1. Ph.D Theses
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/11
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Item Grid Connection of Wind-Solar Hybrid Renewable Energy System, with Active Power Filter Functionality(National Institute of Technology Karnataka, Surathkal, 2019) Jayasankar, V. N.; Vinatha, U.The incorporation of the abundantly available wind and solar energy to the grid using power electronic converter based interfaces makes a reliable hybrid renewable energy system. Assigning harmonic mitigation property to the grid interfacing inverter to mitigate the current harmonics created by the non-linear loads at the load centres, is a cost-effective solution. The inverter controller consists of an outer DC-link voltage control loop and an inner current harmonic mitigation loop. The limitations of existing DC-link voltage controllers are poor stability margin, steady-state error and chattering problem. The widely used pq theory based inner loop controller offers poor performance under non-ideal grid voltage conditions. The conventional low pass filter based fundamental component extraction methods used in pq theory possess some limitations such as additional time delays and low-frequency oscillations. The main focus of this research is the design, simulation, implementation and analysis of a grid-tied wind-solar hybrid renewable energy system with shunt and series active filtering functionalities, under different system conditions. A Backstepping controller based outer loop, with enhanced DC-link loss compensation capability is proposed for the shunt active filter to overcome the limitations of the existing DC-link voltage controllers. The limitations of conventional low pass filter based fundamental component extraction methods are overcome by employing a self-tuning filter in the inner loop of the shunt active filter. An additional self-tuning filter is incorporated to improve the effectiveness of pq theory under non-ideal grid conditions. A self-tuning filter and a Fuzzy logic-based voltage controller are employed to control the series active filter effectively. A laboratory prototype of the shunt active power filter is implemented. The control algorithm is realised in Xilinx Basys-3 FPGA. From the simulation and hardware test results under steady-state and dynamic conditions, it is found that the proposed controller offers better stability, robustness and speed compared to other existing control methods.Item Water Quality Assessment in Distribution System Using Artificial Intelligence(National Institute of Technology Karnataka, Surathkal, 2014) Krishnaji, Patki Vinayak; Shrihari, S.; Manu, B.In this study various artificial intelligence techniques have been compared for assessment and prediction of water quality in various zones of municipal distribution system using six physico-chemical characteristics viz. pH, alkalinity, hardness, dissolved oxygen (DO), total solids (TS) and most probable number (MPN). Fuzzy expert system, artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) were used for the comparative study. The proposed expert system includes a fuzzy model consisting of IF-THEN rules to determine WQI based on water quality characteristics. The fuzzy models are developed using triangular and trapezoidal membership functions with centroid, bisector and mean of maxima (MOM) methods for defuzzification. In ANN method the cascade feed forward back propagation (CFBP) and feed forward back propagation (FFBP) algorithms were compared for prediction of water quality in the municipal distribution system. The comparative study was carried out by varying the number of neuron (1-10) in the hidden layer, by changing length of training dataset and by changing transfer function. ANFIS models are developed by using triangular, trapezoidal, bell and Gaussian membership function. Further, these artificial intelligence techniques are compared with multiple linear regression technique, which is the commonly used statistical technique for modelling water quality variables. The study revealed that artificial neural network (ANN) outperforms other modelling techniques and is a robust tool for understanding the poorly defined relations between water quality variables and water quality index (WQI) in municipal distribution system. This tool could be of great help to the distribution system operator and manager to find change in WQI with changes in water quality varibles.Item Influence of Climatic variables and Socio-Economic deforms on Municipal Residential Water Consumption Estimation using Fuzzy-Wavelet approach(National Institute of Technology Karnataka, Surathkal, 2017) Surendra, H. J.; Deka, Paresh ChandraThe actual level of water consumption is the driving force behind the hydraulic in water distribution system. Consequently it is crucial to estimate the residential water consumption in an urban area as accurately as possible in order to result in reliable simulation models. In this research work, hybrid fuzzy wavelet (denoise and compress) technique has been proposed and used for municipal residential water consumption estimation using climatic variables includes rainfall, maximum temperature, minimum temperature and relative humidity for an urban residential area in a yelahanka city, Bangalore, India. For this purpose historical climatic and water consumption data were collected for a period of ten years. Also field survey is done with questionnaire to collect the information about socio-economic aspects. The developed fuzzy-wavelet denoise and compress models were compared with single fuzzy model. Single Fuzzy model were developed using various membership function, rules criteria with different length of the data set. Also developed single fuzzy models compared with hybrid adaptive neuro fuzzy inference and multiple linear regression models. Denoise and compress process is done after the wavelet transformation using various mother wavelets such as Haar, Daubechies of order 2 to 6 and Discrete Meyer Wavelet for different levels with Shannon entropy. After denoise and compress process, coefficient having useful information is saved and corresponding its statistical properties is transferred to the fuzzy system for better inputoutput mapping. The performances of the developed models were evaluated using performance evaluation indices, such as RMSE, MAE, CC, PE and BIAS. The result indicates that detecting non-linear aspect and selecting an appropriate normalizing technique were beneficial in improving the estimation accuracy of the fuzzy-wavelet model. It is concluded that, fuzzy wavelet denoise and compress technique has promising potential and applicability in the estimation of municipal water consumption estimation with high accuracy.