Solar Photovoltaic Maximum Power Point Tracking via Predictive Technique
The development of renewable energy is widely conducted as one of the initiatives to reduce carbon footprint. For this purpose, the utilization of solar energy is definitely part of it. It contributes almost none in carbon emission. Plus, this renewable source is highly targeted by the society...
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| Format: | Final Year Project Report / IMRAD |
| Language: | en en |
| Published: |
Universiti Malaysia Sarawak
2022
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/39404/2/%E2%80%98Ainaa%20Nur%20Batrisyia%20binti%20Abdul%20Rahman%20-%2024pages.pdf http://ir.unimas.my/id/eprint/39404/5/Ainaa%20Nur%20%20fulltext.pdf http://ir.unimas.my/id/eprint/39404/ |
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| Summary: | The development of renewable energy is widely conducted as one of the initiatives to
reduce carbon footprint. For this purpose, the utilization of solar energy is definitely part
of it. It contributes almost none in carbon emission. Plus, this renewable source is highly
targeted by the society that possess the awareness about the safety of our environment.
Therefore, Solar Photovoltaic Maximum Power Point Tracking via Predictive Technique
is introduced. The application of this system is not limited only for the household usage
yet to the grid connected as well. Irradiance, temperature and the load resistance of the
PV solar panel are the parameters that affect the output generation. The potential
combination gained from P-V and I-V curves could be referred to develop the
optimization system. Hence, from this information, the optimal output voltage, current
and power can be delivered from the PV panel. Two elements that are used in this
research: Maximum Power Point Tracking (MPPT) and Model Predictive Control (MPC).
The first stage of this study is to develop the MPPT algorithm that are commonly divided
into six types; Perturb and Observe (P&O), Incremental Conductance (INC), Fractional
Open Circuit Voltage (FOVC), Fractional Short Circuit Current (FSCC), Artificial Neural
(ANN) and Fuzzy Logic Control (FLC). The technique applied in this paper is Perturb
and Observe with MPC that will boost the generated output. It is believed that this
combination not only capable of increase the system efficiency but intensify the system
performance to the desired level. Apart from that, DC-DC boost converter would be the
intermediate in developing the algorithm to the system. The extraction of the maximum
output power can be achieved through this mechanism. On the other hand, the algorithm
would be diligently going through several alteration in order to achieve the stable coding
command with varied environment factor. The robustness test is implemented to
distinguish the characteristic of every possible characteristic that might affect the output.
This can be classified in term of the rate of time responses during optimal power tracking,
the solution to the non-linear properties of the PV arrays and the mitigation of the surge
oscillation and slope convergence. In addition, benchmarking is done by comparing the
proposed topology with modified P&O Fuzzy Logic Control. |
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