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Charging Station for Electric Vehicles

VIEWS: 3 PAGES: 25

									Charging Station for Electric Vehicles



   Nordic Folkecenter For Renewable Energy




                    June 2008
               Jessica Grove-Smith
INTRODUCTION .............................................................................................3

WIND ENERGY ...............................................................................................5

SPECIFICATIONS.................................................................................................5
WIND TURBINE ...................................................................................................5
INVERTER ..........................................................................................................6
EXPECTED ENERGY PRODUCTION .......................................................................7
POWER CURVE ..................................................................................................7
WIND DISTRIBUTION .........................................................................................11
ENERGY PREDICTION ........................................................................................13

SOLAR ENERGY ..........................................................................................14

SPECIFICATIONS...............................................................................................14
PV PANELS ......................................................................................................14
INVERTER ........................................................................................................15
EXPECTED ENERGY PRODUCTION ......................................................................16
THEORETICAL PREDICTION ................................................................................16
EXPERIMENTAL RESULTS...................................................................................17
A COMPARISON: THE “SUNFLOWER”.................................................................21

ELECTRIC VEHICLE CHARGING ................................................................22

DATA MONITORING AND DISPLAY ...........................................................23

CONCLUSION...............................................................................................25




                                                                                                                  2
Introduction
In today’s world transportation is a major polluter and energy consumer.
People have become used to regularly travelling long distances to work or just
for pleasure and modern lifestyles are often arranged around the permanent
availability of relatively cheap transport options. The current habits and
technologies are not sustainable and solutions need to be found to minimise
the environmental impact as much and as soon as possible. One of them is
the electric car.

The concept of electric vehicles has a very big potential for future applications
- especially if charged on renewable electricity - as they can provide pollution-
free 1 transportation for the main part of the population’s travel needs. The
technologies of electric motors and batteries are already well established;
they are now being adapted and developed further in order to produce higher
energy efficiencies and larger effective capacities. Some people are worried
about the limited range of electric cars, the required charging time or the
maximum available speed. Advancement of technology will lessen the
magnitude of these “problems”. At the same time a range of concepts are
being suggested and introduced for an efficient and clean transport system
based on electricity. This includes, for example, battery leasing (Th!ink’s
“Mobility Pack”), charging stations with battery replacement facilities, vehicle
to grid charging etc.

The use of electric cars as a replacement for the currently used vehicles
based on fossil fuel will only then imply a significant pollution reduction if the
energy used to charge the new cars is produced from renewable sources. 2 As
with every new technology, a big step in achieving a successful changeover
from an old and well-established product is public awareness and genuine
acceptance and interest in the new device. For demonstration and awareness
raising purposes, a renewably powered electric charging station that
incorporates both wind a PV technology, was set up at the Nordic
Folkecenter. This charging station is an information point for all visitors – an
incentive for people to consider electric vehicles as a promising future
transport option.

The beauty of the installed charging station also lies within the simplicity of the
underlying idea: The combination of two complementing renewable energy
sources for energy production all year round. This concept can be applied to a
wide range of applications of which Folkecenter’s charging station for electric
cars is only one example. As is the case here, the system can be connected
to an electricity grid (national or local). Alternatively, batteries could be used
for energy storage, thereby creating a 100% autonomous power production
facility. The scale can be as small or even smaller than demonstrated at the
centre or be increased to much larger sizes. The dimensions and connection


1
 Not taking into account the pollution caused during the entire lifetimes of all components.
2
 “Do Electrical Cars make sense in Denmark?” written by Folkecenter trainee Melissa
Valgardson. Published on the centre’s website.


                                                                                               3
type depend on the specific use - but energy collected from the sun and wind
will complement one another in the wider context of every system.

This report was written with the aim of giving an introduction to the individual
components that make up Folkecenter’s charging station and their initial
performance. It lists the specifications of the main parts and explains how
performance monitoring and calculations were carried out. Where known the
part numbers are given in square brackets. Additional information has been
collected in a folder for easy access, so that any person wanting to work with
the system won’t have to spend time on researching instruction manuals.
Most documents and files are also saved on the centre’s server (Trainees
Completed Work\Integrated Systems\Charging Station). The prepared
Mathcad files can be used for future data analysis in order to monitor the
system’s performance and verify the energy predictions made in this report.




                                                                                   4
Wind Energy

Specifications

Wind turbine

LAKOTA (Aeromag Corporation)

Rotor diameter:                   2.09 m
Swept area:                       3.43 m2
Rated power output:               900 W (at 12.9 ms-1)
Peak power output:                1500W (at 17 ms-1)


The incoming signal from the turbine passes through a commander box where
it is rectified before being sent to the inverter. The commander also ensures
that the maximum inverter input voltage is not exceeded, by sending any
incoming signal above a certain voltage to a dump load (two 1000W, 0.75Ω
resistors connected in series [ASE1000.075]). This voltage limit is controlled
by the load diversion regulator [LDR 48-30], which can be adjusted with a
potentiometer. In the current configuration the potentiometer is set to approx
59V corresponding to the inverter’s properties. A brake is installed in the
commander before signal rectification (careful, the OFF-positions refers to the
brake being turned off, meaning that the turbine is turned on!). The turbine
automatically tilts backwards for overspeed protection and should therefore be
able to withstand quite high wind speeds without having to be stopped
manually.

The turbine was previously connected to a 24 V battery bank for which the
diversion limit had to be significantly lower. As this is not within the normal
range of the potentiometer the addition of two cables in the commander, as
shown in the pictures below, was used to halve the voltage.




          Cables used to halve
          the diversion voltage




                          LDR




                                                          potentiometer
                                                                                  5
Inverter

Windy Boy WB 1100LV (SMA Technologie AG)

Nominal output power:           1000 W
Maximum output power:           1150 W
Maximum input voltage:          60 V
Maximum input current:          62 A
Maximum efficiency:             92 %


Creating a stable electrical signal from the constantly varying power output of
a small wind turbine is not an easy task, which is why there are not many
suitable inverters on the market at the moment. It is much more common to
connect small turbines to a battery bank for energy storage. This is the first
time a small turbine has been connected to the grid at the Folkecenter. The
Windy Boy installed in the charging station is the smallest in the wind turbine
inverter range offered by SMA and so far (for it’s operating time of four
months) it has worked very satisfactorily without any problems.



                                 Windy Boy Efficiency

               100%
                90%
                80%
                70%
  Efficiency




                60%
                50%
                40%
                30%
                20%
                10%
                 0%
                      0   200      400       600        800       1000       1200
                                         AC Power [W]




The above graph depicts the inverter’s efficiency over a range of output
power. The data was recorded during a windy day (maximum one-minute
average wind speed of 14.8 m/s) and covered almost the entire power range
of the inverter. The overall efficiency for this day was 88.29 %.




                                                                              6
Expected Energy Production

Many factors will influence the annual wind energy contribution of the
charging station and before the system has been monitored over a long
period of time all production values are based on assumptions and
predictions. Theoretically, the energy produced can be calculated by
multiplying the wind turbine’s power curve with the local wind distribution.
Taking into account the inverter’s limited efficiency will then allow the
determination of the amount of energy fed into the grid and available for car
charging.


Power Curve

The power curve foremost depends on the turbine’s fixed properties. The
rated power output of the installed turbine is 900 W, which it should reach at
around 13 m/s according to the manufacturer’s specifications. To ensure
production to the turbine’s full capacity for a wide range of wind speeds the
Windy Boy inverter has an internal voltage versus power curve, which can be
adjusted by the user. It is called the “Characteristic Curve” and the device is
delivered with a typical setting for small turbines. It is described by the
following parameters: 3


Parameter                Definition
                         Defines the voltage at the moment when the Windy Boy is ready to perform
U.PVStart [V]            grid synchronization.
                         Defines the voltage at the moment when the Windy Boy begins to feed power
U.DCWindStart [V]        into the mains grid, and begins to extract power from the turbine.
U.DCWindMid [V]          Defines the voltage threshold, after which the curve climbs more steeply.
                         Defines the voltage at the moment when the Windy Boy begins feeding
U.DCWindMax [V]          maximum power into the grid.
P.WindMid [W]            Defines the power threshold, after which the curve climbs more steeply.
                         Reduces the Windy Boy's maximum output power to adapt to wind turbines
P.WindMax [W]            with lower output power.



Different settings were tested under different wind conditions and
subsequently analysed with Mathcad (DataAnalysis1). The file is available for
review and future use on Folkecentre’s server. It requires the input of two text
files, one containing the wind speed data (one minute average) and another
that contains the data collected from the turbine (recorded every 10 seconds).
The Mathcad file sorts the averaged data into wind and voltage bins and then
graphically displays the turbine’s resulting power curve, efficiency coefficient
and characteristic curve. An output file is created in order to facilitate further
analysis and comparison of the data. A different Mathcad file
(DataComparison1) was created for comparison of the turbine’s performance
under different conditions. It imports the experimental results from selected

3
    As defined in the manual.


                                                                                                     7
dates and then graphically displays the data. Some results from these two
Mathcad files are presented on the following pages to show how the turbine
reacted to different Characteristic Curve settings.

The approach used to find the optimal setting was to match the curve to the
actual output produced by the turbine. Determining the optimal setting was not
as simple as it seemed at first because the wind conditions were obviously
different for every set of data recorded. As it turned out in the end, the original
setting had already been fairly adequate (red coloured data in graphs). The
final setting is very similar to the slightly more efficient first correction made to
the parameters (dark blue data set recorded on March 21st) but with a
reduced grid feeding starting voltage U.DCWindStart of 21 V (as for the light blue
data set). This reduction allows for power production at lower wind speeds.
When looking at the raw data it becomes clear that the turbine could actually
produce power at even lower wind speeds. But when the Characteristic Curve
was adjusted for this property by lowering U.DCWindStart and U.PVStart, the load
became too large at higher wind speeds causing the maximum power
production to be strongly limited (green graph). Different settings were tested
in order to counteract this effect but none of them were successful so they are
not included in this report. Giving the curve a steeper gradient also had an
overloading effect (pink data).


                                               Power Curve
                     800




                     600
         Power [W]




                     400




                     200




                      0
                           0              10                 20           30

                                           Wind Speed [m/s]
                               original
                               21.03.
                               27.04.
                               14.05.
                               28.05




                                                                                   8
                                                Efficiencies
                              1
                                           3
Efficiency coeffiecient Cp

                             0.8



                             0.6



                             0.4



                             0.2



                              0
                                   0           10                 20

                                               Wind Speed [m/s]




                                               Voltage Curves
                             50
                                       2



                             40
  DC Voltage [v]




                             30



                             20
                                                                       16

                             10



                              0
                                  0            10                 20

                                               Wind speed [m/s]




                                                                            9
                                       Set Characteristic Curves - Windy Boy



                          1
      Power [P]




                         0.5




                          0
                               0                20                 40               60

                                                     Voltage [V]

The fatter black line in the two graphs displayed on this page represents the
final Characteristic Curve setting.

                                          Measured Characteristic Curves
                           1.5




                               1
             Power [P]




                           0.5




                               0
                                   0            20                 40          60

                                                     Voltage [V]




                                                                                         10
Final characteristic curve parameters:

                           Parameter         final value
                          U.PVStart [V]          20
                         U.DCWindStart [V]       21
                         U.DCWindMid [V]         43
                         U.DCWindMax [V]         57
                          P.WindMid [W]          250
                          P.WindMax [W]         1150


Unfortunately the data collected with the final setting does not cover a large
enough wind speed range to produce a complete power curve. For the
turbine’s annual energy contribution to the system, the dark blue set of data
was used, which was collected with a very similar setting.




Wind Distribution

There are two facilities for recording wind speed at the Folkecenter, one at the
front of the main building and one in the Testfield. Both are at a height of
approximately 10m. The data from the anemometer at the centre is monitored
continuously and can be used to calculate the local wind tendencies and
distribution over a chosen period of time. The most suitable set of data for
determining the wind distribution over one entire year was recorded during
2007. Only 10 days in June and 10 days in December are missing and the
entire set is composed of 10-minute average winds speeds. Ideally, the
average time should be as low as one minute for a more precise distribution
and better correspondence with the determined power curve.

Analysis of the available data was carried out using Mathcad. One file
compares the wind values at the centre and out in the Testfield
(WindComparison1) and a second file is used to calculate the wind
distribution (WindDistribution1). It turned out that the relationship between the
two sites is fairly linear with the wind values out in the Testfield being only
slightly higher, as can be seen in the top graph on the next page. The gradient
of the linear fit is 1.011 and its intercept equals 0.265.

Obviously, the actual difference for every individual value depends on factors
such as the momentary wind direction, turbulence and speed but for an
annual distribution the linear fit can be used as an average correction. The
results are displayed in the graph second graph; they clearly show the
significant effect such a small correction has on the annual distribution. For a
more accurate distribution a continuous set of wind data should be recorded
out in the testfield with one minute averaging over several years.



                                                                                 11
                                                                      Wind comparison
Wind speed in the testfield [m/s]




                                    15




                                    10




                                     5


                                                                                                         Data
                                                                                                         Linear fit
                                     0
                                         0                    5                  10                15                 20

                                                                  Wind speed at the centre [m/s]


                                                                      Wind distribution 2007
                                             0.15




                                              0.1




                                             0.05




                                               0
                                                    0                       10                          20

                                                                          Wind Speed [m/s]
                                                        data (Center)
                                                        Weibull distribution
                                                        corrected data (Testfield)
                                                        corrected Weibull distribution


                                                                                                                           12
A summary of the local wind distribution properties:

                                                         Most
            Wind Speeds [m/s]            Average                   Median
                                                       occurring
                            Data           4.88           3.8      3.8 - 4.7
        Original data
                           Weibull fit     5.12          3.19        4.57
       Corrected data       Data           5.53        3.8 - 4.7   3.8 - 4.7
         (Testfield)       Weibull fit     5.75          3.57        5.13




Energy prediction

Using the wind distribution based on the 2007 data and the previously
determined power curve for the LAKOTA leads to an annual energy
production between 1000 kWh and 1200 kWh per year.

                             Pw = 1100 kWh/year

Instead of multiplying the wind distribution value of every wind bin with the
respective amount of power produced by the LAKOTA, a multiplication with
the corresponding AC-power fed into the grid by the inverter, gives an
indication of the Windy Boy’s overall efficiency. This can then be used to
calculate how much “wind-electricity” is being fed into the grid by the charging
station, on a yearly basis.

Estimated overall inverter efficiency and AC energy production:

                                 ηWB = 86.5 %

                            PwAC = 951.5 kWh/year


Taking into account the DC production range, this final value should fall
between 865 kWh/year and 1038 kWh/year. However, these values represent
predictions based on sets of experimental data but should be confirmed after
long-term monitoring of the stable system. The final version of the
characteristic curve was set on May 30th 2008. This date should be used as a
starting point for future data analysis – the operational time and total energy
production of the Windy Boy were reset to zero at 10 a.m.




                                                                               13
Solar Energy

Specifications

PV panels

(SOLEL AS / GAIA Solar)

The PV system attached to the charging station for electric vehicles is
composed of 25 second-hand monocrystalline silicon solar panels ranging in
capacity from 37 W to 41 W with the following known properties:


Maximum power WP [W]:                          37         38          40            41
Open circuit voltageVoc [V]:                  20.3       20.1        21.4          20.6
Voltage at maximum power VP [V]:                -          -           -           14.6
Short circuit current ISC [A]:                2.8        3.1           3           3.3
Current at maximum power Ip [A]:                -          -           -           2.8
Minimum number of panels:                       3          4           1             -
Area [m2]:                                    0.41       0.41        0.41          0.41


The 25 panels cover a total area of 10.25 m2. For 17 of these panels,
however, the peak power output is not specified. For most of them the
measured open circuit voltage at midday is so high that they are likely to be
able to produce around 40 W, which sums up to a total system capacity of
around 980 W. The system faces south and is mounted at an angle of 30°.
The panels are all connected in series.

In theory, the efficiency of the entire array should be around 10%. However,
the actual efficiency is expected to be a little lower due to the age of the cells.
The only way to determine this is to compare the production with the
momentary incoming solar radiation. This process is subject to fairly high
errors, as it was difficult to determine the solar radiation at exactly the right
angle with the available equipment. The experimental values listed in the table
below result in an average efficiency of 6.28%. This value could be
determined more accurately with the recording of more precise values over a
longer period of time.


                           Inverter Input               Solar radiation     Area      Efficiency of
   Date      Current [A]    Voltage [V]     Power [W]       [W/m2]          [m2]          PV array
  06.03.08      1.21            400          484.00          850            10.25          5.56%
                1.4             410          574.00          850            10.25          6.59%
                1.3             410          533.00          850            10.25          6.12%
  21.04.08      1.4             420          588.00          920            10.25          6.24%



                                                                                                   14
                           1.55         420      651.00        960     10.25      6.62%
                           1.6          420      672.00        1000    10.25      6.56%
                           1.95         400      780.00        1100    10.25      6.92%
                           1.65         410      676.50        950     10.25      6.95%
                           1.05         400      420.00        570     10.25      7.19%
 22.04.08                  2.35         400      940.00        1380    10.25      6.65%
                           2.36         373      880.28        1380    10.25      6.22%
                                                                      Average =   6.28%




Inverter

Sunny Boy SB 1500 (SMA Technologie AG)

Nominal output power:                    1500 W
Input voltage range:                     125 - 500 V (DC)
Maximum input current:                   3-8A
Maximum efficiency:                      ≥ 96 %


The inverter operates in MPP mode (Maximum Power Point) in order to
achieve maximum power production at all times. Some of the internal values
can be adjusted by the user, e.g. the start-up and stopping voltages were set
to the allowed minimum values, which equal 140 V and 100 V, respectively.

As with the Windy Boy, the Sunny Boy’s efficiency depends on the
momentary power production. However, overall the Sunny Boy is more
efficient than Windy Boy, as can be seen in the graph below. This can be
easily explained with the fact of a much more constant and stable input signal.


                                        Sunny Boy Efficiency
                100%
                 90%
                 80%
                 70%
   Efficiency




                 60%
                 50%
                 40%
                 30%
                 20%
                 10%
                  0%
                       0          200          400          600       800         1000
                                                AC Power [W]




                                                                                          15
The data displayed in the graph on the previous page was recorded on March
23rd, a sunny day on which a production-range from 0 W to 884 W was
covered. The maximum efficiency reached on this day was 95.16% and the
overall conversion efficiency equalled 93.90%.




Expected energy production

Theoretical prediction

In order to predict how much energy the PV system of the charging station will
produce yearly, the annual solar radiation onto the panels has to be known.
For the calculations in this report a database provided in the free
downloadable software RETScreen International 4 was used. The following
table shows the relevant values from the database and the array’s resulting
monthly power production (based on a PV efficiency of 6.28% and total area
of 10.25 m2). The numbers show very clearly that a tilt of 30° leads to an
annual production increase.

                                                Daily solar radiation
                        Daily solar radiation                            Monthly power
                                      2           (south, 30° tilt)
                              [kWh/m ]                                  production [kWh]
                                                      [kWh/m2]
        January                 0.50                    1.10                 21.85
        February                1.19                    2.05                 36.98
        March                   2.32                    3.15                 62.90
        April                   3.79                    4.39                 84.79
        May                     5.19                    5.43                108.45
        June                    5.43                    5.44                104.96
        July                    5.34                    5.45                108.82
        August                  4.31                    4.77                 95.24
        September               2.78                    3.51                 67.82
        October                 1.49                    2.35                 46.86
        November                0.75                    1.65                 31.83
        December                0.40                    0.99                 19.72



The above numbers yield an expected annual production of:

                                   Ps = 790.23 kWh/year


As shown in the previous section, the efficiency of the Sunny Boy inverter is
above 90% on a long sunny day, which would imply losses of less than 10%
before the produced energy is fed into the grid. However, the production on
cloudy winter days will be a lot lower, which will dampen the overall efficiency.


4
    http://www.retscreen.net/ang/home.php


                                                                                           16
In order to make a reasonable prediction some values were recorded and
analysed with Mathcad.


Experimental results

The following graphs and numbers give an indication of daily energy
production and overall daily inverter efficiency for a selection of sunny and
cloudier days.

               PV production (DC)      Grid feeding (AC)
Date                                                          Overall efficiency
                   [kWh/day]               [kWh/day]
March 19th            4.69                    4.4                 93.74 %
March 20th            1.16                    0.98                84.07 %
March 21st            1.26                    1.05                83.28 %
April 22nd            6.91                    6.49                93.96 %
April 23rd            6.84                    6.42                93.90 %
April 24th            5.23                    4.88                93.26 %
April 25th            1.39                    1.11                79.95 %
April 26th            2.18                    1.89                86.97%
Total                  30.92                 28.27                91.43 %




                                                                                17
                                                 April 22nd, 2008
                  1000




                  800




                  600
Power [W]




                  400




                  200




                    0
                         0                        2000                    4000

                                 PV production (DC)
                                 Grid feeding (AC)



                                                      April 24th, 2008
                   1000




                    800




                    600
      Power [W]




                    400




                    200




                         0
                             0          1000            2000       3000          4000




                                                                                        18
                              April 25th, 2008
            1000




            800




            600
Power [W]




            400




            200




              0
                   0   1000    2000        3000      4000



                              April 26th, 2008
            1000




            800




            600
Power [W]




            400




            200




              0
                   0          2000                4000




                                                            19
The first graph displays visually how much energy is being lost in the inverter
at any given point in time. Overall the graphs demonstrate the energy
production on different days and the effect of clouds / shadows. The
maximum production seems to lie around 900W. At this time of year the
system starts up at around 6:15 to 6:45 a.m. and ceases to produce between
6.30 and 8:30 p.m., depending on the conditions. This corresponds to 12 - 14
operating hours per day. An interesting next step would be the comparison to
data recorded during the winter months.

A Matchcad file called YearlyProdcution was prepared, which calculates the
average daily energy production for every month and uses these values to
predict the annual energy yield and overall inverter efficiency. However, the
measurements so far have only been made on sunny days in March and April
and therefore don’t take into account the reduced production during winter
months. Calculations should be made once the system has been monitored
for a period of at least one year.

The existing data suggests in overall inverter efficiency of 91.43%. However,
the daily efficiency can be as low as 83% on less productive days. Taking into
account the winter months and more rainy seasons, the overall annual
inverter efficiency is estimated at:

                                   ηSB = 87%

This should be verified after the system has been monitored over a longer
period of time. For now, applying this estimated value to the previously
calculated annual energy production of the PV system, the amount of energy
fed into the grid and available for charging our electric car from the station is
predicted to equal:

                            PsAC = 687.50 kWh/year


The Sunny Boy installed in the charging station was previously used in a
different system. The operating hours and total energy production can
therefore not be used as an absolute reference. On March 6th 2008, when the
first set of data was recorded, the total energy processed by the inverter
equalled 3552 KWh, which had been collected during 15958.8 operating
hours. Taking this as a starting point, the inverter fed 166.9 kWh of energy
into the grid over a period of 7 weeks (April 24th). This energy was collected
during 545.6 operating hours. This corresponds to an average power
production of 305.9 W and average operation of 11 hours per day, which
would lead to an annual energy production of 1228 kWh. It will be interesting
to see how these average values change over the course of the year.

Unfortunately it was not possible to reset the Sunny Boy to fix a starting point
for the charging station system. On May 30th at 10 a.m. when the Windy Boy
was reset, the Sunny Boy had produced 3893.7 kWh of energy in a time
frame of 17027 hours.


                                                                                20
A comparison: The “Sunflower”

On May 16th 2008 a new SMA Sunny Boy was installed by the Sunflower
sculpture in the test field, to replace an old broken one. It is of the same type
(SB1500) as the one used in the charging station and the PV-array is of very
similar size, so a comparison is interesting. The following table lists the
average properties of the mono-crystalline silicon Sunflower PV-panels:


Maximum power WP:                       34 W
Open circuit voltage Voc:               10.5 V
Voltage at maximum power VP:            8.4 V
Short circuit current ISC:              5A
Current at maximum power Ip:            4A
Area of one panel:                      0.285 m2
Number of panels:                       36
Total area:                             10.26 m2
Maximum total capacity:                 1242 W


The total capacity of the system is higher than that of the PV array connected
to the charging station and the cells have a higher theoretical efficiency of
12% (not confirmed experimentally). However, the sculpture faces south-east
and is fixed at a much higher angle of around 80°, which is less advantageous
for a location in Denmark. The annual production depends strongly on the
efficiency of the cells and as this is unknown no prediction will be made within
this report.

After 8 days a first check of the production was made. At 1 o’clock in the
afternoon on a sunny spring day the system was producing 789.05 W (234 V *
3.372 A) and feeding 757 W into the grid. This corresponds to a high inverter
efficiency of 95.9 %, as expected in this power range. During the total 127
operational hours of the Sunny Boy, it had already contributed 40 kWh to the
electricity grid. This means that the inverter had been running approx 15
hours per day with an average power production of 315W. Based on these
values the system would feed 1725 kWh of energy into the grid per year.
However, as with the system installed on the charging station, these average
values will definitely go down during the less sunny seasons of the year and
therefore bring down the total annual energy production.




                                                                                21
Electric Vehicle Charging
Currently a variety of electric vehicles are available in different countries
spread of the world ranging from very simple one-person cars (e.g. Citycom
AG’s City EL) to modern sports machines (Venturi’s Fetish). A list of currently
available cars is saved on the Folkecenter’s server in an Excel file (EV list).
The next years will surely bring some changes, improvements and the
development of entirely new products but the basic technology is most
certainly already available today. Currently, the most successful models
include Norwegian based Th!nk City (Think Global) and the Indian G-Wiz
(RECC), which is used, for example, by people living and working in central
London. They are both two-seater city cars with a consumption of 16.5 and 22
kWh per 100 km, respectively. The question most relevant to this report is
how far one of these cars would be able to drive powered solely on the
renewable energy produced by the wind-solar station?

The total annual energy produced by the charging station is predicted as

                    951.5 + 687.5 = 1639     kWh/year
The table below shows how many kilometres this corresponds to for a
selection of currently available electric cars:


                            Number      Consumption       Approx. yearly
                            of seats    [kWh/100km]        range [km]
     City EL                   1              6              27,317
     Th!nk City                2            16.5             9,933
     G-Wiz                     2             22              7,450
     Example of a
                               4             15              10,927
     converted Twingo


The Th!nk represents a reasonable average value for a useful city car. The
calculated annual range corresponds to a daily distance of 27.2 km per day.
This may not cover regular long distance drives but is more than sufficient for
carrying out necessary tasks (e.g. shopping, driving to work etc.).




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Data monitoring and display
When the wind turbine was first installed the dump load control was still set to
30 V and it was unknown that the two cables described at the start of this
report were the cause of the problem. In order to avoid permanent damage to
the newly obtained Windy Boy by feeding it with a too high voltage (above
60V), the system was connected to batteries or without a load for a short
period of time. The only way of recording data was to attach a voltmeter and
ammeter at appropriate places within the turbine’s controller and manually
taking pictures as quickly as possible. This is method is very time consuming
and not very accurate as the analogue meters don’t react fast enough to the
electronic signal. However, it was good enough to establish that the turbine
was working correctly and could produce up to 1600 W at high enough wind
speeds. It also gave a first idea of appropriate characteristic curve values.

Once the dump load diversion was set correctly at 60 V, data could be
recorded directly from the inverter. SMA’s USB Service Interface cable allows
direct connection from an inverter to a computer two meters away. The
downloadable program Sunny Data then allows simple recording, data display
and export to Excel for analysis. All data used for this report was recorded in
this way. However, this setting has two major disadvantages: Firstly, it
requires the lid of the inverter to be removed during data recording, which is a
serious safety issue. Secondly, only one inverter can be connected at a time,
which makes it impossible to monitor the combined wind-solar system of the
charging station. The USB Service Interface in combination with Sunny Data
is useful for quickly establishing any SMA inverter’s current setting and
production or determining a fault but it does not offer a solution for long-term
data monitoring. For future use and reference: The data collected with Sunny
Data is saved in the local folder C:/Programmer/SMA/Sunny Data/PlantXY/,
where XY is a specified plant number. For example, Plant02 contains the data
collected from the turbine whereas Plant03 refers to the PV array.

SMA provides several options for permanent system monitoring but all of
them require the purchase of additional equipment. A list and descriptions of
the various elements can be found on their website – they range from a small
portable display to web-connected data storage devices in combination with a
weatherproof display. The easiest and cheapest option, which is adequate for
the Folkecenter’s needs, is the direct connection of the inverters to a
computer via RS485 cables. (SMA advised not to use the option of
transferring data via the simpler powerline connection due to excessive noise
in the signal.) This method allows for up to 50 inverters to be connected in
series with a maximum distance of 1.2 km from the computer where the data
is to be recorded. Every inverter has to be equipped with a RS485 piggyback
[485-PB-NR] and a conversion interface [I-7520] with an external power
supply is needed for the computer connection. For data monitoring and
display a program called Sunny Data Control is available on the SMA website,
which is slightly more advanced than the previously used Sunny Data. With
this setup, a range of useful data can now be collected continuously and
simultaneously from both inverters installed in the charging station. The
computer screen can be used effectively to show visitors not only the current


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and total energy production of the system but also the saved CO2 emissions
and graphical displays of the turbine’s and solar array’s daily or monthly
power output. At the time of writing this report the new monitoring system had
only just been installed. It was working correctly but some time should be
invested in figuring out the best settings of the new data analysis and display
programme. The location of all recorded data is the local folder
C:/Programmer/SMA/Sunny Data Control/Plants/Chargin station for EVs/.
Data is recorded once a minute and represents a one-minute average value.
This should be more accurate than the previously applied method (momentary
data recording every ten seconds) but means that all prepared Mathcad files
need to be adapted slightly before they can be used for analysis. According to
the manual, Sunny Data Control allows for access and graphical data display
using Excel from within the program (macros need to be enabled!). This will
be very useful for visitor information display but could not be tested before the
completion of this report.

If the installation of the monitoring system is successful a future project could
be the addition of further useful components. It would make sense, for
example, to permanently install a weather station in the charging station in
order to record the wind speed and maybe even the solar radiation. This data
is essential for the complete analysis of the wind turbine and PV array’s
performance. It is needed in order to calculate the LAKOTA’s power curve to
a much more accurate level than achieved in this report and also, in order to
determine the PV panel’s actual efficiency. Additionally, the wind data could
be used over a longer period of time to precisely establish the local wind
distribution. Another project suggestion is the addition of Folkecenter’s other
SMA inverters to the monitoring system.




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Conclusion
All the small experiments carried out for this report aimed at optimising the
system and confirming the newly acquired Windy Boy’s stable performance.
Repeated data analysis had the result that I gained a thorough understanding
of the system’s properties. I hope that with this report I have managed to pass
some of this knowledge on to the reader.

The poster displayed on the charging station’s container contains a set of
numbers to give Folkecenter’s visitors an idea of the amount of energy that
can be produced with such a renewably powered system and how many
kilometres this translates into on a yearly basis. The report explains where
these numbers came from - it will be interesting to see how accurate these
predictions actually are in one year’s time.




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