Adaptive maximum power point tracking using neural networks for a photovoltaic systems according grid

Introduction. In this paper, to maximize energy transmission in wind power system, various Maximum Power Point Tracking (MPPT) approaches are available. Among these techniques, we have proposed the one based on typical fuzzy logic. Despite the somewhat reduced performance of fuzzy MPPT. For a number of reasons, fuzzy MPPT can replace conventional optimization techniques. In practice, the effectiveness of conventional MPPT methods depends mainly on the accuracy of the information given and the wind speed or knowledge of the aerodynamic properties of the wind system. Novelty. Our new MPPT for monitoring the maximum power point has been proposed. We developed an algorithm to improve control performance and govern the stator’s developed active and reactive power using the typical fuzzy logic 2 and enable robust control of a grid-connected, doubly fed induction generator. Purpose. MPPT which implies the wind turbine’s rotating speed should be modified in real time to capture the most wind energy, is necessary to achieve high efficiency for wind energy conversion, according to the aerodynamic characteristics of the wind turbine. Methods. Developing a mathematical model for a wind energy production system is complex, can be strongly affected by wind variation and is a non-linear problem. Thanks to these characteristics, thus, the Lyapunov technique is combined with a sliding mode control to ensure overall asymptotic stability and robustness with regard to parametric fluctuations in order to accomplish this goal. We contrasted our fuzzy type-2 algorithm’s performance with that of the fuzzy type-1 and Perturbation & Observation (P&O) suggested in the literature. Practical value. The simulation results demonstrate that the control performance is satisfactory when using the fuzzy logic technique. From these results, it can be said for the optimization of energy conversion in wind systems, the fuzzy type-2 technique may offer a workable option. Since it presents a great possibility to avoid problems either technical or economics linked to conventional strategies.

Section: Fig 5 Diagram Design Of Robust Controllersmentioning

confidence: 99%

Maximum power point tracking improvement using type-2 fuzzy controller for wind system based on the double fed induction generator

Kaddache,

Drid,

Khemis

et al. 2024

“…At the same time, the use of these energy sources poses a significant environmental risk to the future of our planet due to the release of greenhouse gases. As a result, producing electrical energy from clean, nonpolluting, and renewable sources has become a global necessity and a topic of interest in our societies [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…The photovoltaic energy results from the direct transformation of rays from the sun into continuous electrical power by means of cells. Thus, to obtain sufficient power, the cells are connected in series and in parallels [2,22]. The connection between the power source and the distribution grid is provided by a series of power converters.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis of power converters in a grid connected photovoltaic system using artificial neural networks

Mimouni

Laribi

Sebaa

et al. 2023

Introduction. The widespread use of photovoltaic systems in various applications has spotlighted the pressing requirement for reliability, efficiency and continuity of service. The main impediment to a more effective implementation has been the reliability of the power converters. Indeed, the presence of faults in power converters that can cause malfunctions in the photovoltaic system, which can reduce its performance. Novelty. This paper presents a technique for diagnosing open circuit failures in the switches (IGBTs) of power converters (DC-DC converters and three-phase inverters) in a grid-connected photovoltaic system. Purpose. To ensure supply continuity, a fault-diagnosis process is required throughout all phases of energy production, transfer, and conversion. Methods. The diagnostic approach is based on artificial neural networks and the extraction of features corresponding to the open circuit fault of the IGBT switch. This approach is based on the Clarke transformation of the three-phase currents of the inverter output as well as the calculation of the average value of these currents to determine the exact angle of the open circuit fault. Results. This method is able to effectively identify and localize single or multiple open circuit faults of the DC-DC converter IGBT switch or the three-phase inverter IGBT switches.

“…A different hybrid energy system has been studied in many research papers [6][7][8][9][10][11][12][13][14][15][16][17][18]. The authors in [19] are proposing to realize a technical-economic capacity of a hybrid renewable energy system (HRES) to occupy the energy demand of a university site in the Himalayan state of northeastern Sikkim, and also the other aspect of exploring the electrical voltage of other renewable energy resources such as biogas and syngas and hydrokinetic energy, in addition to a solar-wind hybridization mainly carried out in the resource-rich urban planning territory of the east of the Himalayas.…”

Section: Introductionmentioning

confidence: 99%

A hybrid renewable energy production system using a smart controller based on fuzzy logic

Moussa

Derrouazin

Latroch

et al. 2022

Introduction. This article proposes an improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology with multiple inputs and outputs (I/O). It is used to control hybrid electric energy sources built around photovoltaic solar panels, wind turbine and electric energy storage system assisted by the electric grid. The novelty in this work that solar photovoltaic, wind turbine and storage system energy sources are prioritized over the grid network which is solicited only during adverse weather conditions, in order to supply a typical household using up to 4,000 Wh per day. In addition of that, the surplus of renewable energy produced during favorable climatic condition is used to produce hydrogen suitable for household heating and cooking using eletrolyzer system. Purpose. Development of improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology. This system is embedded on Arduino 2560 mega microcontroller, on which the fundamental program of fuzzy logic and the distribution of events with all possible scenarios have been implemented according to a flowchart allowing the management of the hybrid system. Methods as well as a parametric search and a simulation to characterize the system, are carried out in order to put on the proposed techniques to ensure continuous accommodation at home. Results. The proposed system results confirm their effectiveness by visualizing the output control signals from the electronic switches. Practical value of which transmits power through a single-phase DC/AC converter to power the AC load for the accommodation.