Видання НТУ "ХПІ"
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Документ Cascade sliding mode maximum power point tracking controller for photovoltaic systems(Національний технічний університет "Харківський політехнічний інститут", 2023) Hessad, M. A.; Bouchama, Z.; Benaggoune, S.; Behih, K.Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands. Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.Документ Fault detection and monitoring of solar photovoltaic panels using internet of things technology with fuzzy logic controller(Національний технічний університет "Харківський політехнічний інститут", 2022) Shweta, Raj; Sivagnanam, Sivaramalingam; Kumar, Kevin ArkPurpose. This article proposes a new control monitoring grid connected hybrid system. The proposed system, automatic detection or monitoring of fault occurrence in the photovoltaic application is extremely mandatory in the recent days since the system gets severely damaged by the occurrence of different faults, which in turn results in performance degradation and malfunctioning of the system. The novelty of the proposed work consists in presenting solar power monitoring and power control based Internet of things algorithm. In consideration to this viewpoint, the present study proposes the Internet of Things (IoT) based automatic fault detection approach, which is highly beneficial in preventing the system damage since it is capable enough to identify the emergence of fault on time without any complexities to generate Dc voltage and maintain the constant voltage for grid connected hybrid system. Methods. The proposed DC-DC Boost converter is employed in this system to maximize the photovoltaic output in an efficient manner whereas the Perturb and Observe algorithm is implemented to accomplish the process of maximum power point tracking irrespective of the changes in the climatic conditions and then the Arduino microcontroller is employed to analyse the faults in the system through different sensors. Eventually, the IoT based monitoring using fuzzy nonlinear autoregressive exogenous approach is implemented for classifying the faults in an efficient manner to provide accurate solution of fault occurrence for preventing the system from failure or damage.