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E-raamat: Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK, and the Role of Soft Computing Techniques

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  • Sari: Green Energy and Technology
  • Ilmumisaeg: 08-Apr-2015
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319149417
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Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK, and the Role of Soft Computing TechniquesSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Green Energy and Technology
  • Ilmumisaeg: 08-Apr-2015
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319149417
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This textbook starts with a review of the principles of operation, modeling and control of common solar energy and wind-power generation systems before moving on to discuss grid compatibility, power quality issues and hybrid models of Solar PV and Wind Energy Conversion Systems (WECS). MATLAB/SIMULINK models of fuel cell technology and associated converters are discussed in detail. The impact of soft computing techniques such as neural networks, fuzzy logic and genetic algorithms in the context of solar and wind energy is explained with practical implementation using MATLAB/SIMULINK models.

This book is intended for final year undergraduate, post-graduate and research students interested in understanding the modeling and control of Solar PV and Wind Energy Conversion Systems based on MATLAB/SIMULINK.







- Each chapter includes Learning Objectives at the start, a Summary at the end and helpful Review Questions

- Includes MATLAB/SIMULINK models of different control strategies for power conditioning units in the context of Solar PV

- Presents soft computing techniques for Solar PV and WECS, as well as MATLAB/SIMULINK models, e.g. for wind turbine topologies and grid integration

- Covers hybrid solar PV and Wind Energy Conversion Systems with converters and MATLAB/SIMULINK models

- Reviews harmonic reduction in Solar PV and Wind Energy Conversion Systems in connection with power quality issues

- Covers fuel cells and converters with implementation using MATLAB/SIMULINK
1 Introduction 1(58)
1.1 What Is Energy?
1(5)
1.1.1 The Energy Scenario
2(2)
1.1.2 Energy Crisis: Global and Indian
4(2)
1.2 Energy Efficiency
6(1)
1.2.1 Efficient Energy Use
7(1)
1.3 Classification of Energy Sources
7(1)
1.4 Solar Photovoltaics
8(5)
1.4.1 Solar Radiation
11(1)
1.4.2 Measurement of Solar Radiation
12(1)
1.5 Wind Energy
13(5)
1.5.1 Renewable Energy in the 12th Five-Year Plan (2012-2017)
14(1)
1.5.2 Barriers to Achieving Higher Growth
15(3)
1.6 Benefits of Renewable Energy Sources
18(1)
1.7 Trends in Energy Consumption
19(15)
1.7.1 Annual Energy Consumption
24(1)
1.7.2 RES in INDIA
25(1)
1.7.3 National Policy Measures Supporting Renewables
26(1)
1.7.4 Renewable Energy Law
27(1)
1.7.5 Generation Based Incentive (2009-2012)
28(1)
1.7.6 Renewable Energy Certificate Scheme
29(1)
1.7.7 National Clean Energy Fund
30(1)
1.7.8 Other Initiatives: Renewable Regulatory Fund Mechanism
30(1)
1.7.9 Land Allocation Policy
31(1)
1.7.10 Grid Integration Issues
31(1)
1.7.11 Grid Transmission Planning Process
32(1)
1.7.12 Interconnection Standards
33(1)
1.7.13 Green Energy Corridor
33(1)
1.7.14 India Smart Grid Task Force
33(1)
1.8 Worldwide Potentials of Renewable Energy Sources
34(7)
1.9 Need for New Energy Technologies
41(3)
1.10 Introduction to Matlab and Simulink
44(1)
1.11 Introduction to Soft Computing
44(11)
1.11.1 Soft Computing Techniques
45(7)
1.11.2 Applications of Soft Computing Techniques in Solar Energy
52(2)
1.11.3 Applications of Soft Computing (AI) Techniques in Wind Energy
54(1)
1.12 Summary
55(1)
Bibliography
55(4)
2 Application of MATLAB/SIMULINK in Solar PV Systems 59(86)
2.1 Basics of Solar PV
60(1)
2.2 PV Module Performance Measurements
61(5)
2.2.1 Balance of System and Applicable Standards
62(3)
2.2.2 Photovoltaic Systems Total Costs Overview
65(1)
2.3 Types of PV Systems
66(5)
2.3.1 Grid-Connected Solar PV System
66(1)
2.3.2 Stand-Alone Solar PV System
67(2)
2.3.3 PV-Hybrid Systems
69(1)
2.3.4 Stand-Alone Hybrid AC Solar Power System with Generator and Battery Backup
69(2)
2.4 MATLAB Model of Solar PV
71(12)
2.4.1 SIMULINK Model of PV Module
79(2)
2.4.2 SIMULINK Model for PV Array
81(1)
2.4.3 SIMULINK Model to Find Shading Effect
82(1)
2.5 Charge Controller
83(13)
2.5.1 Batteries in PV Systems
84(1)
2.5.2 Battery Types and Classifications
85(1)
2.5.3 Battery Charging
85(1)
2.5.4 Battery Discharging
86(2)
2.5.5 Battery Gassing and Overcharge Reaction
88(1)
2.5.6 Charge Controller Types
88(6)
2.5.7 Charge Controller Selection
94(1)
2.5.8 Operating Without a Charge Controller
95(1)
2.5.9 Using Low-Voltage "Self-Regulating" Modules
95(1)
2.5.10 Using a Large Battery or Small Array
96(1)
2.6 MATLAB Model of SOC
96(4)
2.6.1 SIMULINK Model
98(2)
2.7 MATLAB Model of Charge Controller
100(3)
2.8 Inverter
103(5)
2.8.1 Centralized Inverters
104(2)
2.8.2 String Inverters
106(1)
2.8.3 Multi-string Inverters
107(1)
2.8.4 Module Integrated Inverter/Micro-inverters
107(1)
2.8.5 Inverter Topology
108(1)
2.9 MATLAB/SIMULINK Model of Inverter
108(2)
2.9.1 SIMULINK Model
109(1)
2.10 Maximum Power Point Tracking
110(30)
2.10.1 MPPT Techniques
115(15)
2.10.2 MATLAB/SIMULINK Implementation of Perturb and Observe Method
130(1)
2.10.3 MATLAB/SIMULINK Model of the Incremental Conductance Method
130(1)
2.10.4 PV Module with MPPT Techniques
130(10)
2.11 Summary
140(1)
Bibliography
140(5)
3 Soft Computing Techniques in Solar PV 145(102)
3.1 Introduction
145(1)
3.2 MPPT Using Fuzzy Logic
146(6)
3.2.1 Implementation
147(1)
3.2.2 Description and Design of FLC
148(3)
3.2.3 Simulation and Results
151(1)
3.3 Neural Networks for MPP Tracking
152(10)
3.3.1 Background of Neural Networks
154(2)
3.3.2 Implementation
156(3)
3.3.3 Algorithm for ANN Based MPPT
159(1)
3.3.4 Simulation Results
160(2)
3.4 Neuro-Fuzzy Based MPPT Method
162(19)
3.4.1 Fuzzy Neural Network Hybrids
164(1)
3.4.2 Theoretical Background of ANFIS
164(4)
3.4.3 Architecture of Adaptive Neuro-Fuzzy Inference System
168(2)
3.4.4 Hybrid Learning Algorithm
170(3)
3.4.5 Neuro-Fuzzy Network Model and Calculation Algorithm
173(2)
3.4.6 ANFIS Network Specifications
175(1)
3.4.7 Algorithm for Neuro-Fuzzy Based MPPT
175(3)
3.4.8 Results for Neuro-Fuzzy Based MPPT
178(3)
3.5 Fuzzy Based Solar Tracking
181(12)
3.5.1 Design Process of the Fuzzy Controller
185(1)
3.5.2 SIMULINK Model
186(2)
3.5.3 Simulation Results of Solar Tracking System
188(5)
3.6 MATLAB/SIMULINK Model of Two Axis Sun Tracker Using Fuzzy Logic
193(6)
3.6.1 Sensors
194(2)
3.6.2 Design of FLC for Sun Tracking System
196(3)
3.6.3 SIMULINK Model and Results of FLC Based Sun Tracker System
199(1)
3.7 FLC for Solar Powered Energy
199(7)
3.7.1 Methodology
201(1)
3.7.2 Theoretical Explanation
201(3)
3.7.3 SIMULINK Model of FLC Blocks
204(2)
3.7.4 Simulation Results
206(1)
3.8 Fuzzy Optimization for Solar Array System
206(16)
3.8.1 Photovoltaic Systems
211(2)
3.8.2 Peak-Power-Transfer Search
213(3)
3.8.3 Fuzzy Logic Based Solar Array Controller
216(6)
3.8.4 Experimental Results
222(1)
3.9 Forecasting of Solar Irradiance Using ANN
222(10)
3.9.1 Relation Between Solar Irradiance and Weather Variations
224(2)
3.9.2 Reconstruction for the Input Vector of the Forecasting Model
226(3)
3.9.3 ANN Forecasting Model Using Statistical Feature Parameters
229(3)
3.10 Parameter Identification of Solar Cell Using Genetic Algorithm
232(6)
3.10.1 Method of Determining the Parameters of Solar Cell Using Genetic Algorithms
235(3)
3.11 Application of Neuro-Fuzzy Technique for Prediction of Solar Radiation
238(5)
3.11.1 Neuro-Fuzzy Predictor (NFP)
238(3)
3.11.2 Error Metrics
241(1)
3.11.3 Neural Networks Training
241(1)
3.11.4 Prediction Results with NNP
242(1)
3.12 Summary
243(1)
Bibliography
244(3)
4 Wind Energy Conversion Systems 247(62)
4.1 Introduction
247(2)
4.2 Wind Characteristics
249(1)
4.3 Wind Turbine
250(2)
4.3.1 Fixed-Speed Wind Turbines
251(1)
4.3.2 Variable-Speed Wind Turbines
252(1)
4.4 Components of WECS
252(4)
4.4.1 Description of Components
253(3)
4.5 Types of Wind Turbine Generators
256(6)
4.5.1 Type 1 WTG
258(1)
4.5.2 Type 2 WTG
258(2)
4.5.3 Type 3 WTG
260(1)
4.5.4 Type 4 WTG
261(1)
4.5.5 Type 5 WTG
262(1)
4.6 Power Converter Topologies for Wind Turbine Generators
262(12)
4.6.1 Permanent Magnet Synchronous Generators
262(5)
4.6.2 Doubly Fed Induction Generators
267(5)
4.6.3 Induction Generators
272(1)
4.6.4 Synchronous Generators
273(1)
4.7 Economics of Wind Energy Conversion Systems
274(2)
4.8 Grid Connection
276(4)
4.8.1 Unique Configurations for Linking Wind Turbines on the Grid
276(4)
4.9 Modeling of Wind Turbine Using MATLAB/SIMULINK
280(10)
4.9.1 SIMULINK Models
280(7)
4.9.2 Simulation and Results
287(3)
4.10 MATLAB/SIMULINK Model of Type 1 WTG
290(2)
4.10.1 Pitch Angle Control System
291(1)
4.10.2 Parameters
291(1)
4.11 MATLAB/SIMULINK Model of Type 2 WTG
292(2)
4.12 MATLAB/SIMULINK Model of Type 3 WTG
294(2)
4.13 MATLAB/SIMULINK Model of Type 4 WTG
296(2)
4.14 MATLAB/SIMULINK Model of Grid Connection
298(7)
4.15 Summary
305(1)
Bibliography
306(3)
5 Soft Computing Techniques in Wind Energy Conversion Systems 309(82)
5.1 Prediction of Wind Turbine Power Factor
310(16)
5.1.1 Problem Formulation
310(2)
5.1.2 Artificial Neural Networks
312(3)
5.1.3 Adaptive Neuro-fuzzy Inference System (ANFIS)
315(7)
5.1.4 Description of Profile Types
322(1)
5.1.5 Design of the ANN
322(1)
5.1.6 ANFIS for Prediction of Power Factor
323(1)
5.1.7 Estimation of the Optimal Power Factor
324(2)
5.2 Pitch Angle Control
326(8)
5.2.1 Problem Definition
327(1)
5.2.2 Fuzzy Logic Controllers
327(1)
5.2.3 Genetic Algorithms
328(1)
5.2.4 Conventional Pitch Angle Control
329(2)
5.2.5 Fuzzy Logic for Pitch Control
331(2)
5.2.6 Genetic Algorithm Controller for Pitch Angle Control
333(1)
5.3 MPPT for WECS
334(5)
5.3.1 Fuzzy Logic Based MPPT Controller
336(3)
5.4 Economic Dispatch for Wind Power System
339(7)
5.4.1 Mathematical Model of Economic Dispatch for Power System Based on Wind Energy
339(2)
5.4.2 Quantum Genetic Algorithm (QGA) for Economic Dispatch of Wind Power System
341(4)
5.4.3 Strength Pareto Evolutionary Algorithm (SPEA) Approach
345(1)
5.5 SEIG Driven by WECS
346(9)
5.5.1 Mathematical Model for SEIG Driven by WECS
347(2)
5.5.2 Controllers
349(1)
5.5.3 Fuzzy Logic Controller
349(3)
5.5.4 Genetic Algorithm
352(3)
5.6 FLC Based STATCOM
355(6)
5.6.1 Modeling of STATCOM
355(1)
5.6.2 MATLAB/SIMULINK Model
356(4)
5.6.3 Simulation Results
360(1)
5.7 FLC Based Wind Energy Production System
361(13)
5.7.1 Wind/Battery Energy Production System
361(1)
5.7.2 The Wind Turbine Model
362(1)
5.7.3 Battery Model
363(1)
5.7.4 Fuzzy Logic Controller
363(6)
5.7.5 MATLAB SIMULINK Model
369(1)
5.7.6 Simulation Results
369(5)
5.8 Prediction of Wind Speed Based on FLC
374(5)
5.8.1 Controller Model
376(1)
5.8.2 Experimental Results
376(3)
5.9 Fuzzy Logic Controlled SPWM Converter for WECS
379(9)
5.9.1 Components of Standalone WECS
380(3)
5.9.2 MATLAB/SIMULINK Model
383(1)
5.9.3 Simulation Results
383(5)
5.10 Summary
388(1)
Bibliography
388(3)
6 Hybrid Energy Systems 391(80)
6.1 Need for Hybrid Energy System
391(1)
6.2 Hybrid Solar PV/Wind Energy System Using MATLAB/SIMULINK
392(10)
6.2.1 Architecture of Solar-Wind Hybrid System
393(1)
6.2.2 Implementation Using MATLAB/SIMULINK
393(2)
6.2.3 Small Domestic Power Grid Based on Hybrid Electrical Power
395(2)
6.2.4 Small Industrial Power System Based on Hybrid Renewable Energy
397(5)
6.3 Hybrid Model of Solar PV and Wind Energy System Using Cuk-Sepic Converter
402(13)
6.3.1 Objectives
403(1)
6.3.2 Hybrid Power System
403(1)
6.3.3 Cuk: SEPIC Based Converter on Source Side
404(3)
6.3.4 Model for Hybrid Wind and Solar Power Plant
407(1)
6.3.5 Three Phase Uncontrolled AC-DC Bridge Rectifier
407(3)
6.3.6 Total Harmonic Distortion
410(1)
6.3.7 Test Simulation and Results
410(5)
6.4 Hybrid Model of Solar PV and Diesel Energy System
415(3)
6.4.1 Need for Solar PV Diesel Hybrid System
415(1)
6.4.2 Photovoltaic Diesel Hybrid System
415(1)
6.4.3 Components of the Photovoltaic Diesel Hybrid System
416(2)
6.4.4 MATLAB/SIMULINK Model of Solar PV/Diesel Hybrid System
418(1)
6.5 Fuzzy Logic Controller for Hybrid Power System
418(17)
6.5.1 FLC for HPS
421(1)
6.5.2 Description of the Model
422(4)
6.5.3 Implementation in MATLAB
426(9)
6.6 Fuzzy Logic Based MPPT for Hybrid Solar and WECS
435(33)
6.6.1 Methodology
438(4)
6.6.2 Design Considerations
442(4)
6.6.3 Intelligent Controller
446(4)
6.6.4 Fuzzy Logic Controller Based MPPT for HPS
450(1)
6.6.5 PID Controller
451(2)
6.6.6 Simulation of Solar PV Under Atmospheric Conditions
453(5)
6.6.7 Simulation of FLC Based MPPT
458(10)
6.7 Summary
468(1)
Bibliography
469(2)
7 Grid Integration Techniques in Renewable Energy Systems 471(74)
7.1 Introduction
471(8)
7.1.1 Integration of Small Scale Generation into Distribution Grids
472(1)
7.1.2 Different Types of Grid Interfaces
472(1)
7.1.3 Issues Related to Grid Integration of Small Scale Generation
472(5)
7.1.4 Integration of Large Scale Renewable Energy Generation
477(2)
7.2 MATLAB Model of Grid Integration
479(10)
7.2.1 Photovoltaic Module
480(1)
7.2.2 Boost Converter
480(2)
7.2.3 SIMULINK Model of Boost Converter
482(3)
7.2.4 Implementation of Grid Integration Using MATLAB
485(4)
7.3 Phase Locked Loop for Grid Connected Power System
489(7)
7.3.1 Challenges Imposed on an Inverter-Based DG Interface
491(1)
7.3.2 Requirements for Establishing a Grid Connection
492(2)
7.3.3 Grid Synchronization Algorithms
494(2)
7.3.4 PLLs for Three Phase Systems
496(14)
7.4 Grid Connected Inverters
503(1)
7.4.1 Inverters
503(1)
7.4.2 Pulse Width Modulation Control
504(4)
7.4.3 Grid Filter
508(2)
7.5 Current Controllers for PWM Inverters
510(5)
7.5.1 SRF PI Current Controller
510(3)
7.5.2 Cascaded Deadbeat and PI Controller
513(2)
7.6 SIMULINK Model of PLL Grid Connected Power System .
515(23)
7.6.1 SIMULINK Model of a Synchronous Reference Frame PLL
515(1)
7.6.2 SIMULINK Model of a Synchronous Reference Frame PLL During Unbalanced Fault
516(2)
7.6.3 SIMULINK Model of a DSRF PLL
518(1)
7.6.4 SIMULINK Model of a DSRF PLL Under an Unbalanced Fault
518(4)
7.6.5 SIMULINK Model of αβPLL
522(2)
7.6.6 SIMULINK Model of αβPLL During Unbalanced Fault
524(1)
7.6.7 SIMULINK Model of a D&alpoha;β PLL
524(2)
7.6.8 SIMULINK Model of a Dαβ PLL Under an Unbalanced Fault
526(2)
7.6.9 SIMULINK Model of a Decoupled Double Synchronous Reference Frame PLL(DDSRF PLL)
528(4)
7.6.10 SIMULINK Model of a DDSRF PLL During an Unbalanced Fault
532(2)
7.6.11 SIMULINK Diagram of Grid Synchronization of the Inverter Using the Hybrid Dαβ PLL
534(2)
7.6.12 SIMULINK Model of SRF PI Controlled Voltage Source Inverter
536(1)
7.6.13 SIMULINK Diagram of Grid Synchronization of the Inverter Using Cascaded Deadbeat and PI Controller
536(2)
7.6.14 Comparison of Current THD of SRF PI and Cascaded Deadbeat and PI Controllers
538(3)
7.7 Summary
541(1)
Bibliography
542(3)
8 Harmonic Reduction Techniques in Renewable Energy Systems 545(52)
8.1 Introduction
545(2)
8.2 Power Quality Issues
547(2)
8.3 Sources and Effects of Power Quality Problems
549(1)
8.4 Standards Associated with Power Quality
550(2)
8.4.1 IEEE Standards
550(1)
8.4.2 SEMI International Standards
551(1)
8.5 Measurement of Power Quality in Solar PV Systems
552(5)
8.5.1 System Description
552(1)
8.5.2 Measurement Procedure for Power Quality in PV System
553(1)
8.5.3 Assessment Procedure for Power Quality in PV Systems
554(1)
8.5.4 Description of Case Studies
555(1)
8.5.5 Problem Evaluation and Solution Description
556(1)
8.6 Distribution Static Compensator
557(4)
8.6.1 SIMULINK Model of DSTATCOM
558(1)
8.6.2 Simulation Results
558(3)
8.7 Dynamic Voltage Restorer
561(7)
8.7.1 Equations Related to DVR
561(2)
8.7.2 SIMULINK Model of DVR
563(3)
8.7.3 Results and Discussion
566(2)
8.8 Unified Power Quality Conditioner
568(5)
8.8.1 UPQC with PV Array
569(1)
8.8.2 SIMULINK Model of UPQC
570(1)
8.8.3 Simulation Results
570(3)
8.9 Harmonic Reduction in WECS
573(8)
8.9.1 Power Quality Standards and Issues
574(1)
8.9.2 Power Curtailment or Wind Turbine Disconnection
575(1)
8.9.3 Coordination with Other Generating Plants
576(1)
8.9.4 Load Control
576(1)
8.9.5 Reactive Compensation and Voltage Control
577(4)
8.10 Power Quality in WECS- A Case Study
581(11)
8.10.1 Topology for Power Quality Improvement
584(3)
8.10.2 SIMULINK Model of Grid Connected WECS
587(1)
8.10.3 SIMULINK Model of Grid Connected WECS with STATCOM
587(1)
8.10.4 FFT Analysis
587(5)
8.11 Summary
592(1)
Bibliography
593(4)
9 Fuel Cell and Converters 597(54)
9.1 Introduction
597(1)
9.2 Fuel Cell Technology
598(29)
9.2.1 Importance of Fuel Cell
599(1)
9.2.2 Types of Fuel Cells
600(3)
9.2.3 Electrical Behaviour of Fuel Cell
603(2)
9.2.4 Need for Power Electronic Converters
605(2)
9.2.5 DC-DC Converters
607(1)
9.2.6 Conventional Boost Converter
608(3)
9.2.7 Cascaded Boost Converter
611(3)
9.2.8 Interleaved Boost Converter
614(6)
9.2.9 Isolated Converters
620(1)
9.2.10 Flyback Converter
621(1)
9.2.11 Forward Converter
622(1)
9.2.12 Push-Pull Converter
623(2)
9.2.13 Half Bridge Converter
625(1)
9.2.14 Full Bridge Converter
626(1)
9.3 Inverters
627(12)
9.3.1 Single Phase Inverter
627(1)
9.3.2 Half-Bridge Configuration
628(1)
9.3.3 Half Bridge with Resistive Load
628(1)
9.3.4 Half Bridge with RL Load
628(2)
9.3.5 - Full Bridge Configuration
630(1)
9.3.6 Full Bridge with Resistive Load
631(1)
9.3.7 Full Bridge with Resistive Load
631(1)
9.3.8 Three Phase Inverter
632(3)
9.3.9 Z-Source Inverter
635(2)
9.3.10 LLCC Resonant Inverter
637(2)
9.4 Fuel Cell System with Motor Load
639(1)
9.5 Architecture of Multiple Fuel Cells for High Voltage/High Power Applications
640(8)
9.5.1 Series Architecture
642(1)
9.5.2 DC Bus Distribution Architecture
643(2)
9.5.3 HFAC Distribution Architecture
645(1)
9.5.4 Multilevel Architecture
646(2)
9.6 Summary
648(1)
Bibliography
649(2)
Appendix I. Models Used to Assess the Performance of Solar PV Systems 651(14)
Appendix II. Research Projects 665(24)
Appendix III. SIMULINK Block Sets 689(58)
Appendix IV. Data for Case Study 747(36)
Index 783
Dr.S. Sumathi has pursued her B.E. (Electronics and Communication Engineering), M.E. (Applied Electronics) and PhD (Data Mining). She has a teaching experience of 24 years. Currently she is an Associate Professor in the Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore. She has published about 46 Technical papers in reputed National and International Journals and 52 papers in National and International Conferences. In addition, she has authored 5 books with leading publishers like Springer-Verlag and CRC press. She is a recipient of several awards from Institution of Engineers and ISTE. Her areas of specialization are Neural Networks, Fuzzy Systems and Genetic Algorithms, Pattern Recognition and Classification, Data Warehousing and Data Mining, Operating systems and Parallel Computing.

Dr. L. Ashok Kumar has completed his B.E. (EEE), ME (Electrical Machines) MBA (HRM) PhD (Wearable Electronics). He has both teaching and industrial experience of 17 years. At present he is working as a Professor in the Dept. of EEE, PSG College of Technology, Coimbatore. He has got 16 research projects from various Government funding agencies. He has published 72 Technical papers in reputed National and International Journal and presented 77 research articles in International and National Conferences. He is a recipient of many National and International Awards. He is a member of various National & International Technical bodies like ISTE, IETE, TSI, BMSI, ISSS, SESI, SSI CSI & TAI. His areas of specializations are Wearable Electronics, Power Electronics & Drives and Renewable Energy Systems.

Dr. P. Surekha completed her B.E. (Electrical and Electronics Engineering), M.E. (Control Systems) and Ph.D (Computational Intelligence). Her experience includes 10 years with a combination of teaching and industry. She is presently working in the Department of Electrical and Electronics Engineering, PES University, Bangalore. She has published 22 technical papers in International Journals and 16 papers in National and International conferences. Along with journals, to her credit, she has published 3 books with publishers like Springer-Verlag and CRC Press. Her areas of interest include Robotics, Virtual Instrumentation, Mobile Communication and Computational Intelligence.
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