Renewable energy conversion systems involve converting the available energy sources to forms which can be beneficial to the society, or group of people in question. The commonly used renewable energy sources are wind and solar energy. The systems which converts energy resources to a more useful form in the community are referred to as solar Energy conversion systems. The solar resource convertors are the earth surface, the sun heat, and the photovoltaic systems which are of our interest in this case. The above defined resource has a capacity to be used in an ecosystem technology, which will mean the power produced is in line with the environmental sustainability. To convert solar resource, one must have a solar conversion system, of which it is made up of aperture, receiver, storage, form of distribution and the control mechanism. The aperture acts as a regulator to letting in light, receiver then transforms the solar rays which may be stored intermittently before distribution. The control mechanisms perform solar regulation and distribution too, example is convertor (Renewableenergyworld.com 2018)
Wind energy comes second in the commonly harnessed renewable energy sources. Wind energy can be utilized by using wind energy conversion systems. These conversion systems are devices which when rotated by the wind energy blowing, causes a mechanical effect which can be utilized to power devices such as water pumps or generators capable of producing electrical energy. The commonly used machines are wind turbines. (Alvarenga, Costa and Lobo 1996) (Wind turbine wakes for wind energy, 2011)
The simulation and the hardware experiments are ideal for practical design of the renewable systems. Currently, there is a rapid reduction of the nonrenewable energy sources. This has made it necessary for the improvement and research on utilizing the renewable energy. The research focus is on reducing the energy loses and easy tracking of the maximum power point. An intelligent algorithm was used to monitor the irradiance of the solar. The experiment is done using simulation hardware’s, but the algorithm mimics the true outdoor solar radiation. therefore, the experiment is a representation of the solar and energy production by wind. The current and voltage analysis of these modules will also be analyzed.
Experiments on Photovoltaics
Objective of the experiment
The main objective of doing this experiment was to perform MPP tracking of the inverter’s operating point at different shadings of the solar generator.
To achieve the objective, the following procedure was followed:
Circuit provided in the practical script as shown below was assembled. The mains voltage was then turned on through the power supply CO3208-1P. the next step was to open the virtual instrument representing the solar panel. The provided settings were then performed on the hardware systems.
This involved shading a number of modules under a given irradiance as depicted on the script.
The results from the experiment were represented on the graphs below. These simulations were done under different parameters captioned
From the above experiments. The invertor outputs different total power based on the exposure to the light. It was noted that the system incorporates an intelligent algorithm which searches for a correct maximum power point for the photovoltaic systems even when they are shaded.
The power output increases linearly as the UV increases. However, the maximum UV that could be achieved for this case is between 470-485. This is a read from the graph above.
When both the two modules are shaded, the total power output from the invertor drops, this is because the surface exposed to light for the photovoltaic systems has been reduced. The reduction in the invertors power implies that the direct voltage of the invertor has reduced. To achieve a maximum power output, all the cells should always be exposed to the light. There’s a great effect that results when both the two solar are on shadow, solar cells are connected in such a way that all should contribute to the total supply, when one is in a shadow, the flow of current will be affected, hence power output will be reduced. (Kuperman, Averbukh and Lineykin 2013)
On increasing the number of modules to five, the following graphs were obtained.
Shading the photovoltaic module to 100% will automatically cause the invertor to switch off after some time. The photovoltaic invertor depends on power from the solar systems. Shading to 100% reduces the current and hence no power. The algorithm finds it difficult to locate the maximum power point when the shadow range is between 80-100 because the photovoltaics facility MPP is found outside the range of invertors mpp range.
Objective of the experiment
The main objective of doing this experiment was to perform MPP tracking of the inverter’s operating point without shading the solar generator.
To achieve the objective, the procedure used in the previous experiment was used, only that the solar generator was not shaded. The output of the solar generator was linear.
Power is calculated as follows
Pmax= VMIM
(A Review of Modelling of Photovolaic Solar Cell for Maximum Power Point Tracking, 2016)
Where the initials above represents power, voltage and current that could be produced at maximum point.
To determine the efficiency of invertor, a number of factors must be considered. Efficiency refers to the percentage of output in relation to the output of solar.
Mathematically, efficiency will be expressed follows
Where E represents the efficiency
Consider the graph below
Suppose power output from solar
=700watts
The invertors outputs 350watts, the losses might be as a result of electrical resistance among other factors
E=50%
Influence of mechanical speed on generator voltage
The goal of this experiment was to understand the relationship that exists between the frequency of a generator and its speed. This will be achieved by performing an exercise that will involve determining the generator parameter of voltages frequency ranging from 1200rpm-1400rpm in 100rpm span. A circuit was setup as described on the lab script shown in picture below.
Figure 7 figure showing the experiment setup, from class lab script
On completing the setup, the machine was powered, and the controls turned on. A three-phase grid for the control module was switched on, the transformers connection through the breaker was to remain intact. The USB interface of the DFIG was then opened and connected to the pc. The required speeds were set up ENABLE button actuated. The amplitude used was 40% with frequency 0 Hz.
The following were the results obtained,
When the mechanical speed is 1200rpm, the mechanical frequency is 40Hz and the voltage frequency is 40Hz
When the mechanical speed is 1300rpm, the mechanical frequency is 43Hz and the voltage frequency is 43Hz
When the mechanical speed is 1400rpm, the mechanical frequency is 47Hz and the voltage frequency is 47Hz
From the above results, the motor displays the characterises of a synchronous motor.
The increase in mechanical speed is linear to that of the voltage generated.
The main goal of this experiment was to understand the relationship that exist between the speed, rotor current frequency and stator frequency.
The exercises that were done were:
To determine the feed frequency needed by the rotor at frequency of 50Hz and speed of 1200rpm
Also to practice more for speed of 1300 and 1400 rpm
Figure 8 variable rotor and stator frequency experiment setup
The setup was assembled as shown above.
On completing the setup, the machine was powered, and the controls turned on. A three-phase grid for the control module was switched on, the transformers connection through the breaker was to remain intact. The USB interface of the DFIG was then opened and connected to the pc. The required speeds were set up ENABLE button actuated. The amplitude used was 40% with frequency 0 Hz.
The instrument frequency was then increased slowly to attain 50Hz frequency
The following analysis were made,
When the mechanical speed is 1200 rpm, the rotor frequency is 10Hz in order to get 50Hz frequency of the stator.
When the mechanical speed is 1300 rpm, the rotor frequency is 7Hz in order to get 50Hz frequency of the stator.
When the mechanical speed is 1400 rpm, the rotor frequency is 3Hz in order to get 50Hz frequency of the stator.
In this experiment, it was noted that:
The main objective was to understand the relationship between the rotor current and the stor voltage.
Other objectives include:
To examine the influence of rotor current on stator voltage
Investigate the influence of speed and current
Figure 9 setup on the experiment
The setup was assembled as shown above.
On completing the setup, the machine was powered, and the controls turned on. A three-phase grid for the control module was switched on, the transformers connection through the breaker was to remain intact. The USB interface of the DFIG was then opened and connected to the pc. The required speeds were set up ENABLE button actuated. Set frequency to 0Hz.
The voltages and amperage were set as provided in table.
Figure 10 graph obtained from the experiment on rotor current and stator voltage
The graph indicates the following
The main experiment goals were as stayed below
In connecting generator to the grid, some conditions must be met. The conditions are as stated below
The grid frequency must be equal to the generator frequency
The voltage produced by the generator must be equal to that produced in the grid
Both the grid and generator phase angles must be equal.
These conditions must be met in any system. Failure to meet the conditions might cause high compensation needed for the currents. However, the results may be catastrophic as the components could be damaged. during our experiment, a software was used to monitor the experimental plant connection.
The following exercises were performed:
Rotor current was setup together with frequency so as to enable it be connected to the grid
The synchronization to grid was performed at different speeds
Allow the generator to synchronize with grid under given parameters automatically
On completing the setup, the machine was powered, and the controls turned on. A three-phase grid for the control module was switched on, the transformers connection through the breaker was to remain intact. The USB interface of the SYNCHRONIZER was then opened and connected to the pc. The required speeds were set up ENABLE button actuated.
The speed control was then set to 1200rpm and the actuator valve was enabled.
The following settings were then,
On completing, the system was turned on. the generator was therefore connected to the grid.
the phase shift between the generator and the grid could be adjusted if both the frequencies of grid and generator are similar. To adjust the phase angle, some changes on the might be done on the frequency of the generator. The current of the generator rotor has an effect to that on the grid, this is because it has an influence on generators voltages magnitude
the synchronization was repeated for speeds of 1300rpm and 1400rpm
The following comparisons of generator when offline and in online modes were made
The voltage of generator when in online is equal to the voltage from the grid
As the generator voltage increases, the other parameters have to be monitored in order to achieve synchronization with the grid.
The voltages of the generator and the grid have different characteristics of amplitude, phase angles and frequency.
The simulation was done using a PVsyst software. The results from the simulation are as follows.
(Jones K. Chacko and Prof. K J Thomas 2015)
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The simulation parameters of the given system were as follows Title of Project: GRID CONNECTED PROJECT SIMULATION Location of the simulation Doncaster United Kingdom statistics Latitude 53.5°N time definition of the location Legal Time Time zone UT Albedo 0.20 mereological data: Doncaster |
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Simulation variant: the simulation is based on class parameters Date of simulation |
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Simulation parameters Collector Plane Orientation 30° Azimuth 0° Models used Pérez Diffuse Erbs, Metronome Horizon Near Shadings PV Array Characteristics PV modulePoly 250 Wp 60 cells Original PVsyst database Made by type Total quantity Photovoltaic modules in series 8 modules in parallel 23 strings Total number of PV modules Nb. modules 184 power produced 251 Wp Array global power Nominal (STC) 46.0 kWp at operating cond. 41.2 kWp (50°C) Array operating characteristics (50°C) U mpp 218 V I mpp 189 A Estimated area area of the module 299 m² area of the cell 268 m² Inverter characteristics Model UNO-7.6-OUTD-US-S-A (277V) Sourced from the simulator library made by ABB Features voltage output 120-530 V power of single invertor 7.60 kWac Inverter pack Nb. of inverters 9 * MPPT 50 % Total Power 34 kWac Loss factors of the photovoltaic Losses due to thermal effect Uc (const) 29.0 W/m²K Uv (wind) 0.0 W/m²K / m/s Losses due to Resistance of wires Global array res. 20 mOhm Loss Fraction 1.5 % at STC Loss of the whole module Loss Fraction -0.8 % Losses due to mismatch of module Loss Fraction 1.0 % at MPP The factors in incidence of simulation, Parametrization IAM = 1 – bo (1/cos i – 1) bo Param. 0.05 User’s needs: Unlimited load (grid) |
Orientation of the photovoltaic module
PV modules 250 Wp
Photovoltaic system arrays number of modules used 46.0 kWp
Inverter Model 7.60 kW ac
Inverter pack Nb. of units 34.2 kW ac
User’s needs Unlimited load (grid)
Main results, and the balances
|
Globo |
T Amb |
GlobInc |
GlobEff |
EArray |
E_Grid |
EffArrR |
EffSysR |
|
|
kWh/m² |
°C |
kWh/m² |
kWh/m² |
MWh |
MWh |
% |
% |
|
|
June |
146.9 |
15.09 |
145.1 |
139.8 |
6.006 |
5.735 |
13.83 |
13.21 |
|
July |
142.8 |
16.82 |
144.7 |
139.8 |
5.878 |
5.610 |
13.57 |
12.96 |
|
August |
107.7 |
17.02 |
115.7 |
111.8 |
4.795 |
4.571 |
13.85 |
13.20 |
|
September |
89.9 |
14.40 |
110.6 |
107.0 |
4.602 |
4.398 |
13.91 |
13.29 |
|
October |
49.0 |
11.24 |
71.6 |
69.1 |
3.107 |
2.961 |
14.50 |
13.82 |
|
November |
25.9 |
7.35 |
46.2 |
44.5 |
2.054 |
1.953 |
14.85 |
14.13 |
|
December |
17.1 |
4.74 |
38.1 |
36.6 |
1.717 |
1.632 |
15.05 |
14.30 |
|
Period |
579.3 |
12.38 |
671.9 |
648.6 |
28.159 |
26.861 |
14.00 |
13.36 |
Legends: GlobHor Horizontal global irradiation EArray Effective energy at the output of the array
T Amb Ambient Temperature E_Grid Energy injected into grid
GlobInc Global incident in coll. plane EffArrR Effic. Eout array / rough area
GloebEff Effective Global, corr. for IAM and shadings EffSysR Effic. Eout system / rough area
Parameters of the simulation sytem System type
PV Field Orientation
PV modules 250 Wp
PV Array Nb. of modules 46.0 kWp
Inverter Model 7.60 kW ac
Inverter pack Nb. of units 34.2 kW ac
User’s needs Unlimited load (grid)
(Kumar et al. 2017)
Figure 12 loss diagram over the year
The efficiency of the solar invertor will be calculated as follows
E= -4.5% as read on loss diagram above
(Takeda and Motohiro, 2010)
Conclusion
The following conclusions were made during the experiment and simulation
References
A Review of Modelling of Photovoltaic Solar Cell for Maximum Power Point Tracking. (2016). International Journal of Science and Research (IJSR), 5(4), pp.2462-2464.
Jones K. Chacko and Prof. K J Thomas (2015). Analysis of Different Solar Panel Arrangements using PVSYST. International Journal of Engineering Research and, V4(04).
Korecko, J., Jirka, V., Sourek, B. and Cerveny, J. (2010). Module greenhouse with high efficiency of transformation of solar energy, utilizing active and passive glass optical rasters. Solar Energy, 84(10), pp.1794-1808.
Kumar, N., Kumar, M., Rejoice, P. and Mathew, M. (2017). Performance analysis of 100 kWp grid connected Si-poly photovoltaic system using PVsyst simulation tool. Energy Procedia, 117, pp.180-189.
Kuperman, A., Averbukh, M. and Lineykin, S. (2013). Maximum power point matching versus maximum power point tracking for solar generators. Renewable and Sustainable Energy Reviews, 19, pp.11-17.
Renewableenergyworld.com. (2018). Renewable Energy World Home. [online] Available at: https://www.renewableenergyworld.com/index.html [Accessed 14 Dec. 2018].
Takeda, Y. and Motohiro, T. (2010). Requisites to realize high conversion efficiency of solar cells utilizing carrier multiplication. Solar Energy Materials and Solar Cells, 94(8), pp.1399-1405.
Wind turbine wakes for wind energy. (2011). Wind Energy, 14(7), pp.797-798.
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