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Proceedings ArticleDOI

Controlling Megawatt Class WECS by ANFIS Network Trained with Modified Genetic Algorithm

TL;DR: The generated mechanical power from Wind Energy Conversion System (WECS) is highly susceptible on wind energy absorbed by turbine blades whereas they can cause fluctuations in generated power which is addressed by applying a novel strategy for training ANFIS network as a controller to the WECS.
Abstract: The generated mechanical power from Wind Energy Conversion System (WECS) is highly susceptible on wind energy absorbed by turbine blades whereas they can cause fluctuations in generated power. Designing a controller for WECS that leads to smooth generated mechanical power as well as high efficiency even with the presence of low wind speeds can be a challenging problem. This paper addresses this challenge by applying a novel strategy for training ANFIS network as a controller to the WECS. We firstly introducing Genetic Algorithm and Modified Genetic Algorithm optimization methods for training the adaptive network and updating the parameters of ANFIS. Then we use this trained adaptive network as a pitch angle controller for wind turbine. Comparing the results of proposed method with standard parameter optimization methods of ANFIS shows less error and training time in desired results. Also the fluctuations of wind turbine mechanical power decrease by applying trained ANFIS as a control signal for pitch angle entrance. The simulation results by using actual detailed model for wind power system show the effectiveness of the proposed method. Keywords-component; wind energy conversion system (WECS), Wind turbine, Pitch angle, Adaptive-Network-Based Fuzzy Inference System (ANFIS) controller, Optimization, Genetic Algorithm, Modified Genetic algorithm
Citations
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Journal ArticleDOI
TL;DR: In this paper, the authors discussed how to compensate for reactive power losses while reducing active power losses using a GA approach for voltage profile improvement and power smoothing in a modified Type III wind turbine system.

3 citations

Proceedings ArticleDOI
15 Oct 2022
TL;DR: In this article , a review work presents the worldwide generations of wind power and its control considering all constraints and parameters, and presents a hope to settle our future energy demands to be recovered the wind energy can play the vital role in this aspect.
Abstract: This era brings RE ascent more popular in energy generations evolve response in enhancing concern towards environmental issues. Among all RE sources wind energy becomes more attractive in the sense of nonhazardous, cleanest and most cost-effective source of energy. This 20 th century appeals the risk of shortage in fossil fuel, pollutions, carbon dioxide emissions and the surge of power demands. This develops a hope to settle our future energy demands to be recovered the wind energy can play the vital role in this aspect. Fulfilling the clean energy source, this renewable source can also be a part of growth in energy sector. This review work presents the worldwide generations of wind power and its control considering all constraints and parameters.
Proceedings ArticleDOI
15 Oct 2022
TL;DR: In this article , a review work presents the worldwide generations of wind power and its control considering all constraints and parameters, and presents a hope to settle our future energy demands to be recovered the wind energy can play the vital role in this aspect.
Abstract: This era brings RE ascent more popular in energy generations evolve response in enhancing concern towards environmental issues. Among all RE sources wind energy becomes more attractive in the sense of nonhazardous, cleanest and most cost-effective source of energy. This 20th century appeals the risk of shortage in fossil fuel, pollutions, carbon dioxide emissions and the surge of power demands. This develops a hope to settle our future energy demands to be recovered the wind energy can play the vital role in this aspect. Fulfilling the clean energy source, this renewable source can also be a part of growth in energy sector. This review work presents the worldwide generations of wind power and its control considering all constraints and parameters.
Proceedings ArticleDOI
06 May 2023
TL;DR: In this article , the authors present a power harvester design that uses three in-plane capacitive transducers -gap-closing, overlap-varying, and pattern-variant -to operate under ambient vibrations as input energy, leading to changes in capacitance and the harvesting of reliable electrical power.
Abstract: As part of the fourth industrial revolution, low-power electronic devices require a power harvesting system to provide energy for their operation because energy harvesting technologies are crucial for enabling 90% of wireless sensor networks. While solar and thermal energy harvesting are popular methods, they have limitations such as dependence on sunlight and thermal gradients, which make them unreliable for low-wattage electronic equipment and wireless sensing networks. Power harvesting from ambient vibrations can lead to a sustainable system. Currently, there is a focus on different power harvesting principles such as electromagnetic, piezoelectric, and electrostatic. This research work presents a novel power harvester design that uses three in-plane capacitive transducers - gap-closing, overlap-varying, and pattern-varying - to operate under ambient vibrations as input energy. With low levels of input vibrations, the device moves, leading to changes in capacitance and the harvesting of reliable electrical power. The design analysis includes capacitance, frequency, and electromechanical evaluations to acquire capacitance matrices, natural frequencies for different modes, displacement covered by moving mass, charge distribution, and pressure distribution.
References
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Journal ArticleDOI
01 May 1993
TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Abstract: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data pairs. In the simulation, the ANFIS architecture is employed to model nonlinear functions, identify nonlinear components on-line in a control system, and predict a chaotic time series, all yielding remarkable results. Comparisons with artificial neural networks and earlier work on fuzzy modeling are listed and discussed. Other extensions of the proposed ANFIS and promising applications to automatic control and signal processing are also suggested. >

15,085 citations

Journal ArticleDOI
TL;DR: In this paper, a multivariable control strategy for variable speed, variable pitch wind turbine is proposed for the above-rated power operating condition, which is realized by combining a nonlinear dynamic state feedback torque control strategy with a linear control for blade pitch angle.

360 citations

Journal ArticleDOI
TL;DR: The analysis of this study has proven that the GA technique is capable of estimating the optimal cutting conditions that yield the minimum surface roughness value.
Abstract: This study is carried out to observe the optimal effect of the radial rake angle of the tool, combined with speed and feed rate cutting conditions in influencing the surface roughness result. In machining, the surface roughness value is targeted as low as possible and is given by the value of the optimal cutting conditions. By looking at previous studies, as far as they have been reviewed, it seems that the application of GA optimization techniques for optimizing the cutting conditions value of the radial rake angle for minimizing surface roughness in the end milling of titanium alloy is still not given consideration by researchers. Therefore, having dealt with radial rake angle machining parameter, this study attempts the application of GA to find the optimal solution of the cutting conditions for giving the minimum value of surface roughness. By referring to the real machining case study, the regression model is developed. The best regression model is determined to formulate the fitness function of the GA. The analysis of this study has proven that the GA technique is capable of estimating the optimal cutting conditions that yield the minimum surface roughness value. With the highest speed, lowest feed rate and highest radial rake angle of the cutting conditions scale, the GA technique recommends [email protected] as the best minimum predicted surface roughness value. This means the GA technique has decreased the minimum surface roughness value of the experimental sample data, regression modelling and response surface methodology technique by about 27%, 26% and 50%, respectively.

198 citations

Journal ArticleDOI
TL;DR: In this article, the authors aimed at optimizing the surface roughness of die sinking electric discharge machining (EDM) by considering the simultaneous affect of various input parameters such as peak current and voltage.

177 citations

Journal ArticleDOI
TL;DR: In this article, a nonlinear feedback control scheme for variable speed wind turbines, without wind speed measurements, in below rated wind conditions was addressed, where two control strategies were proposed seeking a better performance.

110 citations