This document summarizes a study analyzing the power loss, efficiency, reliability, and cost of a 1 MW/500 kWh battery-based energy storage system for frequency regulation. The study calculates power losses from the battery and power conversion system components under different operating conditions. It then uses these loss calculations to determine the system's efficiency. Reliability is calculated using an Arrhenius life stress relation considering temperature. Total system cost is also broken down. Key findings include the system having 146 kW power loss and 85% efficiency at rated power. Mean time between failures is calculated as 8 years with 73% reliability after 1 year. Battery and power conversion system costs make up 58% and 16% of total cost respectively. Further research

1. A comprehensive power loss, efficiency, reliability and cost calculation
of a 1 MW/500 kWh battery based energy storage system for
frequency regulation application
Md Arifujjaman
Broomfield, CO, USA
a r t i c l e i n f o
Article history:
Received 21 April 2014
Accepted 24 July 2014
Available online
Keywords:
Conduction loss
Cost
Energy storage system
Switching loss
Efficiency
Reliability
a b s t r a c t
Battery based energy storage system (ESS) has tremendous diversity of application with an intense focus
on frequency regulation market. An ESS typically comprised of a battery and a power conversion system.
A calculation of performance parameters is performed in this research. The aim is to formulate an in-
depth analysis of the ESS in terms of power losses of the semiconductor and electrical devices, effi-
ciency, reliability and cost which would foster various research groups and industries around the globe to
improve their future product. In view of this, a relation between the operating conditions and power
losses is established to evaluate the efficiency of the system. The power loss calculation presented in this
paper has taken into account the conduction and switching losses of the semiconductor devices. Af-
terwards, the Arrhenius Life Stress relation is adopted to calculate the reliability of the system by
considering temperature as a covariate. And finally, a cost calculation is executed and presented as a
percentage of total cost of the ESS. It has been found that the power loss and efficiency of the ESS at rated
power is 146 kW and 85% respectively. Furthermore, the mean time between failures of the ESS is 8 years
and reliability remains at 73% after a year. The major cost impact observed is for battery and PCS as 58%
and 16% respectively. Finally, it has been determined that further research is necessary for higher efficient
and lower cost system for high penetration of energy storage system in the market.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
Energy storage technologies are emerging as the most prom-
ising solutions for augmenting frequency regulation application for
utilities. Large scale energy storage solution prefers pumped hydro
due to the maturity of technology as well as requirement posed by
the utility [1]. However, other smaller technologies such as com-
pressed air, thermal, batteries, and flywheels are also evolving
rapidly because of near commercial product viability through
vigorous research by the research groups and industries around the
globe. In contrast to the capabilities of other smaller technologies,
battery storage technology is forefront owing to the competency of
lower power and shorter discharge times, ranging from a few
seconds to 6 h, and easily adaptable at a site without ample
attention on any specific geographical features.
Among various battery chemistries, lead-acid battery remains a
dominant choice for grid-connected energy storage applications.
However, Lithium-ion battery technologies promised enhanced
energy storage densities, greater cycling capabilities, higher safety
and reliability, and lower cost and have reached production levels
as necessary to meet market cost and quality control requirements
[2]. In a package level, a significant advantage of lithium-ion system
as compared to the lead acid is that, a lead acid system must have a
larger nameplate energy capacity than the lithium-ion system to
have the same amount of available energy and is a favorable choice
in the industry. In addition to the battery system, an efficient Power
Conversion System (PCS) is one of the most crucial parts of any
Energy Storage Systems (ESSs). It serves as the interface between
the storage devices and the utilities that distributes electricity to its
customers. While a 2-level PCS for DC to AC power conversion for
utilities is readily available, a 3-level PCS could be an optimum
choice [3]. Adaption of low voltage switches, multiple level of
output voltage, and lower total harmonic distortion are some of the
advantages of a 3-level PCS. The power losses due to switching and
conduction losses are lower due to the use of lower switching
frequency and low forward voltage drop of the semiconductor
switches. Furthermore, when several voltage levels are used, the
dv/dt of the output voltage is smaller thus the stress in cables and
batteries is smaller.E-mail address: sumon326@yahoo.com.
Contents lists available at ScienceDirect
Renewable Energy
journal homepage: www.elsevier.com/locate/renene
http://dx.doi.org/10.1016/j.renene.2014.07.046
0960-1481/© 2014 Elsevier Ltd. All rights reserved.
Renewable Energy 74 (2015) 158e169

2. Recently, many industries around the globe are developing
battery based ESS including an integrated PCS for frequency regu-
lation application. Industries, such as ABB, Saft, Dynapower, Parker,
Bosch, Princeton Power System is the top notch brand names
among others around the globe. The basic product line from the
industries ranges from 1 MW to 4 MW system for a time duration of
30 min to 1 h. Unfortunately, a detail of the information of the
products is not publicly available due to the non-disclosure
agreement nature of the R & D program. These possess a grim
constraint to other emerging industries of the same domain as they
have a very minimal to no information about any in-depth initial
considerations of the ESS product. The non-disclosing nature of the
product information also discourages a high penetration and
further development of the energy storage systems to the market.
In order to enhance a profound understanding of the internal na-
ture of the ESS, an in-depth study is performed and findings are
presented to encourage others for further development of their
product. Although author has investigated an in-depth analysis
with the best of his knowledge, however, author does not take any
responsibility in any circumstances' if applying this research does
not meet the performance expectation of an ESS by any individual,
research groups or any industries. In addition, the research pre-
sented in this article is Author’s own and don’t represent any
company positions, strategies, or opinions.
Among various performances and design criteria for the ESS, the
overall power losses, efficiency, reliability and cost are the most
significant factors that needs extensive investigation because of a
growing concern regarding the energy savings, efficiency and cost.
However, a considerable lack is observed in the previous literatures
that practically discusses with the investigation on calculation of
power loss, efficiency and reliability that varies with the operating
points for an energy storage system. Furthermore, a detail cost
breakdown for an ESS is almost null in the previous literature by
either any research group or industries which is an essence for
developing a product.
An extensive literature review has been performed and found
that there is a considerable need to comprehensively calculate the
power losses of the semiconductor and other electrical devices for
the ESS. A calculation of power losses of a PCS for a given operating
condition is performed in Refs. [4e19] in terms of the total semi-
conductor power losses. However, calculating individual semi-
conductor power loss lacks a considerable valid justification. This is
because, firstly, a non-linear loss calculation approach is unable to
reflect the switching losses of the semiconductor devices, which
could be a dominant factor during the high switching state [4e11].
Secondly, power loss calculation based on the data provided by the
manufacturers is ambiguous and pessimistic [12e16]. Thirdly,
physics-based simulation models of semiconductor devices power
losses requires implicit integration methods, leading to an
increased simulation time. Furthermore, it requires detail knowl-
edge of the dimensions of the devices [17e19]. There have been
very limited efforts found on modeling of the PCS as well as battery
power losses that constitute an ESS for frequency regulation
application.
In addition, most of the reliability calculations for electronic
components are based on the accessible data provided by the mil-
itary handbook for reliability prediction of electronic equipment
which is criticized for being obsolete and pessimistic [20,21]. A
comparative reliability calculation of different PCS has been carried
out based on the military handbook by Aten et al. [21]; however, the
absence of environmental and current stress factors can pose grim
constraints on the calculated reliability value. Rohouma et al. [22]
provided a reliability calculation for an entire PV unit which can
be considered more useful, but the approach lacks valid justification
as the data provided by the author is taken from the manufacturers'
published data which is somewhat questionable. This is due to the
fact that reliability calculations using purely statistical methods
[12], manufacturers data [22,23,28], or military handbook data [24]
neglect the operating point of a component. Moreover, the total
number of components could vary for two systems (which have the
same objective) in order to meet a certain criterion of the overall
system. Although higher components in the ESS will exhibit less
reliability and vice versa, the effects of the covariates could be
different and consequently could lead to a variation in the reliability
[25]. Furthermore, a reliability evaluation for the ESS of a grid
connected application is essential in order to optimize the system
performances as well as system cost [26]. Another important point
to mention is that reliability analysis based on the covariate factor is
strongly influenced by the standard reliability data book also. For
example, it is shown in previous research that different values of
covariate factor for a same covariate is possible by using a different
reliability standard data book [27]. This variation in covariate factor
also varies the reliability of an integrated system which is composed
of numerous semiconductor devices. Moreover, it is well under-
stood that an error in reliability prediction for a system could prove
to be fatal for the high penetration of ESS.
Based on the above discussions, it can be asserted that most of
the attempts for the power loss and reliability calculation have
been developed so far based on several assumptions and often
neglected a fraction of the entire power losses as well as could not
convey the actual reliability data of the system. Furthermore, a
power loss and reliability calculation in the energy storage domain
is difficult to find. This discrepancy could affect the preference of an
efficient grid-connected ESS that is in a great need for high pene-
tration of frequency regulation application. As a consequence, this
research aims at advancing the use of grid-connected ESS by
calculating the power losses and reliability of the semiconductor
and other electrical devices of ESS for varying operating conditions.
Based on the power generation and loss with operating points,
efficiency is calculated for the system. A novel approach has been
presented to relate the power loss to the reliability calculation
through Arrhenius Life Stress relation and consequently mean time
between failures of the ESS is quantified, which can be considered
the most widely used parameter in reliability studies [20]. The
research then extended the scope by calculating the cost of the
energy storage system thus helps other individuals, research
groups or industries to gain a preliminary assumption on the cost of
the system.
This paper is organized as follows: Followed by a detail litera-
ture review in the first section, the configuration of the ESS is
presented in the second section. The third section describes the
power loss calculation in the semiconductor and electrical devices
for considered operating conditions and corresponding efficiency
calculation is presented in fourth section. The fifth and sixth section
describes the approach to calculate reliability and a module based
cost calculation approach of the ESS. The calculation results and
discussions are presented in seventh section and finally, the find-
ings of the investigations are highlighted in the conclusions.
2. Energy storage system description
Fig. 1a shows a functional block diagram of the ESS connected to
a low voltage bus that consists of a combination of four Battery
Strings (BS) and two-parallel-operated 3-level PCS. Each BS
composed of a series connected battery modules (battery modules
are formed by the individual battery cells in series) and a 3-level
PCS which transfers energy to the local low voltage ac bus. Two
BS are protected by a single Battery Management System (BMS)
that has a bi-directional communication with the Energy Man-
agement System (EMS). The EMS is the supervisory controller that
M. Arifujjaman / Renewable Energy 74 (2015) 158e169 159

3. Fig. 1. Energy storage system functional a) Block diagram, b) Detail component level connection.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169160

4. accepts frequency signal from the dispatch center and communi-
cates that with the BMS and local controller of each 3-level PCS. The
PCS is based on P and Q control and the PCS couples to the Point of
Coupling (PCC) through a delta-wye transformer, acting as a source
of leading or lagging active/reactive current. Each PCS should
maintain the frequency at the PCC using only local information. The
PCS can not only convert the input dc voltage to a three-phase AC
voltage with desired magnitude, frequency and phase angle at the
PCC, but also capable to supply bidirectional controllable active and
reactive power to limit the fluctuation of the frequency and voltage
to an allowable range if required. However, it should be mentioned
that the primary objective is to ensure the injection and absorption
of active power depending on the frequency signal and if required,
the PCS is capable to perform to regulate the voltage. The system is
capable providing 1 MW output of 480VAC/60 Hz, three phase low
voltage power. The initial energy capacity is 500 kWh. The system
also adopts LiFePO4 battery technology with long cycle life and
large cell capacity to meet the MW-scale energy storage output. The
switchgear and step up transformer is neglected due to the out of
scope of this research. Fig. 1b shows the detail of the electrical
component level connection that forms the ESS.
3. Power loss calculation
A mathematical model of the power losses in the internal
resistor of the battery and semiconductor devices (diodes/IGBTs)
for the 3-level PCS is required in order to calculate the efficiency of
the ESS. The losses for the resistor and semiconductor devices are
strongly dependent on the voltage and current waveforms.
Simplified analytical derivation of voltage and current equations
associated with the individual semiconductor devices are derived
to determine the power losses. The power loss calculation pre-
sented in this investigation focus on the losses generated during
the conduction and switching states of the semiconductor devices.
3.1. Battery
In an ideal world, a battery cell can be represented as an ideal
voltage source. However, a more practical approach but still ideal is
to represent battery using a voltage in series with a resistor. This
form of representation is the simplest types of battery cell models
and has been widely accepted in electric circuit analysis and design
[29e31]. However, it needs to be mentioned that they are over-
simplified and cannot give any detailed and accurate information
about the battery operation and performance such as the battery
SOC, thermodynamics, etc. More advanced battery circuit models
will be considered and left for future research.
The battery string modeling is performed based on the Theve-
nin's equivalent circuit. Fig. 2 shows the Thevenin's equivalent
model of one of the BS, where Req is the equivalent series resistance
of series combination of battery resistances which is calculated
based on the Thevenin's equivalence.
It has been considered that the battery will be charged and
discharged at the same 2C rate. In such a situation the battery
terminal voltage due to internal resistance can be expressed as
VeqÀt ¼ VeqÀb À ReqÀb  IeqÀb (1)
where Veq-t is the terminal voltage of the Thevenin equivalent
voltage of a BS, Veq-b is the Thevenin equivalent open circuit voltage
of the battery string, Req-b is the Thevenin equivalent resistance of
the BS and Ieq-b is the DC current from the battery string and serves
as the input to the PCS. It should be mentioned that each battery
string is composed of several battery modules that is essentially
made up of battery cells.
The power loss of the battery then can be calculated as.
PlÀeqÀb ¼ VeqÀt  IeqÀb (2)
3.2. 3-Level power conversion system
The conduction losses Pc are comprised of losses in the IGBTs
and diodes. The conduction losses for each switch can be calculated
by (3) [32,33]
Pc ¼ U0Iavg þ rf i2
rms (3)
where U0 is the forward voltage drop with zero current, rf is the
forward resistance, Iavg is the average current and irms is the root-
means-square of the current.
Figs. 3 and 4 summarize all possible power paths and switching
states in the 3-level PCS. The load current Iom(t) ¼ Iomsin(ut À f)
and phase leg voltage as Vo(t) ¼ Vomsinut, and the duty cycle across
the switching devices as:
dT11 ¼
&
M sin ut 0 ut p
0 p ut 2p
(4)
dT12 ¼
&
1 0 ut p
1 þ M sin ut p ut 2p
(5)
dT13 ¼ 1 À dT11 (6)
dT14 ¼ 1 À dT12 (7)
The average and rms currents in IGBTs T11 and T14 of the 3-level
PCS are calculated as follows [32]
I3ÀlvlÀPCS
T11;avg ¼ I3ÀlvlÀPCS
T14;avg ¼
1
2p
Zp
0
dT11iomdut
¼
MI3ÀlvlÀPCS
om
4p
½sinj4j þ ðp À j4jÞcos 4Š (8)
I23ÀlvlÀPCS
T11;rms ¼ I23ÀlvlÀPCS
T14;rms ¼
1
2p
Zp
0
dT11i2
omdut
¼
MI23ÀlvlÀPCS
om
4p
1 þ
4
3
cos 4 þ
1
3
cosð24Þ
!
(9)
Fig. 2. Thevenin equivalent representation of the BS.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169 161

5. where I3ÀlvlÀPCS
om is the peak current of the output current; 4 is the
phase difference between output voltage and current; M is the
modulation index
The average and rms currents in IGBTs T12 and T13 of the 3-level
PCS are calculated as follows [32]
I3ÀlvlÀPCS
T12;avg ¼ I3ÀlvlÀPCS
T13;avg ¼
1
2p
2
6
4
Zp
0
iomdut þ
Zpþ4
p
dT12iomdut
3
7
5
¼
I3ÀlvlÀPCS
om
p
À
MI3ÀlvlÀPCS
om
4p
½sinj4jÀj4jcos 4Š (10)
Fig. 3. Current direction in one leg of 3-level PCS.
Fig. 4. The switching states of 3 level PCS.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169162

6. I23ÀlvlÀPCS
T12;rms ¼ I23ÀlvlÀPCS
T13;rms ¼
1
2p
2
6
4
Zp
0
i2
omdut þ
Zpþ4
p
dT12i2
omdut
3
7
5
¼
I23ÀlvlÀPCS
om
4
À
MI23ÀlvlÀPCS
om
4p
1 À
4
3
cos 4 þ
1
3
cosð24Þ
!
(11)
In principle the diodes from D11 to D14 don't carry any current,
because the current of T11 commutes to D15, the current of T14
commutes to D16 and the current of T12 commutes to T13. This is
demonstrated in Ref. [21].
The average and rms currents in diodes D15 and D16 of the 3-
level PCS are calculated as follows [32]
I3ÀlvlÀPCS
D15;avg ¼ I3ÀlvlÀPCS
D16;avg ¼
1
2p
2
6
4
Zp
0
dT13iomdut þ
Zpþ4
p
dT12iomdut
3
7
5
¼
I3ÀlvlÀPCS
om
p
À
MI3ÀlvlÀPCS
om
4p
½ðp À 24Þcos 4 þ 2 sinj4jŠ
(12)
I23ÀlvlÀPCS
D14;rms ¼ I23ÀlvlÀPCS
D15;rms
¼
1
2p
2
6
4
Zp
0
dT13i2
omdut þ
Zpþ4
p
dT12i2
omdut
3
7
5
¼
I23ÀlvlÀPCS
om
12p
½3p À 6M À 2M cosð24ÞŠ (13)
By substituting the current through T11 or T14 of the PCS into
(3), the conduction loss for T11 and T14 becomes [34]
P3ÀlvlÀPCS
c;T11T14 ¼ 2 Â
Ui0I3ÀlvlÀPCS
T11=T14;avg þ rif I23ÀlvlÀPCS
T11=T14;rms
(14)
where Uio and rif is the forward voltage and resistance of the IGBT
respectively.
In a similar manner the conduction losses of T12 and T13 of the
PCS is
P3ÀlvlÀPCS
c;T12T13 ¼ 2 Â
Ui0I3ÀlvlÀPCS
T12=T13;avg þ rif i23ÀlvlÀPCS
T12=T13;rms
(15)
Similarly, the conduction losses of D15 and D16 of the PCS is
P3ÀlvlÀPCS
c;D15D16 ¼ 2 Â
Ud0I3ÀlvlÀPCS
D15=D16;avg þ rdf I23ÀlvlÀPCS
D15=D16;rms
(16)
where Udo and rdf is the forward voltage and resistance of the diode
respectively.
Using (14)e(16), the total conduction losses can be determined
by
P3ÀlvlÀPCS
c ¼ 3
P3ÀlvlÀPCS
c;D15D16 þ P3ÀlvlÀPCS
c;T11T14 þ P3ÀlvlÀPCS
c;T12T13
(17)
where fsw is the switching frequency of the PCS; ER is the recovery
energy of the switch.
The major switching losses of a pn-diode are primarily due to
the turn-off losses since the turn-on losses are negligible as
compared to the turn-off loss. The energy dissipation at turn-off is
dependent on the charge stored in the depletion region and not lost
due to internal recombination. During the reverse recovery, the
current flows in the reverse direction while the diode remains
forward biased, and this results in a high instantaneous power loss
in the diode. Under the assumption of a linear loss model for the
diodes, the switching loss of the diodes D15 and D16 is given by
(18).
P3ÀlvlÀPCS
sw;D15D16 ¼
2fSWESR
p
$
Vdc2
Vref;d
$
Idc1
Iref;d
(18)
where fsw is the switching frequency of the PCS, ESR signifies the
rated switching loss energy given for the reference commutation
voltage and current Vref,d and Iref,d, while Vdc2 and Idc1 indicate the
actual commutation voltage and current respectively.
In a similar manner, the switching loss of the IGBTs T11 and T14
is given by
P3ÀlvlÀPCS
sw;T11T14 ¼
2fSWðEON þ EOFFÞ
p
$
Vdc2
Vref;i
$
Idc1
Iref;i
(19)
The reference commutation voltage and current for the IGBT is
Vref,i and Iref,i respectively. EON and EOFF signifies the turn-on and
turn-off energies of the IGBT as can be found in the datasheet.
The total switching losses can be calculated as
P3ÀlvlÀPCS
sw ¼ 3
P3ÀlvlÀPCS
sw;D15D16 þ P3ÀlvlÀPCS
sw;T11T14
(20)
There the total power loss of the 3-level PCS can be found as
P3ÀlvlÀPCS
l ¼ P3ÀlvlÀPCS
sw þ P3ÀlvlÀPCS
c (21)
So the total power losses of the of the battery and 3-level PCS
can be determined by using (2) and (21) as.
PESS
l ¼ PlÀeqÀb þ P3ÀlvlÀPCS
l (22)
4. Efficiency calculation
The power condition for grid connected ESS typically does not
require a DCeDC converter for the grid-connected PCS. Because of
the high voltage output of the lithium e ion battery that is capable
to supply enough voltage to the PCS input for a proper injection of
sinusoidal voltage and current in the grid.
In order to calculate the efficiency of the systems, the relation
between the operating point and power generation/loss is needed.
Each of the battery string is composed of 35 battery module con-
nected in series, hence the power generation, Pg of the ESS is
expressed as.
Pg ¼ ViIi¼w1Àwn
i
(23)
where wi represents a particular battery module for and Pgi rep-
resents the power generation for wi battery module. Vi and Ii
represent the voltage and current for wi module respectively. The
power loss of each system can be found as described in Section IV
and the total power loss is mathematically expressed as
Pl ¼
PESS
li
i¼w1Àwn
(24)
The global efficiency, h of the ESS is then calculated as,
h ¼
Pgi À Pli
Pgi
 100% (25)
5. Reliability calculation
Reliability is the probability that a component will satisfactorily
perform its intended function under given operating conditions.
The average time of satisfactory operation of a system is the Mean
M. Arifujjaman / Renewable Energy 74 (2015) 158e169 163

7. Time Between Failures (MTBF) and a higher value of MTBF refers to
a higher reliable system and vice versa. As a result, engineers and
designers always strive to achieve higher MTBF of the power
electronic components for reliable design of the power electronic
systems. The MTBF calculated in this paper is carried out at the
component level and is based on the life time relationship where
the failure rate is constant over time in a bathtub curve [35]. In
addition, the system is considered repairable. It is assumed that the
system components are connected in series from the reliability
standpoint. The lifetime of a power semiconductor is calculated by
considering junction temperature as a covariate for the expected
reliability model. The junction temperature for a semiconductor
device can be calculated as [36].
TJ ¼ TA þ PlRJA (26)
Pl is the power loss (switching and conduction loss) generated
within a semiconductor device and can be found by replacing the Pl
from the loss calculation described in Section 3 for each
component.
The life time, L(Tj) of a semiconductor is then described as
L
À
TJ
Á
¼ L0 exp
À
ÀBDTJ
Á
(27)
where,
L0 is the quantitative normal life measurement (hours) assumed
to be 1 Â 106
B ¼ EA/K, K is the Boltzman's constant which has a value of
8.6 Â 10À5
eV/K, EAis the activation energy, which is assumed to
be 0.2 eV, a typical value for semiconductors [37].
DTJ is the variation of junction and ambient temperature and can
be expressed as
DTJ ¼ TA1 À TJ1 (28)
The failure rate, l is described by
l ¼
1
L
À
TJ
Á (29)
The global failure rate, lsystem is then obtained as the summation
of the local failure rates, li as:
lsystem ¼
XN
i¼1
li (30)
The Mean Time Between Failures, MTBFsystemand reliability,
Rsystem of the system are given respectively by
MTBFsystem ¼
1
lsystem
(31)
Rsystem ¼ eÀlsystemt
(32)
In addition to the above mentioned method, a partial stress
prediction method is used to calculate the reliability of the battery
resistor. The method calculates the failure rate of any component by
multiplying a base failure rate with operational and environmental
stress factors (electrical, thermal etc). It is assumed that the battery
carries a continuous duty cycle operation. The power loss in resistor
can be found from (2) and based on this value, a commercially
available resistor is selected and the stress ratio, S is calculated as
the ratio of the operating power to the rated power of the resistor.
The base failure rate, gb is than calculated as [24]
gb ¼ 4:5 Â 10À9
exp
12
Tv þ 273
343
exp
S
0:6
Tv þ 273
273
(33)
where Tv is the ambient temperature (C) and S is the stress factor.
The failure rate for a wire wound resistor is given by Ref. [24]
gR ¼ gbpRpEpQ Â 1 Â 10À6
failure=hour: (34)
where the resistance factor, pR is 1 as the external resistance is less
than 1 MU. The environmental factor, pE is 1 due to the fact that a
harsh environment is not considered, and the quality factor, pQ is
considered to be 15 due to the use of a commercial resistor.
6. Cost calculation
The preliminary cost of the energy storage system is calculated
based on the available market price of each equipment. The ESS is
considered to build on a module concept where each of the mod-
ules would perform a specific assigned task. Moreover, the modules
will be connected to each other through a detail integration plan.
The cost of ESS is subdivided into 7 sections based on modules and
work load for integration. A short description of each of the section
is presented below:
1. PCS: The PCS mainly comprised of inverter and related switch-
gear. It is assumed that the inverter supplied by a manufacturer
that includes related circuit breaker, fuse and other accessories
that is required for proper protection of the utility and personal.
The cost of the PCS, PCScost is calculated from individual com-
ponents and expressed as a percentage of the total system cost, Tsc
and given by (35)
PCScost½%Š ¼ 16:1Tsc (35)
2. Battery: The battery section holds the battery string, BMS and
necessary DC fuse and breaker and expressed by
Bcost½%Š ¼ 57:4Tsc (36)
3. Electrical System Module (ESM): The ESM integrates PCS, su-
pervisory and local controller, fans and etc. The ESM also in-
tegrates the auxiliary power and other components as required
to perform the essential task. The cost of the ESM is calculated as
ESMcost½%Š ¼ Filtercost þ Aux Transcost þ Contr:cost þ Contac:cost
þ Power_supcost þ Fusecost þ Conncost ESMcost½%Š
¼ ð0:2 þ 0:27 þ 6:05 þ 1:15 þ 0:35 þ 0:18 þ 0:92ÞTsc
(37)
4. Harness: Each of the section within the ESS would be connected
to each other using harness assembly for ease of integration and
testing purposes
Hcost½%Š ¼ 1:8Tsc (38)
5. HVAC: The HVAC section includes the gas suppression system,
ventilation and others as required for proper safety of a
personal.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169164

8. HVcost½%Š ¼ 4:6Tsc (39)
6. Mechanical: The mechanical system comprised of any base that
is required to place the ESM, battery, panel doors and others as
required for the ESS
MCcost½%Š ¼ 4:6Tsc (40)
Labor: The labor considered for a personal to integrate the point
to point wiring of the modules.
LAcost½%Š ¼ 6:4Tsc (41)
7. Results and discussions
The analytical calculations illustrated in the preceding sections
were carried out to determine the total power generation/losses,
efficiency, MTBF and consequently reliability of the ESS under
varying operating conditions. The rated power for the ESS is
assumed to be 1 MW/500 kWh. The PCS switching frequency is
considered as 3 kHz and to investigate the worst-case scenario of
the power loss in this numerical calculation study, the modulation
index is assumed unity and load current is assumed in phase with
the output voltage. In addition, it is well understood that typically
an ESS operates based on the frequency signal from the dispatch
center and it is very difficult to pre assume a well operating
Fig. 5. Power loss as a percentage of rated power for a) Battery system, b) Power conversion system.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169 165

9. condition. However, in order to achieve economic feasibility, it is
extremely important to investigate the reliability at rated power
level. Generally rated power of an ESS is considered before
deployment of an ESS even though the ESS may operate fraction of
the rated power for most of the time of the year. As a result, to
emulate the worst case scenario, reliability at rated power level is
an important aspect from a system for high penetration of energy
storage to the utility. This realistic assumption leads to determine
the reliability for a power level of 1 MW/500 kWh. The thermal
model of the battery and PCS is neglected provided that the heat
sink is adequate enough to maintain the battery/semiconductors
proper working. Power wasted in the power supplies for the control
of the converters is also ignored (It may be between 1 kW and
5 kW). The analytical calculation is based on the Semikron IGBT
module SKiiP 1213 GB123-2DFL V3 [38].
The power loss of the battery for 10%e100% of rated power of
the ESS is presented in Fig. 5a. Higher values of power results in
high power losses and vice versa while charging and discharging
state of the battery. It is assumed that the resistance is unchanged
during charging and discharging state. The corresponding con-
duction and switching losses as well as the total power loss of the
PCS is presented in Fig. 5b for a similar operating condition. The
results of the power losses for both battery and PCS is higher as
soon as the ESS shifts the operating point from low to high regime.
It has been found that the maximum power loss at rated power
level for battery and PCS of the ESS are 130 kW and 16 kW
respectively, while the total power loss of the ESS at rated power is
146 kW.
A comparison of efficiency for the battery and PCS as well as
overall efficiency of the ESS is presented in Fig. 6. The operating
conditions are the same to make a fair assumption between power
loss and efficiency. It is obvious that the battery efficiency degrades
as soon as the operating level shifts from 10% to 100% of rated
power, however, remains in the vicinity of 87% which is similar to
Fig. 6. Efficiency as a percentage of rated power for battery, power conversion system and energy storage system.
Fig. 7. Component reliability of battery and power conversion system.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169166

10. other previous literature. However, the PCS efficiency remains in
the level of 98% which is obviously justifies the appropriate use of a
3-level PCS. It is found from the previous literature that the total
harmonic distortion of the 2-level PCS is high compared to the 3-
level PCS. This is understandable as more voltage level can be ob-
tained from a 3-level PCS that would generate fewer harmonics to
the utility. The output filter requirement of a 2-level PCS is high
compared to a 3-level PCS. This requirement can also be validated
from the harmonics assumption. Dimension and cost of a 2-level
PCS is high compared to a 3-level PCS. Even though a 2-level PCS
has lower device count, nevertheless, lower rating devices can be
used for the same voltage level compared to a 2-level PCS would
make a 3-level PCS less costly and could be an optimum choice for
an energy storage system. Finally, the overall ESS efficiency is found
85% at 100% power level which is a considerable efficiency for
moving forward. Nevertheless, further research is absolutely
necessary to enhance the efficiency and the work is in progress by
the author.
Afterwards, the reliability calculation is performed following the
procedure outlined and the results are presented in Fig. 7. The
calculation reveals that the battery failure rate for the ESS is
1.39 Â 10À5
and the MTBF is 7.17 Â 104
h (8 years). The corre-
sponding figure for the PCS is 2.16 Â 10À5
and 4.64 Â 104
h (5 years)
respectively. It is well understood that the ESS needs to be afford-
able, reliable and most importantly, almost maintenance free for
the average qualified personal to consider installing one. As can be
seen, the need to replace the ESS corresponds to the MTBF value of
8 years. However, it should be kept in mind that typically; a com-
plete checkout would occur in each year by the ESS manufacturer
and in such a scenario, without any maintenance the ESS is capable
Fig. 8. Reliability of the battery, power conversion system and energy storage system a) Over a year, b) Over time.
M. Arifujjaman / Renewable Energy 74 (2015) 158e169 167

11. of a continuous duty cycle operation for around 8 years. Moreover,
the reliability calculation assumed that all the components are
connected in series, which is a very conservative estimation of
reliability. In addition, the PCS reliability is found to around 5 years
based on the previous literature which was primarily computed
form the field data [20,28,39e41]. This study confirms the results
through quantitative calculation which can be a useful tool to
extend the calculation for other PCS configuration.
It should be mentioned that besides the switches, the DC link
capacitors contribute significantly to cost, size and failure of the PCS
on a considerable scale. However, the present research work as-
sumes that the energy storage requirement to the DC link will be
reduced in such a quantity so that Aluminum capacitors could be
replaced by Metallized Polypropylene Film Capacitors to achieve
higher level of reliability without considerably increase the cost
and volume. Nevertheless an effort is undertaking by the author to
include a better design of the DC link capacitor and include the
reliability with the overall system in near future.
Fig. 8a shows the reliability of the battery and PCS for a period of
one year (8760 h) for the ESS. The result reveals that the reliability
of the battery and PCS for the ESS drops to 88% and 83% after one
year, while the reliability of the ESS drops to 73% after one year. The
reliability of the battery and PCS as well as the ESS time is presented
in Fig. 8b. It is easily noted that the reliability of the battery reaches
less than 50% at 50,000 h (5 years), while PCS maintains a lower
value of 35% in the same time frame. The reliability of the ESS re-
mains 17% which combines both performances of battery and PCS.
In both scenarios, the ESS illustrates a reasonable reliability and is
certainly a hopeful direction for the ESS manufacturer around the
globe. This would also enhance to work further on the reliability as
this research quantifies a parameter which could be a good starting
point for further research in the energy storage domain.
Afterwards, the cost calculation is performed as described in
Section 6. An initial design of individual module is performed at the
beginning with a consideration that the proper control and oper-
ation of the ESS is achieved. Fig. 9 reflects that the battery and PCS
constitute a major portion of the cost (16% and 58% respectively),
while mechanical and harness assembly (5% and 2% respectively)
has the lowest impact on the total cost. The ESM, labor and HVAC
system remains in between higher and lower end of the ESS cost. A
vigorous cost reduction of the ESS is being undertaken by the
author and left for future publication.
8. Conclusions
The power loss, efficiency, reliability and cost calculation of a
grid-connected energy storage system for frequency regulation
application is presented. Conduction and switching loss of the
semiconductor devices is used for power loss and efficiency
calculation and temperature is used as a stress factor for the reli-
ability calculation of the energy storage system. In addition, a
module based approach for the energy storage system cost calcu-
lation is presented. It is found that the system ensures lower loss
and consequently higher efficiency. Moreover, the mean time be-
tween failures is in an acceptable agreement and battery and PCS
has the highest impact on the cost of the system. It is expected that
more research will be undertaken for a more efficient and reliable
as well as lower cost system in near future.
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