Energy Management Strategies for Multi-Vectored Energy Hubs to Achieve Low Carbon Societies

Shubham Tiwari is a Research Scholar at the International Institute of Applied Systems Analysis (IIASA), Austria. Jai Govind Singh, PhD, is an Associate Professor in Sustainable Energy Transition at the Asian Institute of Technology, Pathum Thani, Thailand. Sivaraman Palanisamy is an industry professional and also a Research Scholar with the Department of Electrical and Electronics Engineering at CEG Campus, Anna University, Chennai. Sharmeela Chenniappan, PhD, holds the post of Professor in the Department of Electrical and Electronics Engineering. She is also Adjunct Professor at the Centre of E-Vehicle Technologies, and the Centre for Energy Storage Technologies, CEG Campus, at Anna University, Chennai, India. Rupendra Kumar Pachauri, PhD, is an Associate Professor in the Electrical Cluster, School of Advanced Engineering, UPES, Dehradun, India. Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Electrical Engineering, IT and Cybernetics at the University of South-Eastern Norway, Porsgrunn, Norway.

• About the Editors xixList of Contributors xxiiiPreface xxv1 Evaluation of Power/Energy System to the Modern Multi-Vectored Energy Hubs (MV-EHs) 1Ankit Garg, Khaleequr Rehman Niazi, Subhendu Sekhar Sahoo, and Shubham Tiwari1.1 Introduction 11.2 Problem Statement 31.3 Objective 51.4 Theoretical Framework 51.5 Evaluation Framework 81.5.1 Evaluation Criteria of MV-EHs 81.5.2 Data Collection 101.6 Discussion 111.6.1 Regulatory and Policy Framework 121.6.2 Challenges and Future Trends 131.7 Conclusion 15References 162 Introduction of Transactive Energy Management in a Multi-Energy Networked System 19Ankit Garg, Khaleequr Rehman Niazi, Subhendu Sekhar Sahoo, and Shubham Tiwari2.1 Introduction 192.2 Problem Statement 212.3 Objective 222.4 Conceptual Framework 232.5 Multi-Energy Networked System 252.6 Integration of Transactive Energy Management 262.6.1 Objective Function 272.6.2 Constraints 272.6.2.1 Power Balance Constraint 272.6.2.2 Power Generation Constraint 272.6.3 PV Constraints 272.6.4 Battery Storage Constraints 282.6.5 Market Constraints 282.6.6 Working Cases of Microgrids 282.6.6.1 First Case 282.6.6.2 Second Case 292.6.7 Benefits of Integration 292.6.8 Challenges of Integration 302.7 Discussion 302.7.1 Advantages 322.7.1.1 Enhanced Efficiency 322.7.1.2 Expanded Adaptability 322.7.1.3 Further Developed Strength 322.7.2 Disadvantages 332.7.2.1 Complex Framework Joining 332.7.2.2 Information About Executives and Security 332.7.2.3 Administrative and Market Boundaries 332.7.3 Challenges 332.7.3.1 Technical Challenges 332.7.3.2 Regulatory Challenges 342.7.4 Future Directions 352.7.5 Possible Improvements and Innovations in Transactive Energy Management 352.8 Conclusion 36References 383 Energy Management Strategies for Optimal Scheduling of Multi-Energy Network Hubs 41Divya Sharma and Naran M. PindoriyaNomenclature 413.1 Introduction 433.1.1 Background 433.1.2 Related Work 443.2 System Architecture and Problem Formulation 463.2.1 System Architecture 463.3 Problem Formulation 513.3.1 DSO Objective Function 513.3.2 EH Coordinator Objective Function 513.3.3 Electrical Network 513.3.4 Thermal Network 523.3.5 Supply–demand Balance in EHs 533.3.6 Multi-Objective Optimization Formulation for DSO and EH Coordinator 533.3.7 Bargaining Game Between EHs 543.3.8 Economic Scheduling Model of Cooperative EHs 553.4 Results and Discussion 563.4.1 Case 1: Non-cooperative Operation of EHs 593.4.2 Case 2: Cooperative Operation of EHs 663.5 Conclusion 72References 754 Impact of Hydrogen and Power-to-Gas Technology on MV-EHs 79Subhendu Sekhar Sahoo, Ankit Garg, Khaleequr Rehman Niazi, and Shubham Tiwari4.1 Introduction 794.2 Objectives 814.3 Hydrogen Storage Technology 834.4 Power-to-Gas (P2G) Technologies 864.4.1 System Components 874.4.2 Integration with Power Systems 884.5 Role of Hydrogen in Sustainable MV-EHs 894.5.1 Environmental Impact 894.5.2 Economic Considerations 904.5.3 Case Study and Examples 914.6 Conclusion 92References 935 Modeling and Analysis of MV-EHs with Advanced Energy Storage Units 97Rengamani Shenbagalakshmi, Jaganathan Subramaniyan, Govindasamy Ramprakash, and Veerappan Vengatesan5.1 Introduction 975.2 Evolution of Energy Hubs, Their Components, Benefits, and Classification 985.2.1 Energy Hubs: Basic Definition and Structure 985.2.2 The Background of the EH Methodology 1005.2.3 Elements of Energy Hubs 1015.2.3.1 Adapting Converters 1015.2.3.2 Converters for Switching 1025.2.4 Benefits of Energy Hubs 1025.2.4.1 Management of Incorporated Energy 1035.2.4.2 Enhanced Effectiveness 1035.2.4.3 Improved Adaptability 1035.2.4.4 Savings on Costs 1035.2.4.5 Diminished Emissions of Carbon 1045.2.4.6 Adaptability and Dependability 1045.2.4.7 Local Production and Storage of Energy 1045.2.4.8 Assistance with Electric Cars (EVs) 1045.2.4.9 Reliability in Scale 1055.2.4.10 Information and Tracking 1055.2.4.11 Engagement in the Energy Market 1055.2.4.12 Support for Regulation and Policy 1055.3 Multi-Vector Energy Hubs 1065.3.1 Different Types of Interactions and Interdependencies Among Energy Vectors 1075.3.2 Interdependencies Between Natural Gas and Electricity Networks 1075.3.3 Interdependencies Between District Heat and Electricity Networks 1085.3.4 Interdependencies Between Natural Gas, District Heating, and Electricity Networks 1085.3.5 Advantages of MV-EHs 1095.3.6 Challenges in MV-EHs 1095.3.6.1 Technical Difficulties 1095.3.6.2 The Financial Challenges 1095.3.6.3 Social and Environmental Challenges 1115.4 Role of Advanced Energy Storage Technologies in MV-EHs 1125.4.1 Flywheel Energy Storage 1125.4.1.1 Significant Progress to Improve the Energy Storage Performance of Flywheels 1145.4.1.2 Challenges in Integrating Flywheels into MV-EHs 1155.4.2 CAES Technology 1155.4.2.1 Challenges Faced by Compressed Air Storage Systems in MV-EHs 1185.4.3 Pumped Hydro Storage (PHS) 1195.4.4 Batteries and Electrochemical Systems for Energy Storage 1215.4.4.1 Merits and Demerits of Battery ESSs 1235.4.4.2 Challenges in Integrating Battery Energy Storage in MV-EHs 1235.4.5 Thermal Energy Storage Technology 1245.4.6 Magnetic Energy Storage Technology 1245.4.7 Chemical and Hydrogen Energy Storage 1255.5 Mathematical Model of MV-EHs 1285.5.1 Modeling Approaches 1285.5.1.1 Mathematical Modeling 1295.5.1.2 Tools for Simulation 1295.5.1.3 Hybrid Models 1295.5.2 Analytical Techniques 1295.5.2.1 Optimization Algorithms 1295.5.2.2 Performance Analysis 1305.5.2.3 Economic and Environmental Analysis 1305.5.3 Challenges and Opportunities 1305.5.3.1 Challenges 1305.5.3.2 Opportunities 1305.5.4 Policy and Incentive Design 1325.5.4.1 Future Research Directions 1325.6 Conclusion 132References 1336 Market and Energy Trading Mechanism in MV-EHs 141Rajasekharan Rajasree, Dhandapani Lakshmi, Ravichandran Karthick Manoj, Kesavan Stalin, Sivaraman Palanisamy, and Sharmeela Chenniappan6.1 Introduction to Different Market Clearing Mechanisms in MEH 1416.2 Concepts of Market Equilibrium Models 1426.3 Mechanisms of Energy Trading in MEH 1426.3.1 Market Structure and Participants 1426.3.2 Spot and Futures Markets 1436.3.3 Pricing Mechanisms and Instruments 1436.3.4 Environmental and Regulatory Considerations 1436.3.5 Technological Innovations and Market Integration 1436.4 Types of Market Equilibrium in MEHs 1446.4.1 Stable Equilibrium 1446.4.2 Unstable Equilibrium 1446.4.3 Dynamic Equilibrium 1446.4.4 Partial Equilibrium 1456.4.5 General Equilibrium 1456.4.6 Long-Run Equilibrium 1456.4.7 Short-Run Equilibrium 1456.5 Graphical Representation of Market Equilibrium 1456.5.1 Demand and Supply Curves 1466.5.2 Equilibrium Point 1476.5.3 Shifts in Curves 1476.5.4 Surpluses and Shortages 1486.6 Factors Affecting Market Equilibrium Models 1486.7 Energy Market Designs 1496.7.1 Types of Energy Markets 1496.7.2 Market Clearing Mechanisms 1506.7.3 Regulatory Framework 1506.7.4 Incentives for Renewable Energy 1506.7.5 Demand Response Programs 1506.7.6 Integration of Distributed Energy Resources 1506.7.7 Market Interconnections 1506.7.8 Pricing Mechanisms 1516.7.9 Environmental Considerations 1516.7.10 Challenges and Barriers 1516.7.11 Future Trends in Energy Market Design 1516.8 Blockchain Technologies 1516.8.1 Key Components of Blockchain Technology 1526.8.1.1 Blocks 1526.8.1.2 Chain 1526.8.1.3 Nodes 1526.8.1.4 Consensus Mechanisms 1526.8.1.5 Cryptographic Hash Functions 1526.8.1.6 Smart Contracts 1526.8.1.7 Tokens and Cryptocurrencies 1536.8.1.8 Wallets 1536.8.2 Types of Blockchain Technology 1536.8.2.1 Public Blockchain 1536.8.2.2 Private Blockchain 1536.8.2.3 Consortium Blockchain 1536.8.2.4 Hybrid Blockchain 1536.8.2.5 Sidechains 1546.8.2.6 Layer 2 Solutions 1546.8.3 Features of Blockchain Technology 1546.8.4 Benefits of Blockchain Technology 1546.8.5 Challenges and Limitations of Blockchain Technology 1556.8.6 Applications of Blockchain Technology 1566.9 Role of Market Makers in MEHs 1576.9.1 Providing Liquidity 1576.9.2 Reducing Bid-Ask Spreads 1576.9.3 Price Discovery 1576.9.4 Stabilizing Markets 1586.9.5 Reducing Information Asymmetry 1586.9.6 Risk Management 1586.9.7 Facilitating Arbitrage 1586.10 Smart Contracts Between EHs 1586.10.1 Role of Smart Contracts Between Energy Hubs 1586.10.1.1 Energy Trading 1596.10.1.2 Dynamic Pricing 1596.10.1.3 Automated Energy Distribution 1596.10.1.4 Microgrid Management 1596.10.1.5 Energy Storage Management 1596.10.1.6 Grid Balancing and Stability 1606.10.1.7 Carbon Credits and Sustainability Incentives 1606.10.1.8 Grid Services (Demand Response) 1606.10.1.9 Dispute Resolution 1606.10.2 Benefits of Smart Contracts in Energy Hubs 1616.11 Algorithms for Energy Trading Among EHs 1616.11.1 Market-Based Algorithms 1616.11.1.1 Auction Mechanisms 1616.11.2 Game Theory Approaches 1616.11.2.1 Nash Equilibrium 1616.11.2.2 Cooperative Game Theory 1616.11.3 Optimization Algorithms 1626.11.3.1 Linear Programming (LP) 1626.11.3.2 Mixed-Integer Programming (MIP) 1626.11.3.3 Dynamic Programming 1626.11.4 Machine Learning Techniques 1626.11.4.1 Reinforcement Learning (RL) 1626.11.4.2 Neural Networks 1626.11.5 Multiagent Systems 1626.11.5.1 Distributed Algorithms 1626.11.5.2 Consensus Algorithms 1626.11.6 Forecasting Models 1636.11.6.1 Time Series Analysis 1636.11.6.2 Weather Forecasting Models 1636.11.7 Blockchain and Smart Contracts 1636.11.7.1 Decentralized Trading Platforms 1636.11.8 Heuristic Methods 1636.11.8.1 Genetic Algorithms 1636.11.8.2 Particle Swarm Optimization 1636.12 Regulatory Framework for MEHs 1636.12.1 Market Structure and Design 1636.12.2 Price Formation Mechanisms 1646.12.3 Transparency and Reporting 1646.12.4 Market Power and Competition 1646.12.5 Consumer Protection 1646.12.6 Environmental and Sustainability Standards 1646.12.7 Grid Reliability and Security 1656.12.8 Technological Integration 1656.13 Benefits of Market Trading in MEHs 1656.14 Challenges and Limitations of MEHs 1666.15 Case Studies of Energy Trading in MEHs 1666.15.1 Indian Energy Market 1666.15.2 Nord Pool Power Market 1666.15.3 Electric Reliability Council of Texas (ERCOT) in Texas 1676.15.4 Australian National Electricity Market (NEM) 1676.15.5 California Electricity Market 1676.16 Future Trends in Energy Trading in MEHs 1676.16.1 Increased Integration of Renewables 1676.16.2 Decentralized Energy Systems 1686.16.3 Advanced Storage Solutions 1686.16.4 Enhanced Regulatory Frameworks 1686.16.5 Digitalization and Smart Grids 1686.16.6 Global Market Interconnections 1686.16.7 Demand Response Programs 1686.16.8 Focus on Sustainability 1696.17 Conclusion 169References 1697 ImpactofHighorFullShareofRESsandLoad-Side Uncertainty on Multi-Vectored Energy Hubs 173Stephen Oko Gyan Torto, Rupendra Kumar Pachauri, and Jai Govind SinghNomenclature 1737.1 Introduction 1747.1.1 Overview of Multi-Vectored Energy Hubs (MV-EHs) 1777.1.1.1 Core Components of MV-EHS 1777.1.2 Challenges and Opportunities 1777.2 RESs and Their Growing Share 1797.2.1 Trends in RESs Deployment 1817.2.2 Opportunities and Challenges of High RESs Share 1827.3 Handling RES Uncertainty 1837.3.1 Challenges Posed by RES Variability 1847.3.2 Strategies for Managing RES Uncertainty 1857.4 Forecasting Techniques 1857.4.1 Role of Predictive Models in Uncertainty Management 1857.4.1.1 Key Benefits 1867.4.2 Energy Storage Systems as a Buffer for RES Variability 1867.4.3 Innovative Technologies in RES Uncertainty Handling 1877.5 Impact of High or Full RES Share on MV-EHs 1887.5.1 Effects on Energy Production and Distribution 1887.5.2 Case Studies of MV-EHs With High-RES Share 1907.6 Load-Side Uncertainty and Its Impact on MV-EHs 1917.6.1 Understanding Load-Side Uncertainty 1917.6.2 Key Factors Affecting Load-Side Uncertainty 1927.6.3 Demand Side Management Strategies 1937.6.4 Real-Time Pricing and Its Effects on Consumption Patterns 1937.6.5 Technologies for Demand Forecasting and Management 1947.7 Integrated Energy Management Strategies 1957.7.1 Combining Forecasting, RES Handling, and DSM 1957.7.2 Role of Smart Grids and IoT in Integrated Management 1967.8 Multi-Vectored Energy Hub 1967.8.1 Concept of Energy Hub 1967.8.2 Data 1997.8.3 Case Study I 2007.8.4 Case Study II 2037.9 Conclusion and Recommendation 205References 2098 Green Energy, Greener Future: Bioenergy’s Role in Carbon Reduction 213Nilay Kumar Sarker and Prasad Kaparaju8.1 Introduction 2138.2 The Significance of Bioenergy 2148.2.1 Limitations of Wind and Solar Energy 2148.2.2 Benefits of Bioenergy 2158.2.3 Strategies for Low-Carbon Transition Via Bioenergy 2168.3 Integrating Bioenergy into National and Regional Emission Reduction Plans: A Case Study Approach 2178.3.1 Bioenergy in Europe: A Regional Overview 2178.3.2 Bioenergy Initiatives in the Nordic Countries 2188.3.3 Bioenergy Contributions to Emission Reductions in Nigeria 2188.3.4 Uganda’s Approach to Bioenergy 2198.3.5 The Role and Potential of Bioenergy in the United States 2208.3.6 Bioenergy’s Role and Potential in India 2208.3.7 The Role and Potential of Bioenergy in the United States 2218.3.8 Bioenergy’s Role and Potential in Brazil 2228.4 Developing Policy Frameworks to Support Bioenergy 2238.4.1 Policy Strategies in the Nordic Countries 2238.4.2 United Kingdom: Policies Driving Bioenergy 2248.4.3 Bioenergy Policy Landscape in Brazil 2258.4.4 India’s Framework for Bioenergy Development 2258.4.5 Bioenergy Policy Framework in the United States 2268.4.6 Bioenergy Policies in China 2268.4.7 Comparative Analysis of Global Bioenergy Policies 2278.5 Overcoming Barriers to a Low-Carbon Society Through Bioenergy 2278.6 Explorative Case Studies on Bioenergy Implementation 2288.6.1 Innovations in Lignocellulosic Biomass Utilization 2288.6.2 Bioenergy Development in Taiwan 2298.6.3 Bioenergy in Eastern Africa: Challenges and Opportunities 2298.6.4 Bioenergy in Australia: Current Status and Future Potential 2308.7 Bioenergy Coupled with Carbon Capture and Storage (BECCS) 2318.7.1 Advancing Negative Emissions in Pursuit of a Low-Carbon Society 2318.7.2 Exploring Local-Scale Opportunities for Carbon Reduction 2328.7.3 BECCS Implementation Examples from Tanzania 2338.8 Conclusion 233References 2349 Perspectives of Integrating Bioenergy into the Energy Mix in Developing Nations: A SWOT Analysis 237Toyese Oyegoke9.1 Introduction 2379.2 Literature Review 2399.2.1 Overview of Bioenergy 2399.2.1.1 Thermochemical Process Technology 2399.2.1.2 Biochemical Process Technology 2409.2.2 State of Art in Bioenergy Integration in Developing Nations 2429.2.3 Previous Studies on SWOT Analysis of Bioenergy Integration 2439.3 Study Strategy 2459.3.1 Data Sources 2459.3.2 Method of Analysis 2459.4 SWOT Analysis 2469.4.1 The Strengths of Bioenergy Integration in Developing Nations 2469.4.1.1 Abundance of Biomass Resources 2469.4.1.2 Environmental Benefits and Improved Waste Management 2489.4.1.3 Energy Security 2499.4.1.4 Local Energy Production, Rural Development, and Social Acceptance 2499.4.2 The Weaknesses or Limitations of Bioenergy Integration Initiatives 2509.4.2.1 Lack of Infrastructure and High Initial Investment Costs 2509.4.2.2 Technological Challenges 2519.4.2.3 Limited Public Awareness and Acceptance 2519.4.2.4 Competition for Land Usage, Policy, and Regulatory Challenges 2529.4.2.5 Resource Availability and Market Access 2529.4.3 The Opportunities for Bioenergy Integration 2529.4.3.1 Government Incentives and Policies 2539.4.3.2 Growing Demand for Eco-friendly Sustainable Energy Sources and Their Export Potential 2539.4.3.3 Potential for Collaboration with International Organizations and Donor Agencies 2549.4.3.4 Improved Waste Management Technologies and Environmental Benefits 2549.4.3.5 Economic Diversification, Job Creation, and Community Development 2549.4.3.6 Energy Access, Technology Innovation, and Local Content Development 2559.4.4 The Potential Threats to Bioenergy Integration 2559.4.4.1 Competition from Low-Cost Fossil Fuels 2559.4.4.2 Policy and Regulatory Uncertainty and Social Resistance 2569.4.4.3 Vulnerability to Climate Change and Extreme Weather Events 2569.4.5 Key Deductions from the SWOT Analysis Results 2569.4.6 Exploration of Effective Implementation Strategy for Bioenergy Integration in Developing Nations 2579.4.7 SO Strategy 2589.4.8 ST Strategy 2589.4.9 WO Strategy 2599.4.10 WT Strategy 2599.4.11 Implementation Strategies Summary 2609.5 Integration of Bioenergy into Energy Hubs 2609.5.1 Role of Bioenergy in Energy Hubs 2609.5.2 Benefits of Integrating Bioenergy in Developing Nations’ Energy Hubs 2619.5.3 Challenges and Considerations 2629.6 Recommendations, Summary, and Suggestions for Future Studies 2629.6.1 Recommendations 2629.6.1.1 Policy and Regulatory Frameworks 2629.6.1.2 Capacity Building and Technology Transfer 2639.6.1.3 Financial Support and Investment 2639.6.1.4 Public Awareness and Stakeholder Engagement 2639.6.1.5 Research and Development 2639.6.2 Summary of Key Findings 2639.6.3 Suggestions for Future Research 264References 26410 Integration of Carbon Reduction Techniques (CDR) and Emission Trading Mechanisms Among MV-EHs 277Mohammad Parhamfar and Saeed Khorrami10.1 Introduction 27710.2 Energy System Models 27910.2.1 Energy System Optimization Models 27910.3 Energy System Simulation Models 28010.4 Power Systems and Electricity Market Models 28010.5 Qualitative and Mixed-Methods Scenarios 28110.6 A Review of Commitments and Protocols 28110.7 Glasgow COP26 Carbon Trading Agreement 28210.7.1 Carbon ETS Design 28310.7.2 European Union ETS 28410.8 The California Global Warming Solution Act (the United States) 28610.9 The Chinese Market 28710.10 Certified Emissions Reductions 28810.10.1 Clean Development Mechanism 28810.11 Analysis of Risks/Challenges of the Main ETS 29010.11.1 Carbon Pricing Scheme, Carbon Tax, and Emission Trading 29010.11.2 Cap-and-Trade Program 29210.11.3 Offset or Credit Programs 29310.11.4 Rate-Based Program 29310.11.5 Performance of Cap-and-Trade Program 29410.12 Carbon Tax 29410.13 Crediting 29510.13.1 GWP: Global Warming Potential 29510.13.2 Advantages and Disadvantages of a Carbon Tax 29610.13.3 Advantages and Disadvantages of Emission Trading 29610.14 How Is the Offset Market in Developed Countries? 29610.15 Peer-to-Peer Energy Trading System 29710.16 Blockchain Role in Carbon Trading 29710.17 Application of AI in Blockchain-Based Emission Trading 30110.17.1 Game Theory 30210.17.2 AI for Monitoring Carbon Footprint 30310.18 Optimization Approaches 306References 306Index 311