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[IEEE 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) - Delhi, India (2018.10.22-2018.10.24)] 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) - An ANFIS Artificial Technique Based Maximum Power Tracker for Standalone Photovoltaic Power Generation
摘要： This paper mainly develops a buck-boost converter based standalone photovoltaic system (PV) for power generation with maximum power point tracking (MPPT). Buck/boost converter is controlled by an adaptive neuro fuzzy inference system (ANFIS) MPPT algorithm which is programmed in a microcontroller. Inverter current controller using dSPACE DS1104 is performed for this purpose. Reliability and validity of standalone photovoltaic power generation system is justified using found Simulink and hardware results.
关键词： DC-DC buck boost converter,Standalone photovoltaic system,ANFIS,MPPT,dSPACE DS1104
更新于2025-09-12 10:27:22
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Accurate characterization of weld appearance induced by T-joint laser stake-welding by integration of ANFIS approach and numerical simulation
摘要： The geometrical appearance of weld bead is critically important in terms of directly determining the quality and reliability of T-joints laser stake-welding process. In this regard, this paper puts forward an innovative hybrid modeling scheme integrating the adaptive neural fuzzy interface system (ANFIS) with three-dimensional numerical simulation to accurately characterize the weld bead appearance. First, an ANFIS-based model is developed to identify the weld characteristics by experimental observation and provide the key parameters of hybrid heat source involved in the weld numerical simulation. Second, the weld bead geometry, i.e., weld penetration depth, surface weld width and interface weld width are all computed utilizing the numerical simulation method. The proposed numerical model exhibits good agreements with the experimental results in regard to forecasting the weld characteristics. In the end, the role of various welding conditions on the formation mechanism and T-joints bead profiles of the laser stake-welding are elucidated through the simulation model. The simulated results would help provide a much better understanding of the critical factors which does affect the weld appearance, and lay a solid foundation for optimizing of welding parameters and obtaining a high-quality weld.
关键词： T-joints,weld appearance,numerical simulation,ANFIS model,Laser stake-welding
更新于2025-09-11 14:15:04
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[IEEE 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD) - Istanbul, Turkey (2019.3.21-2019.3.24)] 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD) - Photovoltaic power forecasting through temperature and solar radiation estimation
摘要： The Utilization of the photovoltaic power as a source of electricity has been strongly growing. The unpredictability of the PV power energy induces frequency fluctuations and power system instabilities. Thus, short term PV power prediction, from one hour to several hours, becomes very important to ensure grid stability. The photovoltaic power depends on different weather conditions mostly temperature and solar radiation. Therefore, weather data forecasting becomes highly recommended. This paper presents a comparison study between the adaptive neuro-fuzzy inference system and the feed forward neural network for one hour ahead temperature and solar radiation estimation using different input data. Two and four hours ahead forecasting of the metrological data are done using the feed forward neural network model. Using the forecasted weather data, the photovoltaic power is deduced. The accuracy of the topologies is based on the normalized root mean square error (NRMSE), and the mean absolute percentage error (MAPE) The simulation results show that the FFNN outperforms the ANFIS model.
关键词： photovoltaic power,FFNN,ANFIS,prediction,solar radiation,temperature
更新于2025-09-11 14:15:04
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<b>Compatibility of Anfis controller and FPGA in solar power generation for a domestic oad
摘要： Among other soft computing techniques, the Adaptive Neuro Fuzzy Inference System (Anfis) gives a significant and advantageous result in solar power generation, especially in tracking the maximum power point. Due to the dynamic nature of solar irradiance and temperature, efficient energy conversion is not possible. However, advancements in the areas of artificial intelligence have made it possible to overcome the hurdles. The Maximum Power Point Tracking (MPPT) technique adopting the advantages of Anfis has been proven to be more successful with a fast dynamic response and high accuracy. The complete system is modeled using Matlab/Simulink; the hardware results are validated with the benefits of Field Programmable Logic Array (FPGA) instead of ordinary micro-controllers.
关键词： DC-AC power conversion,MPPT,FPGA,Anfis controller,solar power generation
更新于2025-09-09 09:28:46