In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particle swarm optimization (PSO) have been applied and compared to find the best tuning of PID parameters. The results demonstrate that the hybrid T2FPIDC under the Sugeno FIS with optimal PID using PSO produces the best results in terms of stable output power at variable wind speeds and reducing the error in the output signal.
Abstract
An experimental study was conducted for measuring the quality of surface finishing roughness using magnetic abrasive finishing technique (MAF) on brass plate which is very difficult to be polish by a conventional machining process where the cost is high and much more susceptible to surface damage as compared to other materials. Four operation parameters were studied, the gap between the work piece and the electromagnetic inductor, the current that generate the flux, the rotational Spindale speed and amount of abrasive powder size considering constant linear feed movement between machine head and workpiece. Adaptive Neuro fuzzy inference system (ANFIS) was implemented for evaluation of a serie
... Show MoreThe reactions of ozone with 2,3-Dimethyl-2-Butene (CH3)2C=C(CH3)2 and 1,3-Butadiene CH2=CHCH=CH2 have been investigated under atmospheric conditions at 298±3K in air using both relative and absolute rate techniques, and the measured rate coefficients are found to be in good agreement in both techniques used. The obtained results show the addition of ozone to the double bond in these compounds and how it acts as function of the methyl group substituent situated on the double bond. The yields of all the main products have been determined using FTIR and GC-FID and the product studies of these reactions establish a very good idea for the decomposition pathways for the primary formed compounds (ozonides) and give a good information for the effe
... Show MoreBackground: the difference in expression of type IV collagen in borderline tumors and ovarian carcinomas has been studied, but the association with adhesion molecules like CD44 have not gain enough interest. Objectives: The purpose of this study is to assess the expression of CD44v6 and type IV collagen status in borderline tumors and invasive ovarian carcinomas and the correlation between them to define the role of these molecules in tumor invasion and metastasis. Type of the study: A cross sectional study Methods: The study included a total of (101) formalin-fixed paraffin-embedded ovarian tissue blocks; of which (19) cases were borderline tumors and (82) cases were overt ovarian carcinomas. Sections from each block were immunohistoche
... Show MoreEnhancement of the performance for hybrid solar air conditioning system was presented in this paper. The refrigerant temperature leaving the condenser was controlled using three-way valve, this valve was installed after the compressor to regulate refrigerant flow rate towards the solar system. A control system using data logger, sensors and computer was proposed to set the opening valve ratio. The function of control program using LabVIEW software is to obtain a minimum refrigerant temperature from the condenser outlet to enhance the overall COP of the unit by increasing the degree of subcooled refrigerant. A variable load electrical heater with coiled pipe was used instead of the solar collector and the storage tank to simulate the sola
... Show MoreIt is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in
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