Buch, Englisch, 352 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 640 g
Buch, Englisch, 352 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 640 g
ISBN: 978-1-394-26736-1
Verlag: John Wiley & Sons
Comprehensive reference on multi energy hub (MEH) modeling, management, protection, and trading across energy exchange markets with supporting case studies
Energy Management Strategies for Multi-Vectored Energy Hubs to Achieve Low Carbon Societies discusses the complex exchange process across different sources within an evolving set of technologies, presenting multi-vectored energy hub (MV-EH) modeling techniques and associated energy management strategies for their network architecture. This includes in-depth assessments of advanced energy conversion technologies, market mechanisms, and transactive energy management to ensure robust and flexible energy-sharing mechanisms. The book focuses on renewable energy integration in MV-EHs, advanced energy storage, and advance energy conversion technologies.
Later chapters cover detailed analyses of Power-to-X (P2X) technologies, bioenergy integration, and emerging challenges in high-renewable penetration in energy hubs. Case studies of MV-EHs explore the latest advancements such as the carbon tax mechanism, carbon trading strategies, the role of hydrogen generation, and carbon storage to enhance MV-EH performance. Readers will find insights into the integration of carbon reduction techniques (CDR) and emission trading mechanisms, along with the role of bioenergy in building the low emission energy systems. Mathematical models of various new energy conversion systems such as power to gas (P2X), hydrogen storage, and hydrogen usage are also explored.
Edited by a team of highly qualified authors, this book covers additional topics such as: - Types of frameworks to manage network energy hubs, cooperative and non-cooperative strategies, and centralized, decentralized, and distributed system architectures
- Advanced energy conversion units such as electric heat pumps, combined heat and power units, gas boilers, absorption chillers, electric chillers, and energy storage units
- The role of bioenergy, power-to-X, hydrogen, carbon reduction techniques (CDR), carbon taxes, carbon market, and trading strategies in achieving low energy systems
- Technologies to enhance flexibility in MEHs such as electrical, heating, cooling, and community demand response programs
- The impact of high or full share of renewables and load-side uncertainties on MV-EH operations
Delivering a thorough understanding of networked multi-vectored energy systems, and their role in sustainable energy transitions, Energy Management Strategies for Multi-Vectored Energy Hubs to Achieve Low Carbon Societies is an essential reference for engineers, researchers, and graduate students developing energy systems, smart grids, and decarbonization strategies.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
About the Editors xix
List of Contributors xxiii
Preface xxv
1 Evaluation of Power/Energy System to the Modern Multi-Vectored Energy Hubs (MV-EHs) 1
Ankit Garg, Khaleequr Rehman Niazi, Subhendu Sekhar Sahoo, and Shubham Tiwari
1.1 Introduction 1
1.2 Problem Statement 3
1.3 Objective 5
1.4 Theoretical Framework 5
1.5 Evaluation Framework 8
1.5.1 Evaluation Criteria of MV-EHs 8
1.5.2 Data Collection 10
1.6 Discussion 11
1.6.1 Regulatory and Policy Framework 12
1.6.2 Challenges and Future Trends 13
1.7 Conclusion 15
References 16
2 Introduction of Transactive Energy Management in a Multi-Energy Networked System 19
Ankit Garg, Khaleequr Rehman Niazi, Subhendu Sekhar Sahoo, and Shubham Tiwari
2.1 Introduction 19
2.2 Problem Statement 21
2.3 Objective 22
2.4 Conceptual Framework 23
2.5 Multi-Energy Networked System 25
2.6 Integration of Transactive Energy Management 26
2.6.1 Objective Function 27
2.6.2 Constraints 27
2.6.2.1 Power Balance Constraint 27
2.6.2.2 Power Generation Constraint 27
2.6.3 PV Constraints 27
2.6.4 Battery Storage Constraints 28
2.6.5 Market Constraints 28
2.6.6 Working Cases of Microgrids 28
2.6.6.1 First Case 28
2.6.6.2 Second Case 29
2.6.7 Benefits of Integration 29
2.6.8 Challenges of Integration 30
2.7 Discussion 30
2.7.1 Advantages 32
2.7.1.1 Enhanced Efficiency 32
2.7.1.2 Expanded Adaptability 32
2.7.1.3 Further Developed Strength 32
2.7.2 Disadvantages 33
2.7.2.1 Complex Framework Joining 33
2.7.2.2 Information About Executives and Security 33
2.7.2.3 Administrative and Market Boundaries 33
2.7.3 Challenges 33
2.7.3.1 Technical Challenges 33
2.7.3.2 Regulatory Challenges 34
2.7.4 Future Directions 35
2.7.5 Possible Improvements and Innovations in Transactive Energy Management 35
2.8 Conclusion 36
References 38
3 Energy Management Strategies for Optimal Scheduling of Multi-Energy Network Hubs 41
Divya Sharma and Naran M. Pindoriya
Nomenclature 41
3.1 Introduction 43
3.1.1 Background 43
3.1.2 Related Work 44
3.2 System Architecture and Problem Formulation 46
3.2.1 System Architecture 46
3.3 Problem Formulation 51
3.3.1 DSO Objective Function 51
3.3.2 EH Coordinator Objective Function 51
3.3.3 Electrical Network 51
3.3.4 Thermal Network 52
3.3.5 Supply–demand Balance in EHs 53
3.3.6 Multi-Objective Optimization Formulation for DSO and EH Coordinator 53
3.3.7 Bargaining Game Between EHs 54
3.3.8 Economic Scheduling Model of Cooperative EHs 55
3.4 Results and Discussion 56
3.4.1 Case 1: Non-cooperative Operation of EHs 59
3.4.2 Case 2: Cooperative Operation of EHs 66
3.5 Conclusion 72
References 75
4 Impact of Hydrogen and Power-to-Gas Technology on MV-EHs 79
Subhendu Sekhar Sahoo, Ankit Garg, Khaleequr Rehman Niazi, and Shubham Tiwari
4.1 Introduction 79
4.2 Objectives 81
4.3 Hydrogen Storage Technology 83
4.4 Power-to-Gas (P2G) Technologies 86
4.4.1 System Components 87
4.4.2 Integration with Power Systems 88
4.5 Role of Hydrogen in Sustainable MV-EHs 89
4.5.1 Environmental Impact 89
4.5.2 Economic Considerations 90
4.5.3 Case Study and Examples 91
4.6 Conclusion 92
References 93
5 Modeling and Analysis of MV-EHs with Advanced Energy Storage Units 97
Rengamani Shenbagalakshmi, Jaganathan Subramaniyan, Govindasamy Ramprakash, and Veerappan Vengatesan
5.1 Introduction 97
5.2 Evolution of Energy Hubs, Their Components, Benefits, and Classification 98
5.2.1 Energy Hubs: Basic Definition and Structure 98
5.2.2 The Background of the EH Methodology 100
5.2.3 Elements of Energy Hubs 101
5.2.3.1 Adapting Converters 101
5.2.3.2 Converters for Switching 102
5.2.4 Benefits of Energy Hubs 102
5.2.4.1 Management of Incorporated Energy 103
5.2.4.2 Enhanced Effectiveness 103
5.2.4.3 Improved Adaptability 103
5.2.4.4 Savings on Costs 103
5.2.4.5 Diminished Emissions of Carbon 104
5.2.4.6 Adaptability and Dependability 104
5.2.4.7 Local Production and Storage of Energy 104
5.2.4.8 Assistance with Electric Cars (EVs) 104
5.2.4.9 Reliability in Scale 105
5.2.4.10 Information and Tracking 105
5.2.4.11 Engagement in the Energy Market 105
5.2.4.12 Support for Regulation and Policy 105
5.3 Multi-Vector Energy Hubs 106
5.3.1 Different Types of Interactions and Interdependencies Among Energy Vectors 107
5.3.2 Interdependencies Between Natural Gas and Electricity Networks 107
5.3.3 Interdependencies Between District Heat and Electricity Networks 108
5.3.4 Interdependencies Between Natural Gas, District Heating, and Electricity Networks 108
5.3.5 Advantages of MV-EHs 109
5.3.6 Challenges in MV-EHs 109
5.3.6.1 Technical Difficulties 109
5.3.6.2 The Financial Challenges 109
5.3.6.3 Social and Environmental Challenges 111
5.4 Role of Advanced Energy Storage Technologies in MV-EHs 112
5.4.1 Flywheel Energy Storage 112
5.4.1.1 Significant Progress to Improve the Energy Storage Performance of Flywheels 114
5.4.1.2 Challenges in Integrating Flywheels into MV-EHs 115
5.4.2 CAES Technology 115
5.4.2.1 Challenges Faced by Compressed Air Storage Systems in MV-EHs 118
5.4.3 Pumped Hydro Storage (PHS) 119
5.4.4 Batteries and Electrochemical Systems for Energy Storage 121
5.4.4.1 Merits and Demerits of Battery ESSs 123
5.4.4.2 Challenges in Integrating Battery Energy Storage in MV-EHs 123
5.4.5 Thermal Energy Storage Technology 124
5.4.6 Magnetic Energy Storage Technology 124
5.4.7 Chemical and Hydrogen Energy Storage 125
5.5 Mathematical Model of MV-EHs 128
5.5.1 Modeling Approaches 128
5.5.1.1 Mathematical Modeling 129
5.5.1.2 Tools for Simulation 129
5.5.1.3 Hybrid Models 129
5.5.2 Analytical Techniques 129
5.5.2.1 Optimization Algorithms 129
5.5.2.2 Performance Analysis 130
5.5.2.3 Economic and Environmental Analysis 130
5.5.3 Challenges and Opportunities 130
5.5.3.1 Challenges 130
5.5.3.2 Opportunities 130
5.5.4 Policy and Incentive Design 132
5.5.4.1 Future Research Directions 132
5.6 Conclusion 132
References 133
6 Market and Energy Trading Mechanism in MV-EHs 141
Rajasekharan Rajasree, Dhandapani Lakshmi, Ravichandran Karthick Manoj, Kesavan Stalin, Sivaraman Palanisamy, and Sharmeela Chenniappan
6.1 Introduction to Different Market Clearing Mechanisms in MEH 141
6.2 Concepts of Market Equilibrium Models 142
6.3 Mechanisms of Energy Trading in MEH 142
6.3.1 Market Structure and Participants 142
6.3.2 Spot and Futures Markets 143
6.3.3 Pricing Mechanisms and Instruments 143
6.3.4 Environmental and Regulatory Considerations 143
6.3.5 Technological Innovations and Market Integration 143
6.4 Types of Market Equilibrium in MEHs 144
6.4.1 Stable Equilibrium 144
6.4.2 Unstable Equilibrium 144
6.4.3 Dynamic Equilibrium 144
6.4.4 Partial Equilibrium 145
6.4.5 General Equilibrium 145
6.4.6 Long-Run Equilibrium 145
6.4.7 Short-Run Equilibrium 145
6.5 Graphical Representation of Market Equilibrium 145
6.5.1 Demand and Supply Curves 146
6.5.2 Equilibrium Point 147
6.5.3 Shifts in Curves 147
6.5.4 Surpluses and Shortages 148
6.6 Factors Affecting Market Equilibrium Models 148
6.7 Energy Market Designs 149
6.7.1 Types of Energy Markets 149
6.7.2 Market Clearing Mechanisms 150
6.7.3 Regulatory Framework 150
6.7.4 Incentives for Renewable Energy 150
6.7.5 Demand Response Programs 150
6.7.6 Integration of Distributed Energy Resources 150
6.7.7 Market Interconnections 150
6.7.8 Pricing Mechanisms 151
6.7.9 Environmental Considerations 151
6.7.10 Challenges and Barriers 151
6.7.11 Future Trends in Energy Market Design 151
6.8 Blockchain Technologies 151
6.8.1 Key Components of Blockchain Technology 152
6.8.1.1 Blocks 152
6.8.1.2 Chain 152
6.8.1.3 Nodes 152
6.8.1.4 Consensus Mechanisms 152
6.8.1.5 Cryptographic Hash Functions 152
6.8.1.6 Smart Contracts 152
6.8.1.7 Tokens and Cryptocurrencies 153
6.8.1.8 Wallets 153
6.8.2 Types of Blockchain Technology 153
6.8.2.1 Public Blockchain 153
6.8.2.2 Private Blockchain 153
6.8.2.3 Consortium Blockchain 153
6.8.2.4 Hybrid Blockchain 153
6.8.2.5 Sidechains 154
6.8.2.6 Layer 2 Solutions 154
6.8.3 Features of Blockchain Technology 154
6.8.4 Benefits of Blockchain Technology 154
6.8.5 Challenges and Limitations of Blockchain Technology 155
6.8.6 Applications of Blockchain Technology 156
6.9 Role of Market Makers in MEHs 157
6.9.1 Providing Liquidity 157
6.9.2 Reducing Bid-Ask Spreads 157
6.9.3 Price Discovery 157
6.9.4 Stabilizing Markets 158
6.9.5 Reducing Information Asymmetry 158
6.9.6 Risk Management 158
6.9.7 Facilitating Arbitrage 158
6.10 Smart Contracts Between EHs 158
6.10.1 Role of Smart Contracts Between Energy Hubs 158
6.10.1.1 Energy Trading 159
6.10.1.2 Dynamic Pricing 159
6.10.1.3 Automated Energy Distribution 159
6.10.1.4 Microgrid Management 159
6.10.1.5 Energy Storage Management 159
6.10.1.6 Grid Balancing and Stability 160
6.10.1.7 Carbon Credits and Sustainability Incentives 160
6.10.1.8 Grid Services (Demand Response) 160
6.10.1.9 Dispute Resolution 160
6.10.2 Benefits of Smart Contracts in Energy Hubs 161
6.11 Algorithms for Energy Trading Among EHs 161
6.11.1 Market-Based Algorithms 161
6.11.1.1 Auction Mechanisms 161
6.11.2 Game Theory Approaches 161
6.11.2.1 Nash Equilibrium 161
6.11.2.2 Cooperative Game Theory 161
6.11.3 Optimization Algorithms 162
6.11.3.1 Linear Programming (LP) 162
6.11.3.2 Mixed-Integer Programming (MIP) 162
6.11.3.3 Dynamic Programming 162
6.11.4 Machine Learning Techniques 162
6.11.4.1 Reinforcement Learning (RL) 162
6.11.4.2 Neural Networks 162
6.11.5 Multiagent Systems 162
6.11.5.1 Distributed Algorithms 162
6.11.5.2 Consensus Algorithms 162
6.11.6 Forecasting Models 163
6.11.6.1 Time Series Analysis 163
6.11.6.2 Weather Forecasting Models 163
6.11.7 Blockchain and Smart Contracts 163
6.11.7.1 Decentralized Trading Platforms 163
6.11.8 Heuristic Methods 163
6.11.8.1 Genetic Algorithms 163
6.11.8.2 Particle Swarm Optimization 163
6.12 Regulatory Framework for MEHs 163
6.12.1 Market Structure and Design 163
6.12.2 Price Formation Mechanisms 164
6.12.3 Transparency and Reporting 164
6.12.4 Market Power and Competition 164
6.12.5 Consumer Protection 164
6.12.6 Environmental and Sustainability Standards 164
6.12.7 Grid Reliability and Security 165
6.12.8 Technological Integration 165
6.13 Benefits of Market Trading in MEHs 165
6.14 Challenges and Limitations of MEHs 166
6.15 Case Studies of Energy Trading in MEHs 166
6.15.1 Indian Energy Market 166
6.15.2 Nord Pool Power Market 166
6.15.3 Electric Reliability Council of Texas (ERCOT) in Texas 167
6.15.4 Australian National Electricity Market (NEM) 167
6.15.5 California Electricity Market 167
6.16 Future Trends in Energy Trading in MEHs 167
6.16.1 Increased Integration of Renewables 167
6.16.2 Decentralized Energy Systems 168
6.16.3 Advanced Storage Solutions 168
6.16.4 Enhanced Regulatory Frameworks 168
6.16.5 Digitalization and Smart Grids 168
6.16.6 Global Market Interconnections 168
6.16.7 Demand Response Programs 168
6.16.8 Focus on Sustainability 169
6.17 Conclusion 169
References 169
7 ImpactofHighorFullShareofRESsandLoad-Side Uncertainty on Multi-Vectored Energy Hubs 173
Stephen Oko Gyan Torto, Rupendra Kumar Pachauri, and Jai Govind Singh
Nomenclature 173
7.1 Introduction 174
7.1.1 Overview of Multi-Vectored Energy Hubs (MV-EHs) 177
7.1.1.1 Core Components of MV-EHS 177
7.1.2 Challenges and Opportunities 177
7.2 RESs and Their Growing Share 179
7.2.1 Trends in RESs Deployment 181
7.2.2 Opportunities and Challenges of High RESs Share 182
7.3 Handling RES Uncertainty 183
7.3.1 Challenges Posed by RES Variability 184
7.3.2 Strategies for Managing RES Uncertainty 185
7.4 Forecasting Techniques 185
7.4.1 Role of Predictive Models in Uncertainty Management 185
7.4.1.1 Key Benefits 186
7.4.2 Energy Storage Systems as a Buffer for RES Variability 186
7.4.3 Innovative Technologies in RES Uncertainty Handling 187
7.5 Impact of High or Full RES Share on MV-EHs 188
7.5.1 Effects on Energy Production and Distribution 188
7.5.2 Case Studies of MV-EHs With High-RES Share 190
7.6 Load-Side Uncertainty and Its Impact on MV-EHs 191
7.6.1 Understanding Load-Side Uncertainty 191
7.6.2 Key Factors Affecting Load-Side Uncertainty 192
7.6.3 Demand Side Management Strategies 193
7.6.4 Real-Time Pricing and Its Effects on Consumption Patterns 193
7.6.5 Technologies for Demand Forecasting and Management 194
7.7 Integrated Energy Management Strategies 195
7.7.1 Combining Forecasting, RES Handling, and DSM 195
7.7.2 Role of Smart Grids and IoT in Integrated Management 196
7.8 Multi-Vectored Energy Hub 196
7.8.1 Concept of Energy Hub 196
7.8.2 Data 199
7.8.3 Case Study I 200
7.8.4 Case Study II 203
7.9 Conclusion and Recommendation 205
References 209
8 Green Energy, Greener Future: Bioenergy’s Role in Carbon Reduction 213
Nilay Kumar Sarker and Prasad Kaparaju
8.1 Introduction 213
8.2 The Significance of Bioenergy 214
8.2.1 Limitations of Wind and Solar Energy 214
8.2.2 Benefits of Bioenergy 215
8.2.3 Strategies for Low-Carbon Transition Via Bioenergy 216
8.3 Integrating Bioenergy into National and Regional Emission Reduction Plans: A Case Study Approach 217
8.3.1 Bioenergy in Europe: A Regional Overview 217
8.3.2 Bioenergy Initiatives in the Nordic Countries 218
8.3.3 Bioenergy Contributions to Emission Reductions in Nigeria 218
8.3.4 Uganda’s Approach to Bioenergy 219
8.3.5 The Role and Potential of Bioenergy in the United States 220
8.3.6 Bioenergy’s Role and Potential in India 220
8.3.7 The Role and Potential of Bioenergy in the United States 221
8.3.8 Bioenergy’s Role and Potential in Brazil 222
8.4 Developing Policy Frameworks to Support Bioenergy 223
8.4.1 Policy Strategies in the Nordic Countries 223
8.4.2 United Kingdom: Policies Driving Bioenergy 224
8.4.3 Bioenergy Policy Landscape in Brazil 225
8.4.4 India’s Framework for Bioenergy Development 225
8.4.5 Bioenergy Policy Framework in the United States 226
8.4.6 Bioenergy Policies in China 226
8.4.7 Comparative Analysis of Global Bioenergy Policies 227
8.5 Overcoming Barriers to a Low-Carbon Society Through Bioenergy 227
8.6 Explorative Case Studies on Bioenergy Implementation 228
8.6.1 Innovations in Lignocellulosic Biomass Utilization 228
8.6.2 Bioenergy Development in Taiwan 229
8.6.3 Bioenergy in Eastern Africa: Challenges and Opportunities 229
8.6.4 Bioenergy in Australia: Current Status and Future Potential 230
8.7 Bioenergy Coupled with Carbon Capture and Storage (BECCS) 231
8.7.1 Advancing Negative Emissions in Pursuit of a Low-Carbon Society 231
8.7.2 Exploring Local-Scale Opportunities for Carbon Reduction 232
8.7.3 BECCS Implementation Examples from Tanzania 233
8.8 Conclusion 233
References 234
9 Perspectives of Integrating Bioenergy into the Energy Mix in Developing Nations: A SWOT Analysis 237
Toyese Oyegoke
9.1 Introduction 237
9.2 Literature Review 239
9.2.1 Overview of Bioenergy 239
9.2.1.1 Thermochemical Process Technology 239
9.2.1.2 Biochemical Process Technology 240
9.2.2 State of Art in Bioenergy Integration in Developing Nations 242
9.2.3 Previous Studies on SWOT Analysis of Bioenergy Integration 243
9.3 Study Strategy 245
9.3.1 Data Sources 245
9.3.2 Method of Analysis 245
9.4 SWOT Analysis 246
9.4.1 The Strengths of Bioenergy Integration in Developing Nations 246
9.4.1.1 Abundance of Biomass Resources 246
9.4.1.2 Environmental Benefits and Improved Waste Management 248
9.4.1.3 Energy Security 249
9.4.1.4 Local Energy Production, Rural Development, and Social Acceptance 249
9.4.2 The Weaknesses or Limitations of Bioenergy Integration Initiatives 250
9.4.2.1 Lack of Infrastructure and High Initial Investment Costs 250
9.4.2.2 Technological Challenges 251
9.4.2.3 Limited Public Awareness and Acceptance 251
9.4.2.4 Competition for Land Usage, Policy, and Regulatory Challenges 252
9.4.2.5 Resource Availability and Market Access 252
9.4.3 The Opportunities for Bioenergy Integration 252
9.4.3.1 Government Incentives and Policies 253
9.4.3.2 Growing Demand for Eco-friendly Sustainable Energy Sources and Their Export Potential 253
9.4.3.3 Potential for Collaboration with International Organizations and Donor Agencies 254
9.4.3.4 Improved Waste Management Technologies and Environmental Benefits 254
9.4.3.5 Economic Diversification, Job Creation, and Community Development 254
9.4.3.6 Energy Access, Technology Innovation, and Local Content Development 255
9.4.4 The Potential Threats to Bioenergy Integration 255
9.4.4.1 Competition from Low-Cost Fossil Fuels 255
9.4.4.2 Policy and Regulatory Uncertainty and Social Resistance 256
9.4.4.3 Vulnerability to Climate Change and Extreme Weather Events 256
9.4.5 Key Deductions from the SWOT Analysis Results 256
9.4.6 Exploration of Effective Implementation Strategy for Bioenergy Integration in Developing Nations 257
9.4.7 SO Strategy 258
9.4.8 ST Strategy 258
9.4.9 WO Strategy 259
9.4.10 WT Strategy 259
9.4.11 Implementation Strategies Summary 260
9.5 Integration of Bioenergy into Energy Hubs 260
9.5.1 Role of Bioenergy in Energy Hubs 260
9.5.2 Benefits of Integrating Bioenergy in Developing Nations’ Energy Hubs 261
9.5.3 Challenges and Considerations 262
9.6 Recommendations, Summary, and Suggestions for Future Studies 262
9.6.1 Recommendations 262
9.6.1.1 Policy and Regulatory Frameworks 262
9.6.1.2 Capacity Building and Technology Transfer 263
9.6.1.3 Financial Support and Investment 263
9.6.1.4 Public Awareness and Stakeholder Engagement 263
9.6.1.5 Research and Development 263
9.6.2 Summary of Key Findings 263
9.6.3 Suggestions for Future Research 264
References 264
10 Integration of Carbon Reduction Techniques (CDR) and Emission Trading Mechanisms Among MV-EHs 277
Mohammad Parhamfar and Saeed Khorrami
10.1 Introduction 277
10.2 Energy System Models 279
10.2.1 Energy System Optimization Models 279
10.3 Energy System Simulation Models 280
10.4 Power Systems and Electricity Market Models 280
10.5 Qualitative and Mixed-Methods Scenarios 281
10.6 A Review of Commitments and Protocols 281
10.7 Glasgow COP26 Carbon Trading Agreement 282
10.7.1 Carbon ETS Design 283
10.7.2 European Union ETS 284
10.8 The California Global Warming Solution Act (the United States) 286
10.9 The Chinese Market 287
10.10 Certified Emissions Reductions 288
10.10.1 Clean Development Mechanism 288
10.11 Analysis of Risks/Challenges of the Main ETS 290
10.11.1 Carbon Pricing Scheme, Carbon Tax, and Emission Trading 290
10.11.2 Cap-and-Trade Program 292
10.11.3 Offset or Credit Programs 293
10.11.4 Rate-Based Program 293
10.11.5 Performance of Cap-and-Trade Program 294
10.12 Carbon Tax 294
10.13 Crediting 295
10.13.1 GWP: Global Warming Potential 295
10.13.2 Advantages and Disadvantages of a Carbon Tax 296
10.13.3 Advantages and Disadvantages of Emission Trading 296
10.14 How Is the Offset Market in Developed Countries? 296
10.15 Peer-to-Peer Energy Trading System 297
10.16 Blockchain Role in Carbon Trading 297
10.17 Application of AI in Blockchain-Based Emission Trading 301
10.17.1 Game Theory 302
10.17.2 AI for Monitoring Carbon Footprint 303
10.18 Optimization Approaches 306
References 306
Index 311
