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    Prediction of daily pan evaporation using support vector machines
    (CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2014) Pammar, L.; Deka, P.C.
    Water scarcity globally has lead to severe problems in water management. Understanding the rate of evaporation, from surface water resources is essential for precise management of the water balance. However, evaporation is difficult to measure experimentally due to its nature. Preparing reliable forecasts of evaporation has become an essential element towards efficient water management. The objective of this paper is to predict daily pan evaporation using different kernel functions of Support Vector Machines (SVM's) based regression approach for the meteorological data obtained for the region 'Lake Abaya' which is located in the Great Rift Valley, southern part of Ethiopia. The meteorological parameters considered for study includes daily details of mean-temperature (T), wind speed (W), sunshine hours (Sh), relative humidity (Rh), rainfall (P). Among the kernel functions used for study, the polynomial kernel function proved its credibility by showing improved performance in training and testing periods. The evidence for performance of polynomial kernel function was seen in terms of correlation coefficient (CC) obtained for training and testing is respectively 0.940, 0.956 which is acceptable. © 2014 CAFET-INNOVA TECHNICAL SOCIETY.
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    Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control
    (2014) RAJENDRAN, S.; Jena, D.
    This paper presents a nonlinear control approach to variable speed wind turbine (VSWT) with a wind speed estimator. The dynamics of the wind turbine (WT) is derived from single mass model. In this work, a modified Newton Raphson estimator has been considered for exact estimation of effective wind speed. The main objective of this work is to extract maximum energy from the wind at below rated wind speed while reducing drive train oscillation. In order to achieve the above objectives, VSWT should operate close to the optimal power coefficient. The generator torque is considered as the control input to achieve maximum energy capture. From the literature, it is clear that existing linear and nonlinear control techniques suffer from poor tracking of WT dynamics, increased power loss and complex control law. In addition, they are not robust with respect to input disturbances. In order to overcome the above drawbacks, adaptive fuzzy integral sliding mode control (AFISMC) is proposed for VSWT control. The proposed controller is tested with different types of disturbances and compared with other nonlinear controllers such as sliding mode control and integral sliding mode control. The result shows the better performance of AFISMC and its robustness to input disturbances. In this paper, the discontinuity in integral sliding mode controller is smoothed by using hyperbolic tangent function, and the sliding gain is adapted using a fuzzy technique which makes the controller more robust. © 2014, The Author(s).
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    Validation of an integral sliding mode control for optimal control of a three blade variable speed variable pitch wind turbine
    (Elsevier Ltd, 2015) RAJENDRAN, S.; Jena, D.
    Reduction in cost of wind energy requires most efficient control technology which can able to extract optimum power from the wind. This paper mainly focuses on the control of variable speed variable pitch wind turbine (VSVPWT) for maximization of extracted power at below rated wind speed (region 2) and regulation of extracted power when operating at above rated wind speed (region 3). To extract maximum power at below rated wind speed torque control is used whereas to regulate rated power at above rated wind speed pitch control is used. In this paper a nonlinear control i.e. integral sliding mode control (ISMC) is proposed for region 2 whereas a conventional proportional-integral (PI) control is adapted for region 3 of a VSVPWT. The proposed controller is combined with modified Newton Raphson (MNR) wind speed estimator to estimate the wind speed. The stability of the proposed ISMC is analyzed using Lyapunov stability criterion and the control law is derived for region 2 which is also adapted for the transition period between region 2 and region 3 (region 2.5). The dynamic simulations are tested with nonlinear FAST (Fatigue, Aerodynamics, Structures, and Turbulence) wind turbine (WT). The simulation results of ISMC are presented and the control performance is compared with conventional SMC and existing controllers such as aerodynamic torque feed forward control (ATF) and Indirect speed control (ISC). It is seen that especially in region 2.5, ISMC gives better performance compared to all other controllers. © 2015 Elsevier Ltd.
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    Backstepping sliding mode control of a variable speed wind turbine for power optimization
    (2015) RAJENDRAN, S.; Jena, D.
    To optimize the energy capture from the wind, wind turbine (WT) should operate at variable speed. Based on the wind speed, the operating regions of the WT are divided into two parts: below and above the rated wind speed. The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train. At above rated wind speed, the aim is to maintain the rated power by using pitch control. This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control (BSMC). In BSMC, generator torque is considered as the control input that depends on the optimal rotor speed. Usually, this optimal rotor speed is derived from effective wind speed. In this paper, effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR) algorithm. Initially, a conventional sliding mode controller (SMC) is applied to the WT, but the performance of the controller was found to be less robust with respect to disturbances. Generally, WT external disturbance is not predictable. To overcome the above drawback, BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue, aerodynamics, structures, and turbulence (FAST) WT simulator in the presence of disturbances. From the results, it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances. © 2015, The Author(s).
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    Nonlinear control of a wind turbine based on nonlinear estimation techniques for maximum power extraction
    (Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2016) RAJENDRAN, R.; Jena, D.
    This work proposes nonlinear estimators with nonlinear controllers, for variable speed wind turbine (VSWT) considering that either the wind speed measurement is not available or not accurate. The main objective of this work is to maximize the energy capture from the wind and minimizes the transient load on the drive train. Controllers are designed to adjust the generated torque for maximum power output. Estimation of effective wind speed is required to achieve the above objectives. In this work the estimation of effective wind speed is done by using the Modified Newton Rapshon (MNR), Neural Network (NN) trained by different training algorithms and nonlinear time series based estimation. Initially the control strategies applied was the classical ATF (Aerodynamic torque feed forward) and ISC (Indirect speed control), however due their weak performance and unmodeled WT disturbances, nonlinear static and dynamic feedback linearization techniques with the above wind speed estimators are proposed. © 2016 Taylor and Francis Group, LLC.
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    Nonlinear control of wind turbine with optimal power capture and load mitigation
    (Springer Verlag service@springer.de, 2016) RAJENDRAN, R.; Jena, D.
    The main control objectives associated with the variable speed wind turbine is to extract maximum power at below rated wind speed (region 2) and to regulate the power at above rated wind speed (region 3). This paper proposes a nonlinear framework to achieve the above two control objectives. The paper discusses about the application of an integral sliding mode control (ISMC) in region 2 and a fuzzy based proportional integral (PI) control in region 3. Same ISMC is adopted for the stable switching between operating regions (transition region 2.5) and the control input maintains the continuity at the instant of switching. Lyapunov stability criterion is used to prove the stability of ISMC. The controllers are tested for different wind speed profiles with different turbulence component. Finally the performances of the proposed controllers are tested with nonlinear Fatigue, Aerodynamics, Structures, and Turbulence WT model and the results are compared with the existing baseline + PI controllers. © 2015, Springer-Verlag Berlin Heidelberg.
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    A new control method to mitigate power fluctuations for grid integrated PV/wind hybrid power system using ultracapacitors
    (Walter de Gruyter GmbH info@degruyter.com, 2016) Sabhahit, N.S.; Gaonkar, D.N.
    The output power obtained from solar-wind hybrid system fluctuates with changes in weather conditions. These power fluctuations cause adverse effects on the voltage, frequency and transient stability of the utility grid. In this paper, a control method is presented for power smoothing of grid integrated PV/wind hybrid system using ultracapacitors in a DC coupled structure. The power fluctuations of hybrid system are mitigated and smoothed power is supplied to the utility grid. In this work both photovoltaic (PV) panels and the wind generator are controlled to operate at their maximum power point. The grid side inverter control strategy presented in this paper maintains DC link voltage constant while injecting power to the grid at unity power factor considering different operating conditions. Actual solar irradiation and wind speed data are used in this study to evaluate the performance of the developed system using MATLAB/Simulink software. The simulation results show that output power fluctuations of solar-wind hybrid system can be significantly mitigated using the ultracapacitor based storage system. © by De Gruyter 2016.
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    Offshore wind power resource assessment using Oceansat-2 scatterometer data at a regional scale
    (Elsevier Ltd, 2016) Gadad, S.; Deka, P.C.
    In the offshore region the scarcity of in situ wind data in space proves to be a major setback for wind power potential assessments. Satellite data effectively overcomes this setback by providing continuous and total spatial coverage. The study intends to assess the offshore wind power resource of the Karnataka state, which is located on the west coast of India. Oceansat-2 scatterometer (OSCAT) wind data and GIS based methodology were adopted in the study. The OSCAT data accuracy was assessed using INCOIS Realtime All Weather Station (IRAWS) data. Wind speed maps at 10 m, 90 m and wind power density maps using OSCAT data were developed to understand the spatial distribution of winds over the study area. Bathymetric map was developed based on the available foundation types and demarking various exclusion zones to help in minimizing conflicts. The wind power generation capacity estimation performed using REpower 5 MW turbine, based on the water depth classes was found to be 9,091 MW in Monopile (0-35 m), 11,709 MW in Jacket (35-50 m), 23,689 MW in Advanced Jacket (50-100 m) and 117,681 MW in Floating (100-1000 m) foundation technology. In Indian scenario major thrust for wind farm development in Monopile region is required. Therefore as first phase of development, if 10% of the estimated potential in the region can be developed then, 116% of energy deficit for FY 2011-12 could be met. Also, up to 79% of the anticipated energy deficit for the FY 2014-15 of the Karnataka state could be achieved. © 2016 Elsevier Ltd.
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    Control Strategy to Maximize Power Extraction in Wind Turbine
    (Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2016) RAJENDRAN, R.; Jena, D.
    This article deals with nonlinear control of variable speed wind turbine (VSWT), where the dynamics of the wind turbine (WT) is obtained from a single mass model. The main objective of this work is to maximize the energy capture form the wind with reduced oscillation on the drive train. The generator torque is considered as the control input to the WT. In general the conventional control techniques such as Aerodynamic Torque Feed-Forward (ATF) and Indirect Speed Control (ISC) are unable to track the dynamic aspect of the WT. To overcome the above drawbacks the nonlinear controllers such Sliding Mode Controller (SMC) and SMC with integral action (ISMC) with the estimation of effective wind speed are proposed. The Modified Newton Raphson (MNR) is used to estimate the effective wind speed from aero dynamic torque and rotor speed. The proposed controller is tested with different wind profiles with the presence of disturbances and model uncertainty. From the results the proposed controller was found to be suitable in maintaining a trade-off between the maximum energy capture and reduced transient on the drive train. Finally both the controllers are validated by using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) WT simulator. © Association of Energy Engineers (AEE).
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    Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches
    (Elsevier Ltd, 2017) Vathsala, H.; Koolagudi, S.G.
    In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good. © 2016 Elsevier Ltd