In this work, we will compare between two types of converters Cuk and SEPIC because they are the most widely used and are two of the developed family of the converter. This paper presents under MATLAB/Simulink the use of CUK converter with maximum power point tracking (MPPT) technology, to increase its efficiency by an algorithm Perturb and Observe (P&O) and incremental conductance method, then we will apply artificial neural network (ANN) to avoid the disadvantages of MPPT Classical. The MPPT developed presents a better behavior than the P&O system
Słowa kluczowe: Magneto Caloric Effect; Hydrogen; Maximum Power Point Tracking; Perturb and Observe; Artificial Neural Network.
W artykule porównano dwa rodzaje przekształtników CUK i SEPIC ponieważ są one najczęściej używane. Przedstawiono symulację użycia przekształtnika CUK w technice śledzenia punktu maksymalnej mocy MPPT oraz algorytmy Perturb and Observe (P&O) przyroostowej przewodności.
Keywords: przekształtnikio CUK I SEPIC, System fotowoltaiczny,
Magneto Caloric Effect (MCE) consists to liquefying hydrogen to optimize its storage,the hydrogen producedtoday by means of solar energy that become an important source of power generation. However, the main problem in the proper exploitation remain how it is stored; one of the best storage methods is the liquefied hydrogen system. The hydrogen generation system simply consists of a PV module that connected to a hydrogen cell by DC converter that means the best optimization of hydrogen system is optimization of the photovoltaic (PV) system. A dozen of studies have been conducted on the use storage in renewable energy. Where Khalid et al.  suggested a renewable-based energy system for a house using hydrogen as a storage medium. Kalinciet al.  studied a standalone energy system for an island in Turkey using hydrogen as a storage option. ezmalinovic et al.  discussed the role of PEM fuel cells in PV based systems for remote base stations. They considered various scenarios such as PV/battery, PV/battery/diesel, generator and PV/battery/PEM fuel cell . Electrolyzer cell technology provides a sustainable solution for renewable energy storage and hydrogen production. Among all types of electrolyzer cell systems, PEMFC is providing a promising solution for hydrogen and oxygen production and receiving more and more attention due to their higher energy efficiency/density, faster charging/discharging, and a more compact design . Solar power is the conversion of sunlight into electricity, either directly using photovoltaic (PV), or indirectly using concentrated solar power. Concentrated solar power systems use lenses or mirrors and tracking systems to focus a large area of sunlight into a small beam. Photovoltaic cells convert light into an electric current using the photovoltaic effect . PV solar systems exist in many different configurations with regard to their relationship to inverter systems, external grids, f [...]
 Boutelhig, A., Mellit, A., Hanini, S., Ground water sources assessment for sustainable supply through photovoltaic water pumping system, in M’zab valley, Ghardaia, Energy Procedia, vol.141, pp. 76-80. 2017.  Sabat, M., Baczyński, D., Szafranek, K., The trials of providing the power and energy balancing of the studied area concerning the cooperation of the res, employing a different number of these sources, Przeglad Elektrotechniczny, vol.93, no 9, pp. 11-15, 2017.  Benhamza, T., Laidi, M., Hanini, S., Modeling of an Improved Liquid Desiccant Solar Cooling System by Artificial Neural Network, Lecture Notes in Networks and Systems, 35, pp. 337- 348, 2018.  Bartosik, M., Kamrat, W., Kaźmierkowski, M., (...), Strupczewski, A., Szeląg, A., Storage of electrical energy and hydrogen economy, Przeglad Elektrotechniczny, vol.92, no 12, pp. 332-340, 2016.  Hatti, M., Operation and maintenance methods in solar power plants, Use, Operation and Maintenance of Renewable Energy Systems, pp. 61-93, 2014.  Singh, B., Singh, S., GA-based optimization for integration of DGs, STATCOM and PHEVs in distribution systems, Energy Reports, 5, pp. 84-103, 2019.  Saadi, A., Becherif, M., Ramadan, H.S., Hydrogen production horizon using solar energy in Biskra, Algeria, International Journal of Hydrogen Energy, vol.41, no47, , pp. 21899-21912, 2016.  Hatti, M.; Meharrar, A.; and Tioursi, M. Novel approach of maximum power point tracking for photovoltaic module neural network based. In Int. Symposium on Environment Friendly Energies in Electrical Applications. pp. 1-6. 2010.  Malinowski, M., Chmielowiec, J., Paściak, G., Świeboda, T., Usability evaluation of PEM fuel cell and supercapacitors application in the emergency power backup system, Przeglad Elektrotechniczny, vol.89, no 8, pp. 201-204, 2013.  Amar Bensaber, A., Benghanem, M., Guerouad, A., Amar Bensaber, M., Power flow control and management of a hybrid power system, Przeglad Elektrotechniczny, vol. 95, no1, pp. 186-190, 2019.  Wu, J., Xing, X., Liu, X., Guerrero, J.M., Chen, Z., Energy management strategy for grid-tied microgrids considering the energy storage efficiency, IEEE Transactions on Industrial Electronics, vol.65,no12, pp. 9539-9549, 2018.  Dai, M., Tang, D., Giret, A., Salido, M.A., Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints, Robotics and Computer-Integrated Manufacturing, vol. 59, pp. 143-157, 2019.  Hatti, M.; Tioursi, M. and Nouibat, W. Neural Network Approach for Semi-Empirical Modelling of PEM Fuel-Cell. In Industrial Electronics, 2006 IEEE International Symposium on vol.3, pp.1858-1863, 2006.  Ganjehsarabi, H., Performance assessment of solar-powered high pressure proton exchange membrane electrolyzer: A case study for Erzincan, International Journal of Hydrogen Energy, 44(20), pp. 9701-9707, 2019.  Chmielewski, A., Możaryn, J., Piórkowski, P., Bogdziński, K., Battery Voltage Estimation Using NARX Recurrent Neural Network Model, Advances in Intelligent Systems and Computing, 920, pp. 218-23, 2020.