Artificial Intelligence-Based Smart Power Systems
Artificial Intelligence-Based Smart Power Systems
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Author(s): Chenniappan, Sharmeela
Padmanaban
Padmanaban, Sanjeevikumar
Palanisamy, Sivaraman
Sanjeevikumar, P.
Sivaraman, P.
ISBN No.: 9781119893967
Pages: 400
Year: 202212
Format: Trade Cloth (Hard Cover)
Price: $ 210.52
Dispatch delay: Dispatched between 7 to 15 days
Status: Available

Editor Biography xv List of Contributors xvii 1 Introduction to Smart Power Systems 1 Sivaraman Palanisamy, Zahira Rahiman, and Sharmeela Chenniappan 1.1 Problems in Conventional Power Systems 1 1.2 Distributed Generation (DG) 1 1.3 Wide Area Monitoring and Control 2 1.4 Automatic Metering Infrastructure 4 1.5 Phasor Measurement Unit 6 1.6 Power Quality Conditioners 8 1.7 Energy Storage Systems 8 1.


8 Smart Distribution Systems 9 1.9 Electric Vehicle Charging Infrastructure 10 1.10 Cyber Security 11 1.11 Conclusion 11 References 11 2 Modeling and Analysis of Smart Power System 15 Madhu Palati, Sagar Singh Prathap, and Nagesh Halasahalli Nagaraju 2.1 Introduction 15 2.2 Modeling of Equipment''s for Steady-State Analysis 16 2.2.1 Load Flow Analysis 16 2.


2.1.1 Gauss Seidel Method 18 2.2.1.2 Newton Raphson Method 18 2.2.1.


3 Decoupled Load Flow Method 18 2.2.2 Short Circuit Analysis 19 2.2.2.1 Symmetrical Faults 19 2.2.2.


2 Unsymmetrical Faults 20 2.2.3 Harmonic Analysis 20 2.3 Modeling of Equipments for Dynamic and Stability Analysis 22 2.4 Dynamic Analysis 24 2.4.1 Frequency Control 24 2.4.


2 Fault Ride Through 26 2.5 Voltage Stability 26 2.6 Case Studies 27 2.6.1 Case Study 1 27 2.6.2 Case Study 2 28 2.6.


2.1 Existing and Proposed Generation Details in the Vicinity of Wind Farm 29 2.6.2.2 Power Evacuation Study for 50 MW Generation 30 2.6.2.3 Without Interconnection of the Proposed 50 MW Generation from Wind Farm on 66 kV Level of 220/66 kV Substation 31 2.


6.2.4 Observations Made from Table 2.6 31 2.6.2.5 With the Interconnection of Proposed 50 MW Generation from Wind Farm on 66 kV level of 220/66 kV Substation 31 2.6.


2.6 Normal Condition without Considering Contingency 32 2.6.2.7 Contingency Analysis 32 2.6.2.8 With the Interconnection of Proposed 60 MW Generation from Wind Farm on 66 kV Level of 220/66 kV Substation 33 2.


7 Conclusion 34 References 34 3 Multilevel Cascaded Boost Converter Fed Multilevel Inverter for Renewable Energy Applications 37 Marimuthu Marikannu, Vijayalakshmi Subramanian, Paranthagan Balasubramanian, Jayakumar Narayanasamy, Nisha C. Rani, and Devi Vigneshwari Balasubramanian 3.1 Introduction 37 3.2 Multilevel Cascaded Boost Converter 40 3.3 Modes of Operation of MCBC 42 3.3.1 Mode-1 Switch S A Is ON 42 3.3.


2 Mode-2 Switch S A Is ON 42 3.3.3 Mode-3-Operation - Switch S A Is ON 42 3.3.4 Mode-4-Operation - Switch S A Is ON 42 3.3.5 Mode-5-Operation - Switch S A Is ON 42 3.3.


6 Mode-6-Operation - Switch S A Is OFF 42 3.3.7 Mode-7-Operation - Switch S A Is OFF 42 3.3.8 Mode-8-Operation - Switch S A Is OFF 43 3.3.9 Mode-9-Operation - Switch S A Is OFF 44 3.3.


10 Mode 10-Operation - Switch S A is OFF 45 3.4 Simulation and Hardware Results 45 3.5 Prominent Structures of Estimated DC-DC Converter with Prevailing Converter 49 3.5.1 Voltage Gain and Power Handling Capability 49 3.5.2 Voltage Stress 49 3.5.


3 Switch Count and Geometric Structure 49 3.5.4 Current Stress 52 3.5.5 Duty Cycle Versus Voltage Gain 52 3.5.6 Number of Levels in the Planned Converter 52 3.6 Power Electronic Converters for Renewable Energy Sources (Applications of MLCB) 54 3.


6.1 MCBC Connected with PV Panel 54 3.6.2 Output Response of PV Fed MCBC 54 3.6.3 H-Bridge Inverter 54 3.7 Modes of Operation 55 3.7.


1 Mode 1 55 3.7.2 Mode 2 55 3.7.3 Mode 3 56 3.7.4 Mode 4 56 3.7.


5 Mode 5 56 3.7.6 Mode 6 56 3.7.7 Mode 7 58 3.7.8 Mode 8 58 3.7.


9 Mode 9 59 3.7.10 Mode 10 59 3.8 Simulation Results of MCBC Fed Inverter 60 3.9 Power Electronic Converter for E-Vehicles 61 3.10 Power Electronic Converter for HVDC/Facts 62 3.11 Conclusion 63 References 63 4 Recent Advancements in Power Electronics for Modern Power Systems-Comprehensive Review on DC-Link Capacitors Concerning Power Density Maximization in Power Converters 65 Naveenkumar Marati, Shariq Ahammed, Kathirvel Karuppazaghi, Balraj Vaithilingam, Gyan R. Biswal, Phaneendra B.


Bobba, Sanjeevikumar Padmanaban, and Sharmeela Chenniappan 4.1 Introduction 65 4.2 Applications of Power Electronic Converters 66 4.2.1 Power Electronic Converters in Electric Vehicle Ecosystem 66 4.2.2 Power Electronic Converters in Renewable Energy Resources 67 4.3 Classification of DC-Link Topologies 68 4.


4 Briefing on DC-Link Topologies 69 4.4.1 Passive Capacitive DC Link 69 4.4.1.1 Filter Type Passive Capacitive DC Links 70 4.4.1.


2 Filter Type Passive Capacitive DC Links with Control 72 4.4.1.3 Interleaved Type Passive Capacitive DC Links 74 4.4.2 Active Balancing in Capacitive DC Link 75 4.4.2.


1 Separate Auxiliary Active Capacitive DC Links 76 4.4.2.2 Integrated Auxiliary Active Capacitive DC Links 78 4.5 Comparison on DC-Link Topologies 82 4.5.1 Comparison of Passive Capacitive DC Links 82 4.5.


2 Comparison of Active Capacitive DC Links 83 4.5.3 Comparison of DC Link Based on Power Density, Efficiency, and Ripple Attenuation 86 4.6 Future and Research Gaps in DC-Link Topologies with Balancing Techniques 94 4.7 Conclusion 95 References 95 5 Energy Storage Systems for Smart Power Systems 99 Sivaraman Palanisamy, Logeshkumar Shanmugasundaram, and Sharmeela Chenniappan 5.1 Introduction 99 5.2 Energy Storage System for Low Voltage Distribution System 100 5.3 Energy Storage System Connected to Medium and High Voltage 101 5.


4 Energy Storage System for Renewable Power Plants 104 5.4.1 Renewable Power Evacuation Curtailment 106 5.5 Types of Energy Storage Systems 109 5.5.1 Battery Energy Storage System 109 5.5.2 Thermal Energy Storage System 110 5.


5.3 Mechanical Energy Storage System 110 5.5.4 Pumped Hydro 110 5.5.5 Hydrogen Storage 110 5.6 Energy Storage Systems for Other Applications 111 5.6.


1 Shift in Energy Time 111 5.6.2 Voltage Support 111 5.6.3 Frequency Regulation (Primary, Secondary, and Tertiary) 112 5.6.4 Congestion Management 112 5.6.


5 Black Start 112 5.7 Conclusion 112 References 113 6 Real-Time Implementation and Performance Analysis of Supercapacitor for Energy Storage 115 Thamatapu Eswararao, Sundaram Elango, Umashankar Subramanian, Krishnamohan Tatikonda, Garika Gantaiahswamy, and Sharmeela Chenniappan 6.1 Introduction 115 6.2 Structure of Supercapacitor 117 6.2.1 Mathematical Modeling of Supercapacitor 117 6.3 Bidirectional Buck-Boost Converter 118 6.3.


1 FPGA Controller 119 6.4 Experimental Results 120 6.5 Conclusion 123 References 125 7 Adaptive Fuzzy Logic Controller for MPPT Control in PMSG Wind Turbine Generator 129 Rania Moutchou, Ahmed Abbou, Bouazza Jabri, Salah E. Rhaili, and Khalid Chigane 7.1 Introduction 129 7.2 Proposed MPPT Control Algorithm 130 7.3 Wind Energy Conversion System 131 7.3.


1 Wind Turbine Characteristics 131 7.3.2 Model of PMSG 132 7.4 Fuzzy Logic Command for the MPPT of the PMSG 133 7.4.1 Fuzzification 134 7.4.2 Fuzzy Logic Rules 134 7.


4.3 Defuzzification 134 7.5 Results and Discussions 135 7.6 Conclusion 139 References 139 8 A Novel Nearest Neighbor Searching-Based Fault Distance Location Method for HVDC Transmission Lines 141 Aleena Swetapadma, Shobha Agarwal, Satarupa Chakrabarti, and Soham Chakrabarti 8.1 Introduction 141 8.2 Nearest Neighbor Searching 142 8.3 Proposed Method 144 8.3.


1 Power System Network Under Study 144 8.3.2 Proposed Fault Location Method 145 8.4 Results 146 8.4.1 Performance Varying Nearest Neighbor 147 8.4.2 Performance Varying Distance Matrices 147 8.


4.3 Near Boundary Faults 148 8.4.4 Far Boundary Faults 149 8.4.5 Performance During High Resistance Faults 149 8.4.6 Single Pole to Ground Faults 150 8.


4.7 Performance During Double Pole to Ground Faults 151 8.4.8 Performance During Pole to Pole Faults 151 8.4.9 Error Analysis 152 8.4.10 Comparison with Other Schemes 153 8.


4.11 Advantages of the Scheme 154 8.5 Conclusion 154 Acknowledgment 154 References 154 9 Comparative Analysis of Machine Learning Approaches in Enhancing Power System Stability 157 Md. I. H. Pathan, Mohammad S. Shahriar, Mohammad M. Rahman, Md.


Sanwar Hossain, Nadia Awatif, and Md. Shafiullah 9.1 Introduction 157 9.2 Power System Models 159 9.2.1 PSS Integrated Single Machine Infinite Bus Power Network 159 9.2.2 PSS-UPFC Integrated Single Machine Infinite Bus Power Network 160 9.


3 Methods 161 9.3.1 Group Method Data Handling Model 161 9.3.2 Extreme Learning Machine Model 162 9.3.3 Neurogenetic Model 162 9.3.


4 Multigene Genetic Programming Model 163 9.4 Data Preparation and Model Development 165 9.4.1 Data Production and Processing 165 9.4.2 Machine Learning Model Development 165 9.5 Results and Discussions 166 9.5.


1 Eigenvalues and Minimum Damping Ratio Comparison 166 9.5.2 Time-Domain Simulation Results Comparison 170 9.5.2.1 Rotor Angle Var.


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