Nallapaneni Manoj Kumar

Techno-economic analysis of 1 MWp grid connected solar PV plant in Malaysia

ABSTRACT Most of the public and private technical universities in Malaysia have considerably abundant free areas, which could be a better place for equipping the renewable energy harvesters. The main objective of this paper is to analyse the feasibility of developing a solar PV plant at two different campuses of Universiti Malaysia Pahang (UMP). This paper proposes 1 MW solar PV power plant at the Pekan Campus (Rural Campus), and Gambang (Suburban Campus) of UMP located in the east coast state of Pahang, which is biggest among other states in Peninsular Malaysia. The technical viability of the proposed crystalline technology based PV plant with open rack or free stand mounting position is analysed using PVGIS (Photovoltaic Geographical Information Systems) and PV Watts’s software. The economic and environmental aspects of the proposed plant are also analysed based on standard parameters. The proposed plant of 1u2009MWp Solar PV plant can generate around 1390u2009MWh, of electricity per annum with a GHG emission reduction of 818.71 tCO2 per annum. The PV power plant can contribute in meeting 5% of total energy requirements of the campus. The technical performance obtained through PVGIS is quite comparable with the PV Watts results.

Application of Multi-domain Fusion Methods for Detecting Epilepsy from Electroencephalogram Using Classification Methods

Electroencephalogram (EEG) signal is a time series delineative signal which contains the useful knowledge about the state of the brain. It has high temporal resolution for detection of chronic brain disorders such as epilepsy/seizure, dementia, etc. Technically, a feature mainly targets to capture the significant and typical characteristics hidden in EEG signals. In view of the low accuracy of commonly used methods for discrimination of EEG signals, this paper presents an efficient multi-domain fusion method to enhance classification performance of EEG signals. Features are extracted using autoregressive method (AR) employing Yule-Walker and Burg’s algorithms respectively to generate feature from EEG. This paper implements two schemes of multi-domain fusion methods, the first one is AR method and wavelet packet decomposition (WPD) and the second one is AR method and Sample entropy (SampEn). Next, classification of extracted features is performed by different classifiers like Support vector machine (SVM) classifier, Linear Discriminant Analysis (LDA) classifier, Artificial neural network (ANN) classifier, K-nearest neighbor (KNN) and Ensemble classifier. Compared to AR-based method, fusion methods are yielding high accuracies. The ANN classifier has obtained the highest classification accuracy of 98.12% with the feature AR Burg-WPD combination compared to other classifiers in multi-domain fusion methods.

Computer-Aided Diagnosis of Epilepsy Based on the Time-Frequency Texture Descriptors of EEG Signals Using Wavelet Packet Decomposition and Artificial Neural Network

An adaptive time-frequency (t-f) representation of electroencephalographic (EEG) signals with high time and frequency resolutions using wavelet packet decomposition are introduced in this paper for automated diagnosis of epilepsy. The novel texture pattern techniques namely local neighbor descriptive pattern (LNDP) and symmetric weighted LNDP (SWLNDP) are proposed to obtain distinct features from the t-f images. Proposed texture pattern techniques are insensitive to local and global variations as the consecutive neighboring pixels are compared. SWLNDP is a modified version of LNDP which improves the computational efficiency of the system by reducing the feature vector length. The histogram based features are extracted from the texture pattern of t-f images and fed into artificial neural network (ANN) for classification of signals. The obtained results show that ANN attained an accuracy of 100% using proposed techniques for classifying epileptic and normal signal. Further the performance of the proposed system was analyzed for fifteen different cases using University of Bonn EEG dataset.

Development of Single and Multi-jet Conical Nozzle Based Open Jet Facility for Cold Jet Simulation

A significant negative impact is possible on practical high-speed propulsion applications due to shock wave and boundary layer interactions (SWBLI) when a supersonic jet is discharged out from a nozzle. So it is important to study the impacts associated with SWBLI. To study further, it is essential to analyze the physics of supersonic jet flow field by developing an open jet facility (OJF) in the laboratories. Supersonic jet can be produced in laboratories by allowing compressed air to escape through a nozzle into the atmosphere. Modeling, fabrication, and CFD simulation of nozzle-based open jet facility will help in understanding the supersonic jet flow. In this paper, an open jet facility is developed with single- and multi-jet conical nozzles in the Wind Tunnels Laboratory of Karunya University. The performance of this facility is evaluated theoretically and experimentally based on the runtime at different Mach numbers. Z-type schlieren technique is also applied to analyze the cold jet flow at a Mach number 2. CFD simulation is also carried out to verify the flow pattern that is visualized in experimental process.

Solar irradiance forecasting and energy optimization for achieving nearly net zero energy building

Solar energy and the concept of passive solar architecture are being increased in several areas to attain the net-zero energy concept. This paved the way for an increase in the need of solar irradiance forecasting for both solar PV applications and Passive Solar Architectural buildings. First, solar irradiance forecasting was done with 131u2009400 data sets (1-h data for 15 years) which was split into monthly mean for every year. This model was evaluated by forecasting the post-consecutive years one by one with the pre-consecutive years which includes the pre-forecasted years. This model was shown to have RMSE values of 11% to 24% for various seasonal forecasting using the Random Forest Algorithm in WEKA, which gave the annual irradiance results nearer to the PV Sol energy forecasting results. The R-value was in the range of 0.8 to 0.9 for various seasons which is good. Building Energy Optimization was carried out using BEopt 2.8 software designed by NREL. The chosen building was set to the standard parameters in India, and then, the optimization was done with various customized parameters and systems available in India to reduce the energy consumption from 192.2 MMBtu/yr to 109.1 MMBtu/yr with a 7u2009kW Solar PV System to attain the net-zero energy concept.Solar energy and the concept of passive solar architecture are being increased in several areas to attain the net-zero energy concept. This paved the way for an increase in the need of solar irradiance forecasting for both solar PV applications and Passive Solar Architectural buildings. First, solar irradiance forecasting was done with 131u2009400 data sets (1-h data for 15 years) which was split into monthly mean for every year. This model was evaluated by forecasting the post-consecutive years one by one with the pre-consecutive years which includes the pre-forecasted years. This model was shown to have RMSE values of 11% to 24% for various seasonal forecasting using the Random Forest Algorithm in WEKA, which gave the annual irradiance results nearer to the PV Sol energy forecasting results. The R-value was in the range of 0.8 to 0.9 for various seasons which is good. Building Energy Optimization was carried out using BEopt 2.8 software designed by NREL. The chosen building was set to the standard parameter...

Performance of thin-film BIPV as double sloped pitched roof in buildings of Malaysia

ABSTRACT Solar energy in built environments became more popular in the recent years emerging as building integrated photovoltaics (90° façade and 0° roof BIPV). However, in most cases, residential buildings have varying roof pitches instead of 0° roof. In this context, it is significant to assess the energy output and performance of double-sloped pitched roof thin-film BIPV at different angles and orientation. Results show that the performance of the BIPV inclined at 15° and east orientation is better among the other orientation and angles.

Speed control of 3-phase Induction motor fed through direct matrix converter using GSPWM technique with unity input power factor

This paper illustrates the method of speed control of three phase Induction motor using V/F control method which is fed through the direct matrix converter. To make the input power factor unity, the rectifier side of the direct matrix converter is controlled through GSPWM technique. The main advantage of using the direct matrix converter is that the dc-link storage is removed in the proposed one which makes the system rugged, robust and maintenance free. Apart from that, the use of GSPWM technique has drastically reduced the switching losses as explained. The controlling is also efficiently improved and hence the phase current waveform obtained is sinusoidal as desired with less harmonic content. Also, the input power factor obtained with the proposed technique comes out to be unity which definitely improves the power quality fed to the Induction motor. Simulation is carried out in MATLAB/SIMULINK and the results show the effectiveness and efficiency of the proposed converter.