analysis and modeling of a stand-alone power system for the ...

2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
ANALYSIS AND MODELING OF A STAND-ALONE POWER
SYSTEM FOR THE PRODUCTION OF ELECTRICAL ENERGY
WITH HYDROGEN LONG-TERM STORAGE
Dimitris Ipsakis 1,2 , Spyros Voutetakis 1 , Panos Seferlis 1,3 ,
Fotis Stergiopoulos 1 , Simira Papadopoulou 4 , Costas Elmasides 5 ,
Chrysovalantis Keivanidis 5
1 Chemical Process Engineering Research Institute (CPERI), CEntre for Research and Technology
Hellas (CERTH), P.O. Box 60361, 57001, Thermi-Thessaloniki, Greece
2 Department of Chemical Engineering, Aristotle University of Thessaloniki, P.O. Box 1517, 54124
Thessaloniki, Greece
3 Department of Mechanical Engineering, Aristotle University of Thessaloniki, P.O. Box 484, 54124
Thessaloniki, Greece
4 Automation Department, Alexander Technological Educational Institute of Thessaloniki, P.O. Box 14561,
54101 Thessaloniki, Greece
5 Sunlight Systems SA, Neo Olvio, Xanthi, 67200, Greece
ABSTRACT
This paper describes the dynamic simulation results for a Stand-Alone Power System that is
used for stationary applications. The integrated system consists of a Photovoltaic Array (PV-
Array) and Wind Generators for energy production from renewable energy sources, a
Polymer Electrolyte Membrane (PEM) Electrolyzer, a PEM Fuel Cell, a hydrogen storage
unit, a Lead-Acid Accumulator and the Power Conditioning Equipment. The results during a
two-month period revealed important information about the energy demands that cannot be
met by the renewable energy sources, also for the surplus energy, especially during midday,
when water electrolysis is possible to be supported. Futhermore, the amount of hydrogen that
is produced from the Electrolyzer and the amount of hydrogen that is required for energy
production in the Fuel Cell is taken into consideration for the design of the hydrogen storage
system. Dynamic simulations of the integrated system as a single entity after studying each
subunit separately, are to be used as the basis of developing end evaluating a “plant-wide”
model based control strategy.
1. INTRODUCTION
The use of renewable energy systems for the production of electrical energy, can contribute
significantly to the reduction of greenhouse emissions such as carbon monoxide and carbon
dioxide. The variations of the weather conditions during the year however, lead to the need of
a more complicated system that consists of many components which can contribute to the
electrical production. The introduction of integrated systems for hydrogen production through
water electrolysis, storage and utilisation in Fuel Cells, can provide an efficient means of
storing energy for medium to long term use. Hydrogen is often referred to as the energy
carrier of the future, because it can be used to store intermittent renewable energy sources
such as solar and wind energy [1]. Energy storage is needed in these systems due to the
intermittent nature of wind and solar energy. Traditionally, deep-cycle Lead-Acid
Accumulators have been used as the means of energy storage but recently Fuel Cells in
combination with an electrolyser for hydrogen generation and hydrogen storage tanks have
been considered for energy storage [2].

2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
The advantages of using PV-systems and Wind Generators to generate electricity
include the avoidance of pollutants emissions, long lifetime and low maintenance requirement
[2]. Moreover, solar and wind energy is abundant, free, clean and inexhaustible.
Previous studies on modeling of Stand-Alone Power Systems considered each
subsystem as individual. Ulleberg Ø. [3], introduced and evaluated various models for each
subsystem whereas the Wind Generator wasn’t included in the original scheme. The results
were very close to the experimental data from the implementation. Kohle et al. [4], presented
a model for a PV-Array coupled with a Wind Generator that takes into account
meteorological data and gives a daily profile of the produced energy. A dynamic model of a
PEM Electrolyzer was introduced and evaluated by Gorgun [5], whereas the simulated results
for the hydrogen production were used for the study of the storage dynamics. The Fuel Cell
characteristics were studied extensively where among others the electrical behaviour was
described by empirical equations [6] and the dynamic behaviour was described by a set of
differential equations [7]. Furthermore, Manwell J.F. and McGowan J.G. [8] developed the
KiBaM model that is used for modeling Lead-Acid Accumulators. Their model is very
accurate for different types of Accumulators as it only requires three parameters that can be
found by manufactures’ data. Moreover, other studies regarded the experience gained from
the operation of such an integrated system [9, 10].
In this study, the simulated results for each subsystem of the Stand-Alone Power
System during a two-month period will be presented. Applications scenarios were examined
in order to study the behaviour of the Lead-Acid Accumulator during the two months where
constant charges and discharges took place. Moreover, the amount of hydrogen that was
produced through water electrolysis was used for the study of the storage capacity in relation
with the amount of hydrogen that was required and consumed in the Fuel Cell unit.
2. Integrated System for the Production of Electrical Energy
An application utilizing solar and wind energy with hydrogen production through water
electrolysis, storage and utilisation in Fuel Cells is currently under development at Neo Olvio,
Xanthi in the framework of a research project with the participation of Chemical Process
Engineering Research Institute and Sunlight Systems S.A. The Renewable Energy System
consists of a PV-Array with an installed capacity of 5 kW p and three (3) Wind Generators
rated at 3kW p totally. Surplus energy is to be supplied to a PEM Electrolyzer, rated at 4.2kW p
after the demands for a 1kW constant load have been met. The hydrogen produced is to be
stored in cylinders under high pressure. In case there is a lack of energy, a PEM Fuel Cell
rated at 4kW p is going to be used to provide power. Also, in order to account for short-term
demands, a Lead-Acid Accumulator with a total capacity of 3000Ah, 48V is also used and
charged by the renewable energy sources or the Fuel Cell depending on the availability of the
renewable energy sources. A back up unit (Diesel Generator) could be used in order to cover
the electrical needs that can’t be met by the system. Its potential use however, would be
identified during the study of the system. Furthermore, power electronic converters are
employed for power management and for the integration of the various subsystems. Figure 1
represents a layout of the system developed.

2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
Figure 1: Block diagram of the proposed Stand-Alone Power System
3. Simulation of the Integrated System During a Two-Month Period
The design and analysis of the aforementioned integrated system requires detailed
mathematical models for the various subsystems in order to evaluate the performance of each
unit separately before studying the Stand-Alone Power System as a single entity. Initially,
each subsystem was modeled individually before integrating all the components in the
simulation model. Matlab ® was used as the simulation tool for the study of the integrated
system. In this paragraph, the simulated results from the operation of the integrated Stand-
Alone Power System will be presented and discussed. The basic steps of the study are the
following:
• Calculation of the output power from the PV-array and the Wind Generators for
time period equal to two (2) months.
• Calculation of the charging current, discharging current and State-of-Charge
(SOC) for the Lead-Acid Accumulator based on the developed algorithm.
• Calculation of the total hydrogen production and consumption during the two
month period.
• Study of various scenarios regarding the SOC of the Accumulator and the output
power from the Fuel Cell.
The results from the auxiliary units such as the compressor and the buffer tanks are not
presented in this study.
3.1 Renewable Energy System
The Renewable Energy System (RES) comprises the PV-Array and the Wind Generators.
Solar radiation, wind speed and temperature as a function of time are used as input data in
order to calculate the output power from the PV-array and the Wind Generators.
The relationship that describes the Current-Voltage (I-V) characteristics in a PV-System was
based on an equivalent electrical circuit that depicts the electrical phenomena during the solar
absorption from the module. This relationship is given by Eq.(1), [3]:

2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
V
pv
+ I
pv
⋅ Rs
I
pv
= I
L
− I
D
− I
sh
= I
L
− I
O
⋅[exp(
) −1]
(1)
α
where I pv , I L , I D , I sh denote the operation current, light current, diode current and shunt current
respectively in A, I o the diode reverse saturation current in A, R s the series resistance in Ω, α
the curve fitting parameter in Volt and V pv the operation voltage in Volt
The above parameters depend on the solar radiation and the cell temperature and can be easily
calculated from manufacturer’s data which are provided for the PV-modules. The power from
the PV-Array is described as known from:
P
= V pv
⋅ I
⋅η
pv pv conv
(2)
where η conv denotes the efficiency of the DC/DC converter~90-95%
The output power of the Wind Generator is given by the following equation [11]:
P
m
= c
ρ ⋅ Α
w 3
p
( λ,
β ) ⋅ vwind
⋅ηinv
(3)
2
where P m denotes the mechanical output of the turbine in W, c p the performance coefficient of
the turbine, ρ the air density in kg/m 3 , Α w the turbine swept area in m 2 , v wind the wind speed in
m/s, λ the tip speed ratio, β the blade pitch angle in deg and η inv denotes the efficiency of the
AC/DC converter~90-95%
The relationship for c p is given by equation that is based on the characteristics of the wind
turbine and can also be estimated from manufacturer’s data regarding the rotor speed in
relation with the wind speed [10]. From the above equations the power from the PV-Array
and the Wind Generators is presented in figures 2 and 3 respectively.
5000
1800
Output Power, Watt
4000
3000
2000
1000
Output Power, Watt
1600
1400
1200
1000
800
600
400
200
0
0 200 400 600 800 1000 1200 1400
Time, h
0
0 200 400 600 800 1000 1200 1400
Time, h
Figure 2: Output Power from the 5kW p Photovoltaic
System
Figure 3: Output Power from the 3kW p Wind
Generators
3.2 Lead-Acid Accumulator
The total power, P RES is calculated by the sum of the power P pv and P m . The power demand
for the Load, P load is constant throughout the year at 1kW (or the equivalent energy is
24kWh/day). The shortage or surplus power is calculated as:

2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
P = P RES
− P load
(4)
Based, on the deficit or shortage of power an Energy Management (EM) strategy was
developed and used.
Two limits of the State-of-Charge of the Accumulator are introduced: the minimum State-of-
Charge, SOC min , where power needs to be provided to the Accumulator and the maximum
State-of-Charge, SOC max , where the Electrolyzer is possible to operate. The basic steps of the
EM-algortihm are explained below.
• If P0 then the surplus power is provided to the Electrolyzer for the production of
hydrogen or to charge the Accumulator, depending on the SOC: if SOC≥SOC max then
the surplus energy is provided to the Electrolyzer as long as P≥P min,elec . If P≤ P min,elec
or if P≥ P max,elec then the spared energy is used to charge the battery.
Figure 4 presents the operation current of the Accumulator that has been calculated according
to the EM-algorithm. The negative values indicate the charging that takes place while positive
values imply the discharging due to lack of power. A very important parameter that needed to
be studied in detail was the SOC as it influences the operation of the Accumulator, of the
Electrolyzer and of the Fuel Cell. The SOC max limit was assumed to be 91% and the SOC min
limit was assumed to be 84%. The State-of-Charge of the Accumulator is given by:
SOC( t + 1) = SOC(
t)
⋅σ + I ⋅η
⋅ ( ∆t)
(5)
ac
ac
ac
where SOC is the State-of-Charge of the Accumulator in %, η ac is the efficiency factor ~95%,
Ι ac is the charging/discharging current in Α, σ ac is the discharging rate of the Accumulator and
t is the time in hr.
30
100
Current, A
15
0
-15
-30
-45
-60
State of Charge, %
98
96
94
92
90
88
86
SOCmax
-75
84
SOCmin
-90
0 200 400 600 800 1000 1200 1400
Time, h
82
0 200 400 600 800 1000 1200 1400
Time, h
Figure 4: Operation Current during the twomonth
period
Figure 5: State of Charge of the
Accumulator during the two-month period

3.3 Hydrogen Unit
2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
As was mentioned earlier, the electrolysis took place only when sufficient surplus energy
existed from the Renewable Energy System and the SOC of the Accumulator was above the
upper limit. Similarly, the Fuel Cell operated when there was lack of energy and the SOC of
the Accumulator reached the lower limit. In both cases, the hydrogen that was produced from
the excess energy at the PEM Electrolyzer and the hydrogen consumed at the PEM Fuel Cell
is given by Eq. (6).
n
H 2
=
n
c
⋅ I
n ⋅ F
⋅ n
F
(6)
where n H2 denotes the hydrogen flow rate in mol s -1 , n c the number of cells (Electrolyzer or
Fuel Cell), n the number of electrons per moles of water (n = 2), F the Faraday constant,
96485 As mol -1 , I the operation current in A (Electrolyzer or Fuel Cell) and n F the Faraday’s
efficiency (in case of the Fuel Cell the Faraday’s efficiency is used as 1/ n F ).
The operation current of the Fuel Cell was fixed in order to provide 2kW while the
Electrolyzer was able to operate from 25% to 100% of its nominal power. Figure 6 shows the
total hydrogen (production and consumption during the two month time period). Hydrogen
was stored in compressed cylinders for future use. The Van der Waals equation is used for the
calculation of the pressure inside the storage tanks [3]:
P
T
2
n ⋅ R ⋅T
n
= − a ⋅
(7)
V − n ⋅b
V
T
2
T
where Ρ T denotes the pressure in the storage tanks in bar, n the mole of hydrogen in mol, R
the universal gas constant in 0.08314 bar·lt/K·mol, T the storage tank temperature in K, V T
the storage tanks volume in lt and a,b the equation coefficients in lt 2 atm/mol 2 and lt/mol
respectively.
70000
Total Hydrogen, lt
60000
50000
40000
30000
20000
10000
0
0 200 400 600 800 1000 1200 1400
Time, h
Storage Pressure, bar
18
16
14
12
10
8
6
4
2
0
0 200 400 600 800 1000 1200 1400
Time, h
Figure 6: Hydrogen production and consumption
during the two-month period
Figure 7: Storage pressure during the twomonth
period
As can be seen from figure 7, there was a constant reduction of the pressure when the Fuel
Cell was operating and after it was stopped there was a constant pressure inside the storage
tanks. Similarly when the Electrolyzer was working, hydrogen was stored inside the tanks and
the storage pressure was increasing.

3.4 Case Studies
2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
As mentioned earlier, there were two limits taken for the State-of-Charge of the Accumulator.
These two limits were assumed for this study to be SOC max =91% and SOC min =84%. The
study of the integrated system requires an analysis of the effect of the SOC min to the system as
well as the analysis of various values of output power from the Fuel Cell. The manufacturers
recommend that a very low value for SOC min would be hazardous for the operation of the
Accumulator because it would reduce its lifetime. Furthermore, the use of the Fuel Cell at
high output power would cause the Fuel Cell to work less in order to cover the electrical
needs of the system and would increase its lifetime but this would result in higher hydrogen
consumption. In this paragraph it would be presented the effect of these two important
parameters to the Stand-Alone Power System in order to identify how SOC min and the Fuel
Cell output power affect the total amount of hydrogen after the 2-month period without taking
into consideration a cost-optimum design study. From tables 1 and 2 it is shown that the
reduction in the SOC min causes the Accumulator to discharge for longer time, while the
Electrolyzer and the Fuel Cell operate for shorter time. This results in lower hydrogen
consumption and production but the total hydrogen stored is more at the end of the two-month
time period.
SOC
limits, %
Total
Hydrogen, lt
Hydrogen from
electrolysis, lt
Hydrogen for
Fuel Cell , lt
84-91 23361 35391 72504
80-91 41164 25400 44711
76-91 47781 23559 36252
Table 1: Results for hydrogen production and consumption for three values of SOC min
SOC
limits, %
Charging
Time, h
Discharging
Time, h
Electrolysis
Time, h
Fuel Cell
Operation Time, h
84-91 564 812 88 60
80-91 568 835 61 37
76-91 566 842 56 30
Table 2: Results for the operation time of the different subsystems for three values of
SOC min
Another scenario, involved the operation power mode of the Fuel Cell. If the Fuel Cell is
considered to be studied as an individual component then higher output power leads to higher
hydrogen consumption. From tables 3 and 4 it is shown that the reduction in the output power
from the Fuel Cell causes the Accumulator to charge for shorter time and to discharge for
longer time, while the Electrolyzer operates for longer time and the Fuel Cell operates for
shorter period. This results in higher hydrogen consumption and production but the total
hydrogen stored is less at the end of the two-month time period. The final decision for the
operation mode of Fuel Cell depends upon many parameters and not only on the total
hydrogen stored and therefore needs to be studied extensively in the future.
Fuel Cell
Power, Watt
Total
Hydrogen, lt
Hydrogen from
electrolysis, lt
Hydrogen for
Fuel Cell , lt
1000 55030 34562 40006
2000 23361 35391 72504
4000 3948 41466 97992
Table 3: Results for hydrogen production and consumption for three values of the output
power from the Fuel Cell

Fuel Cell Power,
Watt
2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
Charging
Time, h
Discharging
Time, h
Electrolysis
Time, h
1000 574 803 87 69
2000 564 812 88 60
4000 530 834 100 38
Fuel Cell
Operation Time, h
Table 4: Results for the operation time of the different subsystems for three values
of the output power from the Fuel Cell
5. Conclusions
In this study, the simulated results for the various subsystems of the Stand-Alone Power
System during a two-month period were presented. When shortage of power occurred, the
Lead-Acid Accumulator provided the necessary power to the system. On the contrary, when
surplus of energy was available, the Lead-Acid Accumulator was charged and potential
operation of the Electrolyzer was possible. The applications scenarios that took place,
revealed that there was sufficient amount of stored hydrogen at the end of month. The Fuel
Cell autonomy for the stored hydrogen was calculated at approximately 19.1h, which is
equivalent to 38.2kWh (in the case of SOCmin=84% and Fuel Cell output power equal to
2kW). One important outcome of the study, was that several charges and discharges took
place during the month. This situation can be hazardous for the Accumulator as it reduces its
lifetime. Thus, in order to protect the accumulator and increase its lifetime, it is vital to
introduce a back-up Diesel Generator (DG) which would provide the system with the
necessary power when there is lack of energy.
6. Future Work
Multiple scenarios, which take into account the State-of-Charge of the Accumulator, variable
conditions regarding the renewable energy sources are going to be used for the optimization
of the system operation. The experimental results from the system operation will be examined
in contrast with the simulated data in order to form the basis for the analysis and design of a
reliable control system for the integrated energy system. New Energy management algorithms
will be developed to achieve an efficient and reliable operation of the system, under variable
supply and demand conditions. All these results will be used as the basis of developing and
evaluating a ‘’plant-wide’’ model based control strategy.
7. Acknowledgements
The financial support by the General Secretariat for Research and Technology of Greece
(Ministry of Development) is gratefully acknowledged. This study is conducted in the
framework of the research project ΑΜΘ-9.
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2nd International Conference on Renewable Energy Sources and Energy Efficiency
18 – 21, October 2007, Athens, Greece
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