A group of scientists conducted a literature review of nearly a hundred fast algorithms for maximum power point tracking. They extracted ten representative algorithms and showed which of them works best in different scenarios.
Academics from Taiwan have conducted an extensive study on fast maximum power point tracking (FMPPT) algorithms for PV power generation. Like conventional MPPT (Maximum Power Point Tracking) technology, FMPPTs ensure that solar panels operate at the maximum power point to maximize energy generation, but FMPPTs have a faster response time.
“A variety of FMPPT methods have been proposed in the literature, which can be classified into variable step size method (VSS), mathematical model method (MM), numerical optimization method (NO), artificial neural network /fuzzy logic control (ANN/FLC) method and the soft computing (SC) method,” the group explained.
The group began their evaluation with a review of FMPPT methods documented in the literature from 2014 to 2024. They then chose ten representative algorithms and compared them using a MATLAB simulation and experimental framework that used a low-cost digital signal controller (DSC ). Eight methods were based on VSS (methods 1–8), one on NO (method 9) and another on deterministic SC (method 10).
Experimental setup
“The reason for choosing the VSS method is that the MPPT technologies used in commercial solar energy systems (SPGS) today are mostly hill climbing (HC), and the VSS technique can be integrated into the MPPT technology of the original SPGS system. ”, said the scientists. “The reason for choosing the NO technique and the deterministic SC method is that these two approaches have better performance than the VSS method in some cases, and they can be easily achieved using low-cost DSC.”
All FMPPT were then tested on a MATLAB simulation of the JAM5-72–200 solar modules installed in a two-series-one-parallel (2S1P) structure. Each of these modules has a maximum power of 200.02 W, an open circuit voltage of 45.69 V, a short circuit current of 5.69 A, a maximum power point voltage of 37.11 V and a maximum power point current of 5 .39 A. All methods were tested under standard test conditions (STC) and rapid radiation change (FIC).
“This study uses the aforementioned simulation platform to adjust the parameter settings that are not clearly defined in the literature to obtain the optimal parameters for achieving an objective and fair comparison,” the group further explained. “Simulations and experiments are performed for uniform irradiation conditions (UIC) and EN50530:2010 test conditions. These results can provide a reference for the performance of any FMPPT method in an environment where the irradiation level (IL) is relatively stable and the condition where IL changes rapidly.”
In terms of testing the experimental setup, the group used a test setup where a DSC with an FMPPT was connected to a boost converter. It used the AMETEK ETS 600X8 D-PVE programmable DC power supply to simulate a 2S1P SPGS. The load was emulated using the Chroma 63108A electronic load operating in constant voltage mode to simulate a battery load. “The TerraSAS software developed by AMETEK makes it possible to create current-voltage characteristics of solar cell output current based on user-provided parameters, achieving accurate simulation of solar cell characteristics,” the researchers said.
Results
The analysis showed that different methods performed better depending on the test conditions. For example, Method 10 performed better under the STC, compared to the VSS method, with settling time or power loss tracking representing a “clear advantage.” Regarding the rapidly changing irradiation conditions, Method 9 and Method 8 outperformed other methods because they do not rely on current and voltage information for perturbation step (PS) adjustment.
Furthermore, the group found that Method 9 and Method 3 provide the best performance when both STC and FIC are taken into account, while Method 5 and Method 8 can provide the best comprehensive performance. “Taking into account the circuit response time and non-ideal/non-linear characteristics, the performance of Method 8 is the best, followed by Method 4 and Method 5,” the scientists concluded.
Their findings were presented in “Comprehensive overview of fast maximum power tracking algorithms for solar power generation systems”, published in the Ain Shams Engineering Journal. The research was conducted by scientists from National Taiwan University of Science and Technology and Taiwan’s National Changhua University of Education.
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