Generator Cost Curves Evaluation of Conventional Generators

PSerc Project M-24
where
The line active power flows are,
The economic case for bulk energy storage in transmission systems with high percentages of
renewable resources
X=
Wichita State University, Arizona State University
Initiated September 2012
Project Team
W. T. Jewell (PI) – Wichita State University
K. W. Hedman – Arizona State University
G. T. Heydt – Arizona State University
Industry Advisors
Paul Myrda (EPRI) Don Pelley (SRP) James Price (CAISO) Hussam
Sehwail (ITC) Janos Toth (BC Hydro) Helen Whittaker (BCHydro) Bill
Winston (Southern Company)
Students
Haneen Aburub (WSU) Nan Li (ASU)
Trevor Hardy (WSU)
John Ruggiero (ASU)
Zhouxing Hu (WSU)
Nick Steffan (ASU)
Summary: As renewable penetrations increase, the uncertainty and variability of wind and solar may be alleviated by multiple bulk energy storage technologies. This project addresses the
economic case for bulk energy storage optimized for multiple objectives, including cost, congestion, and emissions, for increasing levels of renewable resource penetration.
Motivations
Mathematical Model
The increasing ramping requirement
introduced by renewable energy may
degrade the efficiencies and increase
the average costs of conventional
generators. On the other hand, the fast
ramping capability of energy storage
makes it competitive under high
renewable penetration levels.
A traditional day-ahead generation scheduling problem.
Objective function: minimize expected generator fix costs,
variable costs and ramping costs.
 Ramping costs – costs that occur during the 10-min fast
ramping process:
2l 1 Pg k,t Pg 0,t
Objectives
Evaluation of Conventional Generators
Evaluate the efficiencies and
competitiveness
of
traditional
generators under high renewable
penetration levels.
Identify the effectiveness of energy
storage under high penetration levels
of renewable resources.
23
Marginal Cost, dF/dP ($/MWh)
22
21
Generator Cost Curves
As renewable
penetration levels
increase, conventional
generator will operate
at lower outputs, which
has higher average
costs and lower
marginal costs.
Marginal cost
20
19
18
17
16
15
100
150
200
250
Output, P/ MW
300
350
Average Cost, F/P ($/MWh)
80
Average cost
70
Low penetration level
60
50
High penetration level
40
30
100
150
200
250
Output, P/ MW
300
350
RampCost
c g l[
2
l
Pg 0,t ],
L
An Application
An application to the
state of Arizona has
been studied: three
large pumped hydro
storage facilities have
been
located
and
operated
using
an
optimal storage strategy
regime.
g, k, t
Two PHS and one CAES were included in the model.
Without Energy Storage
Wind
Level
With Energy Storage
Hourly Expected
Hourly Expected
Expected Number of
Expected Number of
Average
Average
Units
Units
Capacity
Capacity
Cost per Unit
Cost per Unit
Factor Dispatched
Factor Dispatched
($/MWh)
($/MWh)
30%
80.98
39.3%
19
81.83
43.6%
18
40%
82.81
33.6%
20
80.07
38.6%
17
50%
84.42
27.8%
20
80.92
31.0%
17
60%
86.46
24.5%
21
80.25
27.8%
17
70%
87.01
22.4%
21
86.52
21.6%
19
Hourly Expected Average Cost = Variable Cost + Fix Cost + Ramping Cost
C g kt
G
Hourly Expected Average Cost
k ,t
t g kt
g 1
Lake
Mead
County
Mohave
Glen
Coconino
Canyon
Year of
Nearby
develop
bus
ment
Water
source
Operating Entity
N/A
Lake
Mead
Western Area Power
Administration
Glen
Canyon
N/S
N/A
Colorado
River
Western Area Power
Administration
Horse
Mesa
N/A
Salt River
Salt River Project
Mead
N/S
k
E g kt
on
Pumped
Location hydro
name
On
Ng
,
g, k, t
k
Horse
Mesa
Maricopa
k ,t
Summary of Results
As renewable penetration levels increase, conventional
generators have higher expected average costs and lower
capacity factors.
Under high renewable penetration levels, energy storage
can improve the efficiencies and reduce the average costs of
conventional generators.
Large scale pumped hydro may be used as an energy
storage medium, even in arid areas such as Arizona
Typical annual operating cost savings are in the 8 to 13%
range for the state of Arizona (accounting for the cost of
added facilities)

Download Report