A neural networks-based maximum power point tracker with improved dynamics for variable dc-link grid-connected photovoltaic power plants

2013 ◽  
Vol 43 (1-2) ◽  
pp. 127-135 ◽  
Author(s):  
Miguel Carrasco ◽  
Fernando Mancilla-David ◽  
Francesco Riganti Fulginei ◽  
Antonino Laudani ◽  
Alessandro Salvini
Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 483
Author(s):  
Novie Ayub Windarko ◽  
Muhammad Nizar Habibi ◽  
Bambang Sumantri ◽  
Eka Prasetyono ◽  
Moh. Zaenal Efendi ◽  
...  

During its operation, a photovoltaic system may encounter many practical issues such as receiving uniform or non-uniform irradiance caused mainly by partial shading. Under uniform irradiance a photovoltaic panel has a single maximum power point. Conversely under non-uniform irradiance, a photovoltaic panel has several local maximum power points and a single global maximum power point. To maximize energy production, a maximum power point tracker algorithm is commonly implemented to achieve the maximum power operating point of the photovoltaic panel. However, the performance of the algorithm will depend on operating conditions such as variation in irradiance. Presently, most of existing maximum power point tracker algorithms work only in a single condition: either uniform or non-uniform irradiance. This paper proposes a new maximum power point tracker algorithm for photovoltaic power generation that is designed to work under uniform and partial shading irradiance conditions. Additionally, the proposed maximum power point tracker algorithm aims to provide: (1) a simple math algorithm to reduce computational load, (2) fast tracking by evaluating progress for every single executed duty cycle, (3) without random steps to prevent jumping duty cycle, and (4) smooth variable steps to increase accuracy. The performances of the proposed algorithm are evaluated by three conditions of uniform and partial shading irradiance where a targeted maximum power point is located: (1) far from, (2) near, and (3) laid between initial positions of particles. The simulation shows that the proposed algorithm successfully tracks the maximum power point by resulting in similar power values in those three conditions. The proposed algorithm could handle the partial shading condition by avoiding the local maxima power point and finding the global maxima power point. Comparisons of the proposed algorithm and other well-known algorithms such as differential evolution, firefly, particle swarm optimization, and grey wolf optimization are provided to show the superiority of the proposed algorithm. The results show the proposed algorithm has better performance by providing faster tracking, faster settling time, higher accuracy, minimum oscillation and jumping duty cycle, and higher energy harvesting.


2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Jelenko Karpić ◽  
Ekanki Sharma ◽  
Tamer Khatib ◽  
Wilfried Elmenreich

Abstract The rising demand for sustainable energy requires to identify the sites for photovoltaic systems with the best performance. This paper tackles the question of feasibility of photovoltaic power plants at high altitude. A direct comparison between an alpine and an urban area site is conducted in the south of Austria. Two low-cost automatic photovoltaic power measurement devices with dual-axis sun tracking and maximum power point tracking are deployed at two test sites. The system periodically performs a scan over the southern semihemisphere and executes maximum power point adjustment in order to assess the performance for a given direction. The gathered data shows a higher photovoltaic power yield in the higher altitude test site. Furthermore, the high altitude photovoltaic power as a function of azimuth and elevation angle appears to be not only higher but also more flat than in lower altitudes. This indicates a lower power loss in case of deviation from the optimal solar angles. The results show that even on low-cost hardware a difference in photovoltaic power can be observed, even though in this experiment it amounts to less than 5% increase of peak power in higher altitudes. However, the measured peak powers on the mountain are more stable and therefore closer to a constant level than the heavily fluctuating peak power values at the low altitude site. Additionally, a slight shift in optimal elevation angles between altitudes can be observed, as the optimum angle turns out to be lower on the high altitude site. This angle shift could be caused by snow reflections on the mountainous test site.


2012 ◽  
Vol 588-589 ◽  
pp. 818-821
Author(s):  
Feng Ge Zhang ◽  
Zhi Fei Teng ◽  
Xiao Ju Yin ◽  
Shi Lu Zhu

The method of maximum power point tracker with PIC18F4520 controlling in photovoltaic power system has been described in this paper. Maximum power point tracker is implemented with a non-inverting buck-boost DC-DC conversion topology. The system is simple with good response speed. And the efficiency of system is approved apparently with the method.


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