Modeling, Simulation, and
Applications of Distributed
Battery Energy Storage
Systems in Power Systems
Xiaokang Xu, Martin Bishop,
Edgar Casale, Donna Oikarinen,
and Michael J.S. Edmonds
S & C Electric Company
CIGRE US 2013 Grid of the Future Symposium
Boston, MA, USA,
October 20-22, 2013
October 2013
Page 1
Energy Storage Projects and Capacity in
US (from DOE Database as of August 2012)
October 2013
Page 2
Major Applications of Battery
Energy Storage System (BESS)
Generation Applications
 Provide renewable sources governor
response and system frequency
regulation. (Renewable generation
typically lacks governor response
and frequency regulation capability.)
 Balance energy needs such as
peaking shaving/valley filling.
(Renewable generation noncontrollable variability increases
balance energy needs.)
 Provide short-term and quick start
reserves.
 Provide renewable energy
production shifting, smoothing and
leveling.
October 2013
Transmission and Distribution
Applications
 Increase transmission capacity factor
for renewable sources.
 Relieve transmission congestion and
relax transmission reliability limits.
 Defer transmission, distribution or
transformer upgrades, capital
expenditure due to congestion, or
peak load growth.
 Provide voltage and VAR support
and reliability enhancement to
manage the fluctuations of renewable
energy production.
 Support islanding system operation
and/or serve loads in isolated areas.
End-User Applications
 Store renewable generation
production.
 Provide time-shifting, load-following
and load-leveling of demand to avoid
peak prices.
 Provide reliability enhancement to
avoid power interruptions.
 Allow utility control for targeted
reliability enhancement.
 Provide renewable generation and
load demand response management.
 Provide load specific voltage
support.
 Provide emergency power.
Page 3
Schematic Diagram of a Typical
BESS
October 2013
Page 4
S&C Delivered BESS Projects
1-MW System – Minnesota
2 x 1-MW System – Canada
1-MW System – Scotland
4-MW System – California
2-MW System – Alameda
2-MW System – Ohio
2-MW System – Indiana
1-MW System – West Virginia
1-MW System – Missouri
1-MW System – Australia
1-MW System – New Mexico
2-MW System – West Virginia
4-MW System – Texas
1-MW System – Catalina
2 x 1-MW System – North Carolina
1-MW System – New Mexico
2-MW System – Ohio
NaS
Li-Ion
October 2013
Advanced Lead Acid
NaNiCl
Page 5
BESS with Renewable Energy
Application
Utility System
MWhr
Meter
MWhr
Meter
Load
Inverter
WTG
BESS
Battery
October 2013
Page 6
DSTATCOM
with
Case StudyRegulation
Results
Capacitor Banks
Case
Cost of Energy
from Utility
Energy from Utility only
Energy from Utility and WTG
Energy from Utility and WTG plus BESS
$3,504,000
$1,555,824
$1,297,149
Cost of
Savings for
Total
Energy from
Load due to
Payment from
WTG and/or
WTG and/or
Load
BESS
BESS
$0
$3,504,000
$0
$1,461,132
$3,016,956
$487,044
$1,655,138
$2,952,287
$551,713
WTG Energy
Curtailment
(MWHr)
Cost of WTG
Energy
Curtailment
Discharging
MWHr from
BESS
Revenue from
BESS
0
1,315
674
$0
$394,359
$202,153
0
0
647
$0
$0
$194,006
For example, when the WTG production is such that the BESS operates with 100%
Depth of Discharge (DOD) per day, the revenue from the BESS would be:
Revenue from BESS = 6 MWh × $300 × 365 (days) = $657,000/year
When operating with 90% DOD per day, the revenue from the BESS would be:
Revenue from BESS = 90% × 6 MWh × $300 × 365 (days) = $591,300/year
Depth of Discharge
(DOD)
Battery Designed Life
(Cycles)
Battery Designed Life
(Equivalent Years)
Revenue from
BESS
Total Revenue from
BESS for Life Cycle
100%
90%
2,500
4,500
7
13
$657,000
$591,300
$4,613,764
$7,474,298
October 2013
Page 7
System Modeling (Peak-Shaving,
Islanding Operation, etc)
25
Peak Shaved
20
Load MVA
ES Discharging
15
ES Charging
Valley Filled
10
Load MVA without ES
Load MVA with ES
5
0
1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47
Time of Day in Half Hour Increments
Pactual, pu
Active Power
Command
Limiter
Active Power
Command, pu
P_batt %
Power Rate of
Change Limiter
+
S
-P_batt %
P
+
PI Controller
÷
S
+
I
Id
-P
-I
Vactual (low bus),
pu
October 2013
Page 8
Idr
System Modeling (Peak-Shaving,
Islanding Operation, etc) (Cont’d)
Vmv actual, pu
1
1  sT 1
Vrefmax
Vmv ref, pu
Qactual, pu
+
1
1  sT 2
Voltage or VAR
Control Mode
Selector
S
PI Controller
+
Q
+
PI Controller
S
Vrefmin
lim
÷
S
-lim
-Q
+
Iqr
Iq
Vmv actual, pu
VAR Command, pu
Vmv, max
Vmv, pu
1
1  sT 3
Vmv, min
Voltage Command
(From SCADA), pu
Vmax
+
S
Vmin
October 2013
VdrMax
+
PI Controller
Vlv, pu
S
+
0
Page 9
Case Study - System
0.997
12.4
UTILITY GRID
1.010
139.4
0.997
12.4
LOAD
3.0
3.0
3.0
1.0
1.0
1.0
1
0.997
12.4
1.000
0.5
FACTS (UPFC)
-0.0
1.000
0.5
1.0
4.0
4.0
2.1R
2.1
2.0
2.0
2.0
MAIN XFRM
0.987
0.5
1.0
1
4.0
1
4.0
1
4.0
1
1
1.0
1.0 1.0
1.0
1.0 1.0
1.0
1.0
1.0
1.0
0.0
0.0
0.0R
PAD XFRM
BESS MODEL
October 2013
Page 10
1
Case Study – Peaking-Saving
October 2013
Page 11
Case Study – Islanding Operation
October 2013
Page 12
Conclusions
• Typical applications of the BESS include output
smoothing and time shifting for intermittent
renewable (wind and solar) energy sources, and
peak shaving and valley filling for the power grid,
and islanding system operations. This paper
presented case studies to discuss these types of
applications. The paper also included modeling
and simulation of the BESS with the widely-used
Power System Simulator PSS®E. Simulation
results show that the BESS dynamic model
responds properly and correctly as expected when
operating in peak shaving/valley filling mode and in
islanding operation mode in a simplified system.
This model can be used for power system studies
involving those typical BESS applications.
October 2013
Page 13