(0.05)
-2.0
(0.10)
-3.0
(0.15)
-4.0
Hourly Energy Price ($/kWh)
-5.0
0
24
48
72
(0.20)
Hourly Consumption (kWh)
96
120
144
Hourly Energy Price [$/kWh]
10.0
(0.25)
168
34
Example of Hourly Load Profile: Conzelmann Household
Before and After Real-time Price Response (BEFORE)
Loadguard Price Point
10 cents/kWh
14 cents/kWh
35
Example of Hourly Load Profile: Conzelmann Household
Before and After Real-time Price Response (AFTER)
Mon-Sun (July 7 - 13, 2008)
9.0
Hourly Consumption [kW]
0.50
0.45
8.0
0.40
7.0
0.35
6.0
0.30
5.0
0.25
4.0
0.20
3.0
0.15
2.0
0.10
1.0
0.05
0.0
0.00
-1.0
(0.05)
-2.0
(0.10)
-3.0
(0.15)
Hourly Energy Price ($/kWh)
-4.0
Hourly Consumption (kWh)
Hourly Energy Price [$/kWh]
10.0
(0.20)
-5.0
(0.25)
0
24
48
72
96
120
144
168
36
Monthly Savings: Real-time Pricing versus Regulated Tariff
35%
30%
25%
20%
15%
10%
5%
0%
Apr-08
Jul-08
Oct-08
Jan-09
Apr-09
Jul-09
Oct-09
Jan-10
37
A Couple of Thoughts on my Personal Real-time Pricing
Experiment
 Substantial cost savings, energy savings unclear
 Potential for information overload
 Feedback is slow (delayed by a month)
 Thermal comfort is compromised
38
Summary
 Load profiles play an important role in power system planning
 When projecting future loads, changes in the load shape will have to
be considered
– Due to technology changes (e.g., smart-grid)
– Due to technology introduction (e.g., electric vehicles)
– Due to market/consumer incentives (new pricing mechanisms)
 Energy efficiency and demand side management can play a
significant role in shaping future load levels and profiles
39