E-Book, Englisch, Band 607, 1011 Seiten, eBook
Proceedings of ICTSES 2018
E-Book, Englisch, Band 607, 1011 Seiten, eBook
Reihe: Lecture Notes in Electrical Engineering
ISBN: 978-981-15-0214-9
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1;Preface;6
2;Contents;8
3;About the Editors;18
4;LED Driver Design and Thermal Management;20
4.1;1 Introduction;20
4.1.1;1.1 Experimental Setup;21
4.2;2 Conclusion;26
4.3;References;26
5;Automatic Generation Control of Interconnected Power Systems Using Elephant Herding Optimization;28
5.1;1 Introduction;28
5.2;2 Modelling of Interconnected Three-Area Power System;29
5.3;3 Proposed Elephant Herding Optimization (EHO) Based Strategy for LFC;31
5.3.1;3.1 Clan Updating Operator;31
5.3.2;3.2 Separating Operator;32
5.4;4 Control Strategy;32
5.5;5 Results and Discussions;33
5.6;6 Conclusion;33
5.7;References;36
6;Use of Ti-Doped Hafnia in Photovoltaic Devices: Ab Initio Calculations;38
6.1;1 Introduction;38
6.2;2 FP-LAPW Theory;39
6.3;3 Results and Discussion;40
6.4;4 Conclusions;42
6.5;References;42
7;Electronic and Optical Response of Photovoltaic Semiconductor ZrSxTe2-x;43
7.1;1 Introduction;43
7.2;2 FP-LAPW Method;44
7.3;3 Results and Discussion;44
7.3.1;3.1 Electronic Structure;44
7.4;4 Conclusions;46
7.5;References;47
8;Investigation of Optical Response of Silver Molybdate for Photovoltaic;48
8.1;1 Introduction;48
8.2;2 Methodology;49
8.2.1;2.1 Experiment;49
8.2.2;2.2 Theory;49
8.3;3 Results and Discussion;50
8.3.1;3.1 Electronic Response;50
8.3.2;3.2 Compton Profile;51
8.3.3;3.3 Optical Response;51
8.4;4 Conclusions;53
8.5;References;53
9;Comparative Analysis of Conventional and Meta-heuristic Algorithm Based Control Schemes for Single Link Robotic Manipulator;55
9.1;1 Introduction;55
9.2;2 Control of a Single Link Manipulator;56
9.3;3 Conventional Control Techniques;58
9.3.1;3.1 PID Control;58
9.3.2;3.2 FOPID Control;58
9.3.3;3.3 Tuning of Controller Using GA;58
9.4;4 Results;59
9.5;5 Conclusion;61
9.6;References;61
10;Synthesis of Antenna Array Pattern Using Ant Lion Optimization Algorithm for Wide Null Placement and Low Dynamic Range Ratio;63
10.1;1 Introduction;63
10.2;2 Problem Formulation;64
10.2.1;2.1 Wide Null Placement with Reduced SLL;65
10.2.2;2.2 Dynamic Range Ratio (DRR) Constraint-Based Peak Side Lobe Level (PSLL) Minimization;66
10.3;3 Results and Discussion;67
10.3.1;3.1 Wide Null Placement with Reduced SLL;67
10.3.2;3.2 Dynamic Range Ratio (DRR) Constraint-Based Peak Side Lobe Level (PSLL) Minimization;69
10.4;4 Conclusion;71
10.5;References;72
11;Design and Analysis of a Hybrid Non-volatile SRAM Cell for Energy Autonomous IoT;73
11.1;1 Introduction;74
11.2;2 Background;75
11.3;3 Proposed NV-SRAM Cell;76
11.3.1;3.1 Cell Design Concept;76
11.4;4 Results;79
11.5;5 Conclusion;80
11.6;References;80
12;Bandgap Engineering of AgGaS2 for Optoelectronic Devices: First-Principles Computational Technique;82
12.1;1 Introduction;82
12.2;2 Computational Details;83
12.3;3 Structural Information;84
12.4;4 Results and Discussion;85
12.4.1;4.1 Electronic Properties;85
12.4.2;4.2 Optical Properties;87
12.5;5 Conclusion;88
12.6;References;88
13;Intelligent Power Sharing Control for Hybrid System;90
13.1;1 Introduction;90
13.2;2 System Description and Modeling;91
13.3;3 Control Strategy;92
13.4;4 Proposed Intelligent Control;93
13.5;5 Results and Discussion;95
13.5.1;5.1 Steady-State Response;95
13.5.2;5.2 Dynamic Response;96
13.6;6 Conclusion;98
13.7;References;99
14;Comparative Analysis of Various Classifiers for Gesture Recognition;100
14.1;1 Introduction;101
14.2;2 Related Work;101
14.2.1;2.1 Detection of Target;102
14.2.2;2.2 Recognition of Target;102
14.3;3 Proposed Work;103
14.4;4 Result;104
14.5;5 Conclusion and Future Development;107
14.6;References;108
15;Artificial Intelligence Based Optimization Techniques: A Review;110
15.1;1 Introduction;110
15.2;2 Genetic Algorithm;111
15.3;3 Particle Swarm Optimization;112
15.4;4 Ant Colony Optimization (ACO);113
15.5;5 BAT Algorithm;114
15.5.1;5.1 Random Fly;114
15.5.2;5.2 Local Random Walk;115
15.6;6 Elephant Herding Optimization;115
15.6.1;6.1 Clan Updating Operator;115
15.6.2;6.2 Separating Operator;116
15.7;7 Conclusion;117
15.8;References;117
16;Optimal Location and Sizing of Microgrid for Radial Distribution Systems;119
16.1;1 Introduction;120
16.2;2 Problem Formulation;121
16.2.1;2.1 Objective Function;121
16.2.2;2.2 Constraints;121
16.3;3 Methodology;122
16.3.1;3.1 Proposed Algorithm;122
16.4;4 Case Study;123
16.5;5 Conclusion;126
16.6;References;126
17;Constraint Tariff Model to Reduce the Amount of Cross Subsidy Incorporated in Electricity Tariff Using Iterative Optimization Technique;128
17.1;1 Introduction;128
17.2;2 Basic Model and Recommended Modifications;129
17.3;3 Optimization Problem Formulation;130
17.3.1;3.1 The Objective Function;130
17.3.2;3.2 The Operating Constraints;130
17.3.3;3.3 The Bounds;131
17.4;4 Algorithm Developed;131
17.5;5 Availability of Data and Assumptions;133
17.6;6 Results and Discussion;134
17.7;7 Conclusion;135
17.8;References;136
18;Titration Machine: A New Approach Using Arduino;137
18.1;1 Introduction;137
18.2;2 Motivation;138
18.3;3 Experimental Setup;138
18.4;4 Working and Flowchart;139
18.5;5 Circuit Diagram of Arduino with Motor Shield;139
18.6;6 A Glimpse of the Titration Machine;140
18.7;7 Results;142
18.8;8 Conclusions;143
18.9;References;143
19;Hybrid Method for Cluster Analysis of Big Data;144
19.1;1 Introduction;144
19.2;2 Related Work;145
19.3;3 Proposed Work;146
19.3.1;3.1 The Proposed Model;146
19.3.2;3.2 Workflow of the Algorithm;146
19.4;4 Results and Discussion;147
19.5;5 Conclusions;149
19.6;References;150
20;A New Radio Frequency Harvesting System;151
20.1;1 Introduction;151
20.2;2 Overview of the System;152
20.2.1;2.1 Rectenna;153
20.2.2;2.2 Power Converter;153
20.2.3;2.3 Flyback Converter;154
20.3;3 Methodology;155
20.3.1;3.1 Conceptual Frame Work and Simulations;156
20.4;4 Results;160
20.5;5 Conclusion;161
20.6;References;162
21;Backpropagation Algorithm-Based Approach to Mitigate Soiling from PV Module;163
21.1;1 Introduction;164
21.2;2 Factors Influencing Dust Settlement;164
21.3;3 Training and Modeling of ANN;166
21.4;4 Results and Discussion;168
21.5;5 Conclusion;170
21.6;References;171
22;Real-Time Low-Frequency Oscillations Monitoring and Coherency Determination in a Wind-Integrated Power System;172
22.1;1 Introduction;172
22.2;2 Problem Formulation;174
22.2.1;2.1 Damping Index (DI);174
22.2.2;2.2 Coherent Groups Determination;175
22.3;3 Proposed Methodology;175
22.3.1;3.1 Optimal PMU Placement;175
22.3.2;3.2 Wind Site Selection;175
22.3.3;3.3 Proposed PMU-ANN Based Method;176
22.4;4 Results;177
22.4.1;4.1 Optimal PMU Placement;178
22.4.2;4.2 Proposed Real-Time Monitoring;178
22.5;5 Conclusion;180
22.6;References;180
23;Design and Performance Analysis of Different Structures of MEMS PVDF-Based Low-Frequency Piezoelectric Energy Harvester;182
23.1;1 Introduction;183
23.2;2 Mathematical Modeling;184
23.3;3 Design Parameters of Cantilever Beam;185
23.3.1;3.1 Design Parameters for the Straight T-Shaped Cantilever Structure;186
23.3.2;3.2 Designing Parameters of the Pi-Shaped Cantilever Structure;186
23.4;4 Results and Discussion;187
23.4.1;4.1 Modal Analysis;187
23.4.2;4.2 Dynamic Analysis;189
23.4.3;4.3 Piezoelectric Analysis;189
23.4.4;4.4 Stress Analysis;189
23.5;5 Conclusion;189
23.6;References;190
24;Designing and Implementation of Overhead Conductor Altitude Measurement System Using GPS for Sag Monitoring;192
24.1;1 Introduction;193
24.2;2 Designing of Overhead Conductor Altitude Measurement System;194
24.2.1;2.1 Field Test;195
24.3;3 Accuracy Enhancement Techniques;197
24.4;4 Results;198
24.4.1;4.1 Error Analysis;200
24.5;5 Sag Estimation;201
24.6;6 Conclusion;201
24.7;References;202
25;Risk-Averse G2V Scheduling of Electric Vehicle Aggregator for Improved Market Operations;204
25.1;1 Introduction;204
25.2;2 Risk Controlling in Stochastic Optimization;206
25.3;3 Scenario Generation and Reduction;206
25.4;4 Risk-Aversive Formulation of Stochastic Programming Problem;207
25.5;5 Simulation Results of Risk-Constrained Stochastic Scheduling;209
25.6;6 Conclusion;211
25.7;References;211
26;Optical Gain Tuning in Type-I Al0.45Ga0.55As/GaAs0.84P0.16/Al0.45Ga0.55As Nano-heterostructure;213
26.1;1 Introduction;214
26.2;2 Theoretical Background;214
26.3;3 Simulation Results;215
26.4;4 Conclusions;217
26.5;References;218
27;Semantic Similarity Computation Among Hindi Words Using Hindi Lexical Ontology;219
27.1;1 Introduction;219
27.2;2 Theoretical Background of Hindi Ontology;220
27.2.1;2.1 The Structure for Indo WordNet;221
27.3;3 Proposed Semantic Similarity Method;221
27.4;4 Experiments and Analysis;222
27.5;5 Conclusion;225
27.6;References;226
28;A Dual-Band Microstrip Patch Antenna for Wireless Applications;227
28.1;1 Introduction;227
28.2;2 Antenna Geometry;228
28.3;3 Results and Discussion;229
28.4;4 Conclusion;230
28.5;References;233
29;Analysis of Energy Consumption and Implementation of R-Statistical Programming for Load Forecasting in Presence of Solar Generation;234
29.1;1 Introduction;234
29.2;2 Details of the Installed System;235
29.3;3 Advanced Metering Infrastructure (AMI) Architecture;235
29.3.1;3.1 Smart Energy Meters;236
29.3.2;3.2 Communication Network;236
29.3.3;3.3 Smart Grid Control Center;236
29.4;4 Advanced Data Analysis Using Smart Meter Data;236
29.4.1;4.1 Signature of Monthly Energy Consumption of the House;237
29.4.2;4.2 Signature of Daily Energy Consumption of the House;237
29.5;5 Impact of Renewable Integration;238
29.5.1;5.1 Grid-Connected Solar PV System Without Battery Backup;239
29.5.2;5.2 Grid-Connected Solar PV System with Battery Backup for Partial Load;240
29.5.3;5.3 Comparison of Monthly Consumption Pattern;240
29.6;6 Forecasting of Consumer Energy Consumption;241
29.6.1;6.1 ARIMA Forecasting Model;241
29.6.2;6.2 Simple Exponential Smoothing Forecasting Model;242
29.7;7 Results;243
29.8;8 Conclusion;244
29.9;References;245
30;A Comprehensive Analysis of Delta and Adaptive Delta Modulated Modular Multilevel Converter;246
30.1;1 Introduction;246
30.2;2 Delta Modulation;248
30.3;3 Adaptive Delta Modulation;248
30.4;4 Results and Discussion;248
30.5;5 Conclusion;252
30.6;References;253
31;Speed Control of PMSM Drive Using Jaya Optimization Based Model Reduction;254
31.1;1 Introduction;254
31.2;2 Mathematical Modeling of PMSM Drive and Control;255
31.2.1;2.1 PMSM Drive;256
31.3;3 Order Reduction and Controller Design for PMSM;257
31.3.1;3.1 Jaya Optimization Algorithm [21, 22];257
31.3.2;3.2 Current Control Loop;257
31.3.3;3.3 Speed Control Loop;259
31.3.4;3.4 Tuning of PI Controller Using Optimization Algorithm;260
31.4;4 Conclusion;262
31.5;References;262
32;Jaya Optimization-Based PID Controller for Z-Source Inverter Using Model Reduction;264
32.1;1 Introduction;264
32.2;2 Z-Source Inverter;266
32.3;3 Jaya Optimization Algorithm;268
32.4;4 Simulation and Results;271
32.5;5 Conclusion;273
32.6;References;273
33;Stability Analysis of an Offshore Wind and Marine Current Farm in Grid Connected Mode Using SMES;275
33.1;1 Introduction;275
33.2;2 Configuration of the Studied Systems;276
33.2.1;2.1 Modeling of OWF;276
33.2.2;2.2 DFIG Modeling;277
33.2.3;2.3 Marine Current Turbine;278
33.2.4;2.4 SCIG Modeling;279
33.3;3 SMES Modeling;279
33.4;4 H-Infinity Controller of SMES;280
33.5;5 Simulation Results and Discussion;282
33.6;6 Conclusion;283
33.7;References;284
34;Modeling and Simulation of Proton Exchange Membrane Fuel Cell Hybrid Electric Vehicle;286
34.1;1 Introduction;286
34.2;2 Architecture of Fuel Cell Hybrid Electric Vehicle;288
34.2.1;2.1 Fuel Cell;288
34.2.2;2.2 Unidirectional DC–DC Converter;288
34.2.3;2.3 Bidirectional DC–DC Converter;289
34.2.4;2.4 Energy Storage System (ESS);289
34.3;3 Simulation Results and Discussion;290
34.3.1;3.1 Case Study 1 (Cold Start Mode);290
34.3.2;3.2 Case Study-2 (Normal Operating Mode);290
34.3.3;3.3 Case Study 3 (Acceleration Mode);291
34.3.4;3.4 Case Study 4 (Deceleration Mode);292
34.4;4 Conclusion;293
34.5;References;294
35;Optimum Performance of Carbon Nanotube Field-Effect Transistor Based Sense Amplifier D Flip-Flop Circuits;297
35.1;1 Introduction;297
35.2;2 Theoretical Analysis and Design Consideration of Existing D Flip-Flop Topologies (CNFET);298
35.3;3 Carbon Nanotube Field-Effect Transistor (CNFET);300
35.3.1;3.1 Diameter of CNFET (DCNT);300
35.3.2;3.2 Threshold Voltage (Vth);301
35.3.3;3.3 Width of CNTFET;301
35.3.4;3.4 On Off Current Ratio;301
35.3.5;3.5 Transconductance (gm);302
35.4;4 Simulated Results of Various High-Performance D Flip-Flop Designs;302
35.5;5 Conclusion;304
35.6;References;304
36;Flower Pollination Based Solar PV Parameter Extraction for Double Diode Model;306
36.1;1 Introduction;307
36.2;2 Modeling of Solar PV;308
36.3;3 Problem Formulation;309
36.4;4 Flower Pollination Algorithm;310
36.5;5 Simulation Results and Discussions;312
36.6;6 Conclusion;314
36.7;References;314
37;Cost–Benefit Calculation Using AB2X4 (A = Zn, Cd; B = Ga; X = Te): A Promising Material for Solar Cells;316
37.1;1 Introduction;316
37.2;2 Theoretical Methodology;317
37.3;3 Result Discussion;317
37.3.1;3.1 Method Overview;318
37.3.2;3.2 PV Module Cost Calculation;318
37.4;4 Conclusion;320
37.5;References;320
38;Detection and Analysis of Power System Faults in the Presence of Wind Power Generation Using Stockwell Transform Based Median;321
38.1;1 Introduction;322
38.2;2 Test System Used for the Proposed Study;323
38.3;3 Proposed Methodology;324
38.3.1;3.1 Proposed Fault Index;324
38.3.2;3.2 Stockwell Transform;324
38.4;4 S-Transform Based Simulation Results with Discussion;325
38.4.1;4.1 Line to Ground Fault;325
38.4.2;4.2 Double Line Fault;326
38.4.3;4.3 Double Line to Ground Fault;327
38.4.4;4.4 Three-Phase Fault Involving Ground;328
38.4.5;4.5 Comparative Study;329
38.5;5 Conclusion;330
38.6;References;330
39;A Directional Relaying Scheme for Microgrid Protection;332
39.1;1 Introduction;332
39.2;2 Test Microgrid;334
39.3;3 Directional Relaying Algorithm;334
39.3.1;3.1 Detectors for the Directional Approach;334
39.3.2;3.2 Proposed Technique;336
39.4;4 Simulation Results;336
39.4.1;4.1 Faults During Grid-Connected Mode;337
39.4.2;4.2 Results for Fault During Islanded Mode;338
39.4.3;4.3 Results for Load Switching;338
39.4.4;4.4 Results for High-Impedance Fault (HIF) in Islanding Mode;339
39.5;5 Conclusion;340
39.6;References;340
40;Wavefunctions and Optical Gain in In0.24Ga0.76N/GaN Type-I Nano-heterostructure Under External Uniaxial Strain;342
40.1;1 Introduction;342
40.2;2 Device Structure and Modeling;343
40.3;3 Results and Discussion;345
40.4;4 Conclusions;349
40.5;References;349
41;Cost–Benefit Analysis in Distribution System of Jaipur City After DG and Capacitor Allocation;351
41.1;1 Introduction;351
41.2;2 Problem Formulation;352
41.3;3 Proposed Technique;353
41.4;4 Results;354
41.4.1;4.1 69 Bus Test System;354
41.4.2;4.2 130 Bus (Jaipur City) System;356
41.5;5 Conclusion;357
41.6;References;358
42;Comparative Simulation Study of Dual-Axis Solar Tracking System on Simulink Platform;359
42.1;1 Introduction;359
42.2;2 Developed Solar Tracking System;360
42.3;3 Characteristics of PV Cell;361
42.3.1;3.1 Simulink Block Diagram;362
42.4;4 Simulation Results and Discussion;364
42.4.1;4.1 Elevated Tracking Results;364
42.4.2;4.2 Azimuthal Tracking Results;364
42.5;5 Conclusion;365
42.6;References;365
43;Performance Evaluation and Quality Analysis of Line and Node Based Voltage Stability Indices for the Determination of the Voltage Instability Point;366
43.1;1 Introduction;366
43.2;2 Existing Line and Node Based Voltage Stability Indices;367
43.2.1;2.1 Maximum Loadability Index (MLI);367
43.2.2;2.2 Loadability Index (Lp);368
43.2.3;2.3 Line Loadability Index (Ls);368
43.2.4;2.4 Line Stability Index (Lmn);368
43.2.5;2.5 Line Stability Factor (LQP);369
43.2.6;2.6 Fast Voltage Stability Index (FVSI);369
43.2.7;2.7 Line Collapse Proximity Index (LCPI);369
43.2.8;2.8 L-Index;369
43.3;3 Illustrative Example;370
43.3.1;3.1 With One Fictitious Bus in the Middle of the Transmission Line;371
43.3.2;3.2 With One Fictitious Bus at (3/4)th Length of the Transmission Line;373
43.4;4 Conclusion;374
43.5;References;374
44;Channel Estimation in Massive MIMO with Spatial Channel Correlation Matrix;376
44.1;1 Introduction;376
44.2;2 System Model for Uplink Pilot Transmission;377
44.3;3 MMSE Channel Estimation;378
44.4;4 Spatial Channel Correlation and Pilot Contamination;379
44.4.1;4.1 Impact of Spatial Correlation on Channel Estimation;380
44.4.2;4.2 Impact of Pilot Contamination on Channel Estimation;380
44.5;5 EW-MMSE and LS Estimation Schemes;380
44.5.1;5.1 Element-Wise MMSE Channel Estimator;380
44.5.2;5.2 Least-Square Channel Estimator;381
44.6;6 Simulation Results;381
44.7;7 Conclusion;382
44.8;References;383
45;A New Array Reconfiguration Scheme for Solar PV Systems Under Partial Shading Conditions;385
45.1;1 Introduction;385
45.2;2 System Description;387
45.2.1;2.1 Modeling of a Total Cross Tied TCT Connection;387
45.3;3 Methodology;388
45.4;4 Simulation Results and Discussion;389
45.4.1;4.1 Pattern 1—Short Wide;389
45.4.2;4.2 Pattern 2—Long Wide;392
45.5;5 Conclusion;393
45.6;References;394
46;Adaptability Analysis of Particle Swarm Optimization Variants in Maximum Power Tracking for Solar PV Systems;395
46.1;1 Introduction;395
46.2;2 System Description;396
46.3;3 Modelling of PV Cell;396
46.3.1;3.1 Characteristics of PV Module;398
46.3.2;3.2 Characteristics of PV Array Under Partial Shading Conditions;399
46.4;4 Particle Swarm Optimization: Outline of PSO;399
46.4.1;4.1 Neighbourhood Selection Scheme;401
46.5;5 Simulation and Results Discussion;402
46.6;6 Conclusion;403
46.7;References;407
47;Fault Location Methods in HVDC Transmission System—A Review;408
47.1;1 Introduction;408
47.2;2 Literature Review on Fault Location Techniques;412
47.3;3 Conclusion;415
47.4;References;415
48;Optimal Reactive Power Dispatch Through Minimization of Real Power Loss and Voltage Deviation;417
48.1;1 Introduction;419
48.2;2 Problem Formulation;420
48.2.1;2.1 Objective Function;420
48.2.2;2.2 System Constraints;420
48.2.3;2.3 General Formulation of the Objective Function;421
48.3;3 Solution Methodology;421
48.4;4 Simulation Result;422
48.5;5 Conclusion;425
48.6;References;425
49;IoT Enabled Intelligent Energy Management and Optimization Scheme with Controlling and Monitoring Approach in Modern Classroom Applications;427
49.1;1 Introduction;428
49.2;2 Related Works;428
49.3;3 Contextual Analysis/Background Survey;429
49.4;4 Energy Management in Campus: Challenges;430
49.5;5 Existing System;431
49.6;6 Methodology;431
49.6.1;6.1 Design Criteria;431
49.6.2;6.2 Device Configuration and Working Principles;431
49.7;7 Testing and Evaluation of Project Implementation;432
49.8;8 Future Scope and Conclusion;435
49.9;References;435
50;High Power Density Parallel LC-Link PV Inverter for Stand-alone and Grid Mode of Operation;437
50.1;1 Introduction;438
50.2;2 Operation Principle Under Different Modes;439
50.2.1;2.1 Configuration;439
50.2.2;2.2 Principle of Operation;440
50.3;3 Parameter Design Procedure;441
50.4;4 Zero Voltage Switching Operation (ZVS);444
50.5;5 Simulation Results;445
50.6;6 Conclusions;448
50.7;References;449
51;A Hybrid Forecasting Model Based on Artificial Neural Network and Teaching Learning Based Optimization Algorithm for Day-Ahead Wind Speed Prediction;450
51.1;1 Introduction;450
51.2;2 Working Principle of Hybrid Forecasting Model;451
51.3;3 Forecasting Results and Discussions;453
51.4;4 Conclusion;458
51.5;References;458
52;Risk Averse Energy Management for Grid Connected Microgrid Using Information Gap Decision Theory;459
52.1;1 Introduction;460
52.2;2 Information Gap Decision Theory;461
52.3;3 Problem Formulation;462
52.3.1;3.1 Deterministic MG Energy Management;462
52.3.2;3.2 IGDT Based MG Energy Management;462
52.4;4 Numerical Simulation;463
52.5;5 Conclusions;466
52.6;References;466
53;Power Quality Improvement of Microgrid Using Double Bridge Shunt Active Power Filter (DBSAPF);468
53.1;1 Introduction;468
53.2;2 Shunt Active Power Filter;469
53.3;3 Hysteresis Control Technique;470
53.4;4 Proposed Double Bridge SAPF;471
53.5;5 Simulation Results;472
53.5.1;5.1 Case Study 1;473
53.5.2;5.2 Case Study 2;474
53.6;6 Conclusion;475
53.7;References;476
54;Opposition Theory Enabled Intelligent Whale Optimization Algorithm;477
54.1;1 Introduction;477
54.2;2 Whale Optimization Algorithm;479
54.2.1;2.1 Girdling Prey;479
54.2.2;2.2 Bubble-Net Attacking Method (Exploitation Phase);480
54.2.3;2.3 Prey Search (Exploration Phase);480
54.3;3 Opposition Theory Enabled Intelligent Whale Optimization Algorithm;481
54.3.1;3.1 Implementation of OBL on OIWOA;481
54.3.2;3.2 Implementation of Sinusoidal Function;482
54.3.3;3.3 Implementation of Crossover;482
54.4;4 Results and Discussions;482
54.5;5 Conclusions;484
54.6;References;484
55;Adaptive Inertia-Weighted Firefly Algorithm;486
55.1;1 Introduction;486
55.2;2 Firefly Algorithm;488
55.3;3 Improved Firefly Algorithm;489
55.4;4 Simulation Results and Discussions;491
55.4.1;4.1 Results on Uni-modal Functions;491
55.4.2;4.2 Results on Multi-modal and Fixed Dimension Multi-modal Functions;492
55.5;5 Conclusions;492
55.6;References;493
56;A Review of Scheduling Techniques and Communication Protocols for Smart Homes Capable of Implementing Demand Response;495
56.1;1 Introduction;495
56.2;2 Scheduling Techniques;496
56.2.1;2.1 Rule-Based Scheduling Techniques;496
56.2.2;2.2 Training-Based Artificial Intelligent Techniques;497
56.2.3;2.3 Heuristic and Meta-Heuristic AI Techniques;497
56.3;3 Communication;498
56.3.1;3.1 Wired Communication Protocols;498
56.3.2;3.2 Wireless-Based Communication;499
56.3.3;3.3 Hybrid and Integrated Protocols;499
56.4;4 Conclusion;500
56.5;References;500
57;A Robust Open-Loop Frequency Estimation Method for Single-Phase Systems;504
57.1;1 Introduction;504
57.2;2 Even Harmonics Generation;505
57.3;3 Filtering Requirements;506
57.3.1;3.1 DC-Offset Rejection;506
57.3.2;3.2 Extraction of Fundamental Orthogonal Components;507
57.3.3;3.3 Elimination of Higher Order Harmonics;508
57.4;4 Frequency Estimation;509
57.4.1;4.1 Simulation Setup and Results;509
57.5;5 Conclusion;512
57.6;References;512
58;Demand-Side Load Management for Peak Shaving;514
58.1;1 Introduction;514
58.2;2 Demand-Side Load Management;515
58.3;3 Modeling and Simulation;517
58.3.1;3.1 Modeling;517
58.3.2;3.2 Simulation Process;518
58.4;4 Simulation Results;520
58.5;5 Conclusions;523
58.6;References;523
59;A New Line Voltage Stability Index (NLVSI) For Voltage Stability Assessment;524
59.1;1 Introduction;524
59.2;2 Existing Line Based Voltage Stability Indices;526
59.2.1;2.1 Line Stability Index (Lmn);526
59.2.2;2.2 Fast Voltage Stability Index (FVSI);526
59.2.3;2.3 Line Stability Factor (LQP);526
59.2.4;2.4 Line Voltage Reactive Power Index (VQIline);527
59.2.5;2.5 New Voltage Stability Index (NVSI);527
59.3;3 Effect of Delta on Voltage;527
59.4;4 Proposed Index Formulation;529
59.5;5 Representation of ZIP Load Model;531
59.6;6 Test Case Results;531
59.6.1;6.1 When Conventional (i.e. Constant Power) Load is Used;532
59.6.2;6.2 When ZIP Load Model is Used;534
59.6.3;6.3 Results Comparison Between Conventional Load and ZIP Load Model;534
59.7;7 Conclusion;536
59.8;References;537
60;A Comprehensive Comparative Economic Analysis of ACO and CS Technique for Optimal Operation of Stand-alone HES;538
60.1;1 Introduction;540
60.2;2 Mathematical Formulation;541
60.2.1;2.1 Modeling of System Components;542
60.2.2;2.2 Operation Strategy;545
60.2.3;2.3 Objective Function;546
60.2.4;2.4 Constraints;546
60.3;3 Ant Colony Optimization;547
60.4;4 Cuckoo Search Technique;548
60.4.1;4.1 Levy Flights Technique;548
60.4.2;4.2 Random Walk Technique;549
60.5;5 Comparative Analysis;549
60.6;6 Conclusion;552
60.7;References;553
61;Demand Response in Distribution Systems: A Comprehensive Review;554
61.1;1 Introduction;554
61.2;2 Background and Classification of DRPs;555
61.3;3 An Overview of DR;557
61.4;4 Conclusion;560
61.5;References;560
62;Stochastic Operational Management of Grid-Connected Microgrid Under Uncertainty of Renewable Resources and Load Demand;562
62.1;1 Introduction;562
62.2;2 Stochastic Modeling of Renewable Generation and System Load;563
62.2.1;2.1 Stochastic Modeling of Wind Power Generation;563
62.2.2;2.2 Stochastic Modeling of PV Power Generation;564
62.2.3;2.3 Stochastic Modeling of System Load Demand;565
62.2.4;2.4 Combined Stochastic Modeling of the System;565
62.2.5;2.5 Tournament Selection Based Scenarios Sampling;565
62.3;3 Problem Formulation;565
62.3.1;3.1 Objective Function;565
62.3.2;3.2 Constraints;566
62.4;4 Solution Methodology;567
62.5;5 Simulation Results and Discussion;567
62.6;6 Conclusion;569
62.7;References;570
63;Real-Time High-Speed Novel Data Acquisition System Based on ZYNQ;571
63.1;1 Introduction;572
63.2;2 Overview of the Hardware Platform and Contemporary Solutions;572
63.3;3 Firmware Design of Data Acquisition System;573
63.4;4 Software Interface for Data Acquisition System;574
63.5;5 Results and Discussion;576
63.6;6 Conclusion;577
63.7;References;578
64;Exergetic Analysis of Glazed Photovoltaic Thermal (Single-Channel) Module Using Whale Optimization Algorithm and Genetic Algorithm;579
64.1;1 Introduction;580
64.2;2 System Description;582
64.3;3 Tool Used for Optimization;582
64.4;4 Result and Discussion;583
64.5;5 Conclusion;587
64.6;Appendix: Optimized Value of Parameters;587
64.7;References;588
65;An 8-Bit Charge Redistribution SAR ADC;589
65.1;1 Introduction;589
65.2;2 8-Bit SAR ADC Architecture;591
65.3;3 Implementation of Inner Blocks;593
65.3.1;3.1 S/H Circuit;593
65.3.2;3.2 Comparator;594
65.4;4 Simulation Results;595
65.5;5 Conclusion;597
65.6;References;597
66;Analysis of Triple-Threshold Technique for Power Optimization in SRAM Bit-Cell for Low-Power Applications at 45 Nm CMOS Technology;598
66.1;1 Introduction;598
66.2;2 Approach;600
66.3;3 Analysis and Result;600
66.3.1;3.1 Data Stability;600
66.3.2;3.2 Read Noise Margin;600
66.3.3;3.3 Write Noise Margin;601
66.3.4;3.4 Average Power and Leakage Power;602
66.4;4 Conclusion;604
66.5;References;604
67;Low Power Adder Circuits Using Various Leakage Reduction Techniques;606
67.1;1 Introduction;606
67.2;2 Literature Review;607
67.2.1;2.1 Sleep Transistor Technique;607
67.2.2;2.2 Stack Transistor Technique;608
67.2.3;2.3 Super Cutoff (SCCMOS) Technique;609
67.3;3 Implementation of Adder Circuit;610
67.3.1;3.1 1-Bit Full Adder;610
67.3.2;3.2 4-Bit Ripple Carry Adder;612
67.4;4 Simulation and Analysis;612
67.5;5 Conclusion;614
67.6;References;615
68;A Nature-Inspired Metaheuristic Swarm Based Optimization Technique BFOA Based Optimal Controller for Damping of SSR;617
68.1;1 Introduction;617
68.2;2 System Configuration;618
68.3;3 Development of Overall System Model;619
68.4;4 Application of Optimal Control Theory;619
68.5;5 Optimal Parameter Selection Using BFOA;619
68.5.1;5.1 A Brief Overview of BFOA;619
68.6;6 Results and Discussions;620
68.6.1;6.1 Case Study with 60% Series Compensation;620
68.7;7 Conclusion;622
68.8;References;624
69;New Fuzzy Divergence Measures, Series, Its Bounds and Applications in Strategic Decision-Making;626
69.1;1 Introduction;626
69.2;2 New Information Divergence Measures;627
69.3;3 Series of Fuzzy Divergence Measures;628
69.4;4 Some New Other Fuzzy Information Divergence Measures;632
69.5;5 New Information Divergence and Their Relation with Other Well-Known Divergence Measures;633
69.6;6 Application of Proposed Series of Fuzzy Divergence Making in Strategic Decision-Making;635
69.7;7 Conclusion;638
69.8;References;638
70;Mutual Coupling Reduction of Biconvex Lens Shaped Patch Antenna for 5G Application;639
70.1;1 Introduction;639
70.2;2 Design of the Proposed Antenna;640
70.2.1;2.1 Rotman Lens Equations and Proposed Modification;640
70.2.2;2.2 Design of the Perturbed Strip;641
70.3;3 Design and Simulation of Proposed Antenna;641
70.3.1;3.1 Substrate Material and Height;641
70.3.2;3.2 Design of the Proposed Antenna;642
70.3.3;3.3 Results from Simulation of the Proposed Antenna;642
70.4;4 Conclusion;644
70.5;References;646
71;Analysis of Anti-Islanding Protection Methods Integrated in Distributed Generation;647
71.1;1 Introduction;647
71.2;2 Passive Methods;648
71.3;3 Active Methods;650
71.4;4 Simulation Results;652
71.5;5 Conclusion;654
71.6;References;654
72;Color Image Watermarking with Watermark Hashing;656
72.1;1 Introduction;656
72.2;2 Background;657
72.2.1;2.1 Singular Value Decomposition (SVD);657
72.2.2;2.2 Discrete Wavelet Transform (DWT);658
72.3;3 Hashing Techniques;658
72.4;4 Experiments and Results;659
72.5;5 Conclusions;662
72.6;References;663
73;Global Neighbourhood Algorithm Based Event-Triggered Automatic Generation Control;665
73.1;1 Introduction;665
73.2;2 AGC System Modelling;667
73.3;3 Problem Formulation;668
73.3.1;3.1 Objective Function;668
73.3.2;3.2 Global Neighbourhood Algorithm (GNA);668
73.3.3;3.3 Delay/Sampling Time Dependent Stability;668
73.4;4 Case Study;670
73.4.1;4.1 Case I;670
73.4.2;4.2 Case II;672
73.5;5 Conclusions;673
73.6;References;673
74;A Review on Voltage and Frequency Control of Micro Hydro System;675
74.1;1 Introduction;675
74.2;2 Voltage and Frequency Regulation in Micro Hydro System;677
74.3;3 Classification of ELC on the Basis of Loading;679
74.4;4 Discussion;681
74.5;5 Conclusion;682
74.6;References;682
75;Performance Analysis of Solar and Plug-in Electric Vehicle's Integration to the Power System with Automatic Generation Control;684
75.1;1 Introduction;684
75.2;2 Proposed System Study;685
75.3;3 Selection of Controller and Objective Function;686
75.4;4 Jaya Optimization Technique;687
75.5;5 Result and Analysis;688
75.6;6 Conclusion;691
75.7;7 Appendix;691
75.8;References;691
76;A Bibliographical View on Research and Developments of Photovoltaic and Thermal Technologies as a Combined System: PV/T System;693
76.1;1 Introduction;694
76.2;2 PV/T Air Collector;695
76.2.1;2.1 Effect of Glazing;696
76.2.2;2.2 Effect of Adding Thin Metallic Sheets (TMS) and Fins;696
76.2.3;2.3 Effect of Packing Factor;697
76.3;3 PV/T Water;697
76.4;4 PV/T Combi;698
76.5;5 Modelling of PV/T Collector;699
76.6;6 Optimization Using Soft Computing;700
76.7;7 Conclusion;701
76.8;References;701
77;UPM-NoC: Learning Based Framework to Predict Performance Parameters of Mesh Architecture in On-Chip Networks;703
77.1;1 Introduction;704
77.2;2 Related Work;705
77.2.1;2.1 Learning Models Used in Different Aspects of NoC;705
77.3;3 Design Strategy;706
77.3.1;3.1 Detailed Layout of Unified Performance Model;706
77.3.2;3.2 Data Collection Using Booksim Simulator;707
77.3.3;3.3 Generation of Dataset;708
77.4;4 Results and Discussion;708
77.4.1;4.1 Experimental Results;708
77.4.2;4.2 Validation;710
77.4.3;4.3 Runtime Comparison;711
77.5;5 Conclusion;712
77.6;References;712
78;Comparison of Performance Analysis of Optimal Controllers for Frequency Regulation of Three-Area Power System;714
78.1;1 Introduction;714
78.2;2 Three-Area System Under Study;716
78.3;3 Optimization of Controller Gains;717
78.4;4 Results and Discussion;718
78.5;5 Conclusion;721
78.6;References;721
79;Optimal DG Allocation in a Microgrid Using Droop-Controlled Load Flow;723
79.1;1 Introduction;723
79.2;2 Problem Formulation;725
79.3;3 Methodology;726
79.3.1;3.1 Droop-Controlled Load Flow (DCLF);726
79.3.2;3.2 Non-Dominated Sorted Genetic Algorithm;727
79.3.3;3.3 Fuzzy Satisfying Method;727
79.4;4 Results and Discussions;727
79.5;5 Conclusion;728
79.6;References;729
80;A Comparative Study of Classification Algorithms for Predicting Liver Disorders;731
80.1;1 Introduction;731
80.2;2 Literature Review;732
80.3;3 Methodology;734
80.3.1;3.1 Data Collection;734
80.3.2;3.2 Data Preprocessing;734
80.3.3;3.3 Applying Different Classification Algorithms;734
80.3.4;3.4 Predicting the Test Set Results;735
80.3.5;3.5 Comparison of Models;735
80.4;4 Results and Discussion;735
80.5;5 Conclusion and Future Work;737
80.6;References;737
81;Performance Analysis of Fabricated Buck-Boost MPPT Charge Controller;739
81.1;1 Introduction;739
81.2;2 Experimental Setup;740
81.3;3 Experimental Result;741
81.4;4 Conclusion;745
81.5;References;745
82;Performance Improvement of Cycloconverter Fed Induction Machine Using Shunt Active Power Filter;747
82.1;1 Introduction;747
82.2;2 Input Current of Cycloconverter;748
82.2.1;2.1 Harmonic Analysis of Input Current;749
82.3;3 Harmonic Analysis of Input Current of Cycloconverter Fed Induction Machine;749
82.4;4 Design Shunt Active Power Filter;751
82.4.1;4.1 Voltage Source Converter;751
82.4.2;4.2 Fuzzy Logic Based Controller;752
82.4.3;4.3 Hysteresis Band Current Control Technique;754
82.4.4;4.4 Simulation of Cycloconverter Fed Induction Machine with Shunt Active Power Filter;754
82.5;5 Conclusion;757
82.6;References;758
83;Comparative Analysis of Speaker Recognition System Based on Voice Activity Detection Technique, MFCC and PLP Features;759
83.1;1 Introduction;759
83.2;2 Methodology;760
83.2.1;2.1 Voice Activity Detection (VAD);761
83.2.2;2.2 MFCC;762
83.2.3;2.3 Vector Quantization;762
83.2.4;2.4 Perceptual Linear Predictive (PLP);763
83.2.5;2.5 Database;763
83.3;3 Results and Discussion;764
83.4;4 Conclusions;765
83.5;References;765
84;Nonintrusive Load Monitoring: Making Smart Meters Smarter;766
84.1;1 Introduction;766
84.1.1;1.1 Need for NILM in Smart Meters;766
84.2;2 Working of NILM and Challenges with It;767
84.2.1;2.1 Data Acquisition;768
84.3;3 Proposal;768
84.3.1;3.1 Security Feature to Safeguard Consumer as Well as Appliance;768
84.3.2;3.2 NILM to Predict Appliance Health;770
84.4;4 Conclusion;770
85;Stabilization of Chaotic Systems Using Robust Optimal Controller;772
85.1;1 Introduction;772
85.2;2 Problem Statement;773
85.3;3 Optimal Controller Design;774
85.4;4 Design of Sliding Mode Controller;775
85.5;5 Simulation Results;777
85.6;6 Conclusion;779
85.7;References;779
86;Jaya Algorithm Based Optimal Allocation of Distributed Energy Resources;781
86.1;1 Introduction;781
86.2;2 Problem Description;783
86.2.1;2.1 Boundary Limit of Node Voltage;783
86.2.2;2.2 Power Balance;784
86.2.3;2.3 Distribution Thermal Limit;784
86.2.4;2.4 DERs Generation;784
86.3;3 Description of the Jaya Algorithm;784
86.4;4 Simulation Results;786
86.4.1;4.1 Test System 1:33 Bus Radial Distribution Network;787
86.4.2;4.2 Test System 2: 69 Bus Radial Distribution Network;787
86.5;5 Conclusion;789
86.6;References;789
87;Bayesian Game Model: Demand Side Management for Residential Consumers with Electric Vehicles;791
87.1;1 Introduction;791
87.2;2 System Model;792
87.2.1;2.1 Energy Consumption Cost Model;793
87.2.2;2.2 Payoff Model for EV’s;794
87.3;3 Bayesian Game for Household Consumers;795
87.4;4 Simulation Results;796
87.5;5 Conclusion;798
87.6;References;798
88;Classification of Power System Disturbances Using Support Vector Machine in FPGA;800
88.1;1 Introduction;800
88.2;2 Support Vector Machine;801
88.2.1;2.1 Linear SVM;801
88.2.2;2.2 Nonlinear SVM;802
88.3;3 Power System Transient;804
88.4;4 SVM Implementation;805
88.4.1;4.1 Software Simulation of SVM in MATLAB;805
88.4.2;4.2 Hardware Co-simulation of SVM in FPGA;806
88.5;5 Simulation Result;808
88.6;6 Conclusion;809
88.7;References;809
89;Designing a Smart System for Air Quality Monitoring and Air Purification;811
89.1;1 Introduction;811
89.2;2 Filters and Sensors;812
89.2.1;2.1 Filters;812
89.2.2;2.2 Comparison of Various Filters Used in the Air Purifiers;814
89.2.3;2.3 Sensors;814
89.3;3 Proposed Model;815
89.4;4 Results;816
89.5;5 Conclusion;816
89.6;6 Future Scope;817
89.7;References;817
90;Activation Map Networks with Deep Graphical Model for Semantic Segmentation;819
90.1;1 Introduction;820
90.2;2 Context Deep CRFs;820
90.3;3 Pairwise Potential Functions;821
90.4;4 Prognostic Process;822
90.5;5 Prognostic Consummation Phase;823
90.6;6 Practical Experiments with Validation Set on Matlab Contextual Modeling;823
90.7;7 Conclusion;823
90.8;References;825
91;Grey Wolf Optimized PI Controller for Hybrid Power System Using SMES;827
91.1;1 Introduction;827
91.2;2 Hybrid Power System;828
91.2.1;2.1 Mathematical Modelling of HPS;828
91.3;3 Grey Wolf Optimization;830
91.4;4 Simulation Results and Analysis;831
91.5;5 Conclusion;834
91.6;References;835
92;JAYA-Evaluated Frequency Control Design for Hydroelectric Power System Using RFB and UPFC;836
92.1;1 Introduction;837
92.2;2 Studied Model;838
92.3;3 JAYA-Optimized LFC Designs;838
92.4;4 Result Analysis;841
92.5;5 Conclusion;842
92.6;References;844
93;A Human Face-Shaped Microstrip Patch Antenna for Ultra-Wideband Applications;845
93.1;1 Introduction;845
93.2;2 Antenna Geometry;846
93.3;3 Simulation Results;847
93.4;4 Conclusion;849
93.5;References;851
94;Scheduling Energy Storage to Provide Balancing During Line Contingency at High Wind Penetration;853
94.1;1 Introduction;855
94.2;2 Problem Formulation;856
94.2.1;2.1 Objective Function;856
94.2.2;2.2 Operating Constraints;856
94.2.3;2.3 Wind Generation Constraints;857
94.2.4;2.4 Storage Constraints;857
94.2.5;2.5 Power Balance;858
94.3;3 Data and Result Analysis;858
94.3.1;3.1 Data;858
94.3.2;3.2 Result Analysis;858
94.4;4 Conclusion;861
94.5;References;861
95;Multilevel Inverter Topologies in Renewable Energy Applications;863
95.1;1 Introduction;864
95.2;2 Classical MLI Topologies;865
95.2.1;2.1 Neutral Point Clamped MLI (NPC MLI);865
95.2.2;2.2 Flying Capacitor MLI (FC MLI);866
95.2.3;2.3 Cascaded H-Bridge MLI (CHB MLI);867
95.3;3 RCC Topologies for LV Applications;867
95.3.1;3.1 Developed Cascaded MLI (DC MLI);867
95.3.2;3.2 Cascaded Sub-multilevel Inverter (CSMLI);867
95.3.3;3.3 Multilevel DC-Link Inverter (MLDCLI);869
95.4;4 MLIs in Renewable Energy Applications;869
95.4.1;4.1 Photovoltaic Systems;869
95.4.2;4.2 Wind Energy Conversion System (WECS);870
95.4.3;4.3 Battery Storage Energy Systems (BSES);870
95.5;5 Conclusion;871
95.6;References;871
96;A Review on Demand Side Management Forecasting Models for Smart Grid;875
96.1;1 Introduction;875
96.2;2 Load Forecasting;877
96.2.1;2.1 Traditional Forecasting Method;877
96.2.2;2.2 Modern Forecasting Method;879
96.3;3 Comparative Study of Forecasting Techniques;880
96.4;4 Challenges and Conclusion;881
96.5;References;881
97;Detection of Suspicious Activity in ATM Booth;883
97.1;1 Introduction;883
97.1.1;1.1 Video Surveillance;884
97.1.2;1.2 Overview;884
97.2;2 Related Work;884
97.3;3 Background;885
97.3.1;3.1 Automated Teller Machine;885
97.3.2;3.2 Suspicious Activities in ATM Booth;886
97.4;4 Multiple Object Detection;886
97.4.1;4.1 Viola–Jones Algorithm;886
97.4.2;4.2 Approach Used for Multiple Person Detection;888
97.5;5 Helmet Detection;888
97.5.1;5.1 Circle Hough Transformation;888
97.5.2;5.2 Approach Used for Helmet Detection;891
97.6;6 Results Analysis;891
97.7;7 Conclusion;895
97.8;References;896
98;Mitigation of Power Quality for Wind Energy Using Transmission Line Based on D-STATCOM;898
98.1;1 Introduction;898
98.2;2 Proposed Work;899
98.3;3 Result and Discussion;900
98.4;4 Conclusion;904
98.5;References;905
99;Performance Evaluation of Solar Power Plant;907
99.1;1 Introduction;907
99.2;2 Methodology and Input Parameters;908
99.3;3 Result and Discussion;909
99.4;4 Conclusion;909
99.5;References;911
100;GWO Based PID Controller Optimization for Robotic Manipulator;913
100.1;1 Introduction;913
100.2;2 Modeling of Robotic Manipulator;914
100.3;3 Trajectory for Manipulator;916
100.4;4 PID Controller;916
100.5;5 Optimization Technique;917
100.5.1;5.1 GWO Optimization;917
100.6;6 Simulation and Result Analysis;918
100.7;7 Conclusion;920
100.8;References;921
101;A 26 W Power Supply Based on Luo Converter with Improved Power Factor and Total Harmonic Distortion;922
101.1;1 Introduction;922
101.2;2 Proposed Model: A Power Factor Corrected (PFC) Power Supply Based on Luo Converter;923
101.3;3 Components Selection of Power Supply;924
101.4;4 System Loop Gain Analysis;924
101.5;5 Model Stability Without Controller in Feedback;926
101.6;6 Controller Design and Analysis of Stability System with Compensation Network;926
101.6.1;6.1 Proportional Integral (PI) Controller;927
101.6.2;6.2 Compensator’s Component Design;928
101.6.3;6.3 Model with Proposed Compensated Network: Stability Analysis;928
101.7;7 Simulated Circuit Diagram and Analysis;929
101.8;8 Results Analysis;929
101.9;9 Conclusions;931
101.10;References;931
102;Optimal Strategic Bidding Using Intelligent Gravitational Search Algorithm for Profit Maximization of Power Suppliers in an Emerging Power Market;932
102.1;1 Introduction;932
102.2;2 Problem Formulation;934
102.3;3 Intelligent GSA;935
102.3.1;3.1 Opposition Phenomenon in GSA;936
102.3.2;3.2 Update Mode of Gravity Constant;936
102.4;4 Results and Discussion;936
102.5;5 Conclusion;939
102.6;References;939
103;Synchrophasor Measurements Assisted Naïve Bayes Classification Based Real-Time Transient Stability Prediction of Power System;941
103.1;1 Introduction;941
103.2;2 Naïve Bayes Classifier;942
103.3;3 Proposed Methodology;943
103.3.1;3.1 Optimal PMU Placement Formulation;944
103.3.2;3.2 Data Generation;944
103.3.3;3.3 Feature Selection and Target Assignment;944
103.3.4;3.4 Training, Testing and New Data;945
103.3.5;3.5 Proposed Synchrophasor Measurement Assisted Naïve Bayes Classifier;945
103.4;4 Simulation and Results;945
103.4.1;4.1 Optimal PMU Placement;945
103.4.2;4.2 PMU-Naïve Bayes Based Real-Time Transient Stability Prediction;946
103.5;5 Conclusion;947
103.6;References;947
104;Device Modeling and Characteristics of Solution Processed Perovskite Solar Cell at Ambient Conditions;949
104.1;1 Introduction;949
104.2;2 Methodology;951
104.2.1;2.1 Materials;951
104.2.2;2.2 Preparation of Layers;952
104.2.3;2.3 Device Fabrication;952
104.3;3 Characterization;954
104.3.1;3.1 I–V Measurement;954
104.3.2;3.2 UV-Visible Analysis;954
104.4;4 Summary;955
104.5;References;956
105;Control and Remote Sensing of an Irrigation System Using ZigBee Wireless Network;957
105.1;1 Introduction;958
105.2;2 Materials and Methods;959
105.2.1;2.1 Conceptual System Design;959
105.2.2;2.2 Sensor-Based In-field Station;960
105.2.3;2.3 Irrigation Control Station;961
105.2.4;2.4 Base Station;962
105.2.5;2.5 Graphical User Interface (Gui);962
105.2.6;2.6 Mail Transfer;964
105.3;3 Application and Observations;964
105.4;4 Limitation;965
105.5;5 Conclusion and Future Work;965
105.6;References;966
106;Analysis and Classification of Maximum Power Point Tracking (MPPT) Techniques: A Review;967
106.1;1 Introduction;967
106.2;2 Introduction to MPPT Techniques;968
106.3;3 Types of MPPT Techniques;969
106.3.1;3.1 Conventional Methods;969
106.3.2;3.2 Soft Computing Methods;972
106.3.3;3.3 Comparative Study;974
106.4;4 Conclusion;975
106.5;References;975
107;A Study and Comprehensive Overview of Inverter Topologies for Grid-Connected Photovoltaic Systems (PVS);977
107.1;1 Introduction;978
107.2;2 Evolution of Grid-Connected Inverter Topologies for PVS;978
107.2.1;2.1 Centralized Inverters;981
107.2.2;2.2 String Inverters and AC-Modules;981
107.2.3;2.3 Multi-string Inverters and Cascaded Inverters;982
107.3;3 Power Processing Stages-Based Inverters;982
107.3.1;3.1 SSI: Single-Stage Inverter;982
107.3.2;3.2 MSI: Multiple-Stage Inverter;983
107.4;4 Conclusion;983
107.5;References;984
108;IOT Based Smart Writer;986
108.1;1 Technical Details of the Paper;987
108.1.1;1.1 Origin of Idea;987
108.1.2;1.2 Definition of the Problem;987
108.2;2 Objectives;987
108.2.1;2.1 Printing;987
108.2.2;2.2 Android/IOS Development;988
108.2.3;2.3 App to Machine Communication;988
108.2.4;2.4 Speech to Text Conversion;988
108.2.5;2.5 Signature Printing and Encryption;988
108.3;3 Workplan;988
108.3.1;3.1 Literature Survey;988
108.3.2;3.2 Writer Installation;988
108.3.3;3.3 Arduino Programming;989
108.3.4;3.4 Mobile App Development;989
108.3.5;3.5 Paper Representation;989
108.4;4 Methodology;989
108.5;5 Organization of the Work Elements;990
108.6;6 Time Schedule Chart;991
108.7;7 Technologies Used;991
108.8;8 Conclusion;991
108.9;References;991
109;Design and Implementation of Arduino Based Control System for Power Management of Household Utilities;992
109.1;1 Introduction;992
109.2;2 Environmental Impact of Conventional Energy Resources;993
109.3;3 Solar Power and Scope in India;993
109.4;4 Experimental Setup;994
109.5;5 Results and Discussion;995
109.6;6 Conclusion;998
109.7;References;998
110;Interfacing Python with DIgSILENT Power Factory: Automation of Tasks;999
110.1;1 Python Interpreter;999
110.2;2 Python Power Factory Module;1000
110.3;3 Python Power Factory Module Usage;1000
110.4;4 Conclusion;1002
110.5;References;1003
111;Recent Development in Perovskite Solar Cell Based on Planar Structures;1004
111.1;1 Introduction;1004
111.2;2 Planar Structure;1006
111.3;3 The Inverted Planar Structure;1007
111.4;4 Summary;1009
111.5;References;1009
