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EN
The occurrence of partial shading in solar power systems presents a substantial challenge with widespread implications, sparking extensive research, notably in the field of maximum power point tracking (MPPT). This study emphasizes the critical process of accurately tracking the maximum power points with the characteristic curves of photovoltaic (PV) modules under real-time, diverse partial shading patterns. It explores the various stages of the tracking process and the methodologies employed for optimization. While conventional methods show effectiveness, they often fall short in swiftly and accurately tracking maximum power points with minimal errors. To address this limitation, this research introduces a novel machine learning approach known as adaptive reinforcement learning with neural network architecture (ARL-NNA) for MPPT. The results obtained from ARL-NNA are compared with existing algorithms using the same experimental data. Furthermore, the outcomes are validated through different factors and processing time measurements. The findings conclusively demonstrate the efficacy and superiority of the proposed algorithm in effectively tracking maximum power points in PV characteristic curves, providing a promising solution for optimizing solar energy generation in partial shading patterns. This study significantly impacts various realms of electrical engineering including power engineering, power electronics, industrial electronics, solid-state electronics, energy technology, and other related field of engineering and technology.
2
Content available remote Control of a photovoltaic system by sliding mode based on backstepping
EN
In this article we have studied photovoltaic systems which are non-linear systems. Due to variations in the current-voltage characteristics of PV systems. In fact, we have described the sliding mode method and then we have combined it with the backstepping method. We have applied it to a well-determined PV system. shows that the sliding mode method based on backstepping is more efficient than that of the basic sliding mode.
PL
W tym artykule badaliśmy systemy fotowoltaiczne, które są systemami nieliniowymi. Ze względu na różnice w charakterystyce prądowo-napięciowej systemów fotowoltaicznych. W rzeczywistości opisaliśmy metodę trybu ślizgowego, a następnie połączyliśmy ją z metodą cofania. Zastosowaliśmy to do dobrze określonego systemu fotowoltaicznego. pokazuje, że metoda trybu ślizgowego oparta na krokach wstecznych jest bardziej wydajna niż metoda trybu ślizgowego podstawowego.
EN
Electronic devices feature non-linear switching functionality, current distortion gives rise to harmonics that shorten the life of devices and damage electrical networks, causing malfunctions and overheating. Mitigation of harmonics problems and improvement of power quality are necessary. The shunt active power filter reduces harmonics and greatly improves the sinusoidal shape of the current. This work presents a study with two different voltage sources of a two-level inverter applied to a shunt active power filter based on three phases connected to the grid, the first is a continuous direct source and the second is a photovoltaic source. Simulation results provided good efficiency of the SAPF with the photovoltaic system integration.
PL
Urządzenia elektroniczne posiadają funkcję przełączania nieliniowego, zniekształcenia prądu powodują powstawanie harmonicznych, które skracają żywotność urządzeń i niszczą sieci elektryczne, powodując awarie i przegrzewanie. Niezbędne jest łagodzenie problemów z harmonicznymi i poprawa jakości energii. Bocznikowy aktywny filtr mocy redukuje harmoniczne i znacznie poprawia sinusoidalny kształt prądu. W pracy przedstawiono badanie z dwoma różnymi źródłami napięcia dwupoziomowego falownika zastosowanego do bocznikowego filtra mocy czynnego opartego na trzech fazach podłączonych do sieci, przy czym pierwsza jest ciągłym źródłem bezpośrednim, a druga jest źródłem fotowoltaicznym. Wyniki symulacji zapewniły dobrą wydajność SAPF z integracją systemu fotowoltaicznego.
EN
The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.
5
EN
Solar energy is the most widespread renewable energy source due to the modular structures of PV modules and low maintenance requirement. In this study, a sun tracking system is proposed with a view to achieving a generated energy output than with a fixed PV system. There are two different control structures and algorithms are proposed to control the sun tracking system to increase efficiency. The tracking system uses algorithms to determine the exact position of the sun at any time during the day and to turn the PV modules to a position perpendicular to the sun. In the first control circuit, the position of the sun is precisely found with two identical LDRs and an angle sensor. In the second control circuit, the position of the sun is tracked by using a real time clock and an angle sensor to limit the platform. Greater energy generation is achieved by turning existing solar panels to face the sun. Furthermore, a data acquisition device stores and monitors daily irradiation data on a computer and the data entered in the database are used to produce graphic interfaces.
EN
Maximum power point tracking (MPPT) optimizes overall power generation in photovoltaic (PV) applications. The voltagepower characteristics of PV array operating under variable irradiance and temperature conditions exhibit numerous local maximum power points (MPP). This paper presents the optimization method of MPP tracking, based on the modified Regula Falsi method (MRFM). Results of this method are compared with the conventional perturb & observe (P&O) method and the incremental conductance (IC) method. The modified Regula Falsi method has better convergence, lower oscillation time, less power loss and enhanced output power than the other two methods. To obtain a stable voltage from a solar array, a DC-DC Cuk converter is used. It can step-up and step-down the voltage level according to load requirement. Results have been verified on the MATLAB platform in variable environmental conditions.
EN
This paper presents high performance improved direct power control (DPC) based on model reference adaptive control (MRAC) and neuro-fuzzy control (NFC) for grid connected doubly fed induction generator (DFIG), to overcome the drawbacks of conventional DPC which was based only on PID controllers, namely the speed/efficiency trade-off and divergence from peak power under fast variation of wind speed. A mathematical model of DFIG implemented in the d-q reference frame is achieved. Then, a direct power control algorithm for controlling rotor currents of DFIG is incorporated using PID controllers, and space-vector modulation (SVM) is used to determine a fixed switching frequency. The condition of the stator side power factor is controlled at unity level via MPPT strategy. The MRAC which is based on DPC is investigated instead of PID regulators. Also, the performances of NFC based on DPC are tested and compared to those achieved using MRAC controller. The results obtained in the Matlab/Simulink environment using robustness tests show that the NFC is efficient, has superior dynamic performance and is more robust during parameter variations.
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