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Umfang: 1 online resource (394 pages)

Ausgabe: 1st ed.

ISBN: 9783031588976

Serie: Lecture Notes in Energy Series ; v.101

Anmerkung: Intro -- Foreword -- Preface -- Contents -- Introduction -- 1 The IEA Energy Technology Systems Analysis Program: From the Oil Crisis to the Sustainable Development Goals -- 1.1 IEA-ETSAP Technology Collaboration Programme -- 1.2 Building and Adapting Modelling Tools and Capabilities to Evolving Challenges -- 2 The MARKAL/TIMES Family of Models: Examples and Openness -- 3 This Book: Net Zero Emissions, SDGs, and Energy Security -- 3.1 Part I: Adapting Energy Systems Models to Inform SDGs -- 3.2 Part II: Using Energy System Modelling to Support the Transition to Renewable Energy -- 3.3 Part III: Informing Energy Security with Energy System Models -- 3.4 Part IV: Engaging with Policymakers on Energy System Models -- 3.5 Further Information on Energy Systems Modelling and SDGs -- References -- Part I: Adapting Energy System Models to Inform SDGs -- Low Energy Demand Scenarios for OECD Countries: Fairness, Feasibility and Potential Impacts on SDGs -- 1 Introduction -- 2 Review of Published LED Scenarios -- 2.1 Scenarios Overview -- 2.2 Demand Mitigation Measures -- 2.3 Impacts of LED Scenarios -- 3 The Feasibility and Fairness of LED Scenarios -- 3.1 The Economy and the Rebound Effect (Feasibility) -- 3.1.1 Demand and the Economy -- 3.1.2 The Rebound Effect -- 3.2 Price Elasticity (Fairness) -- 3.3 Model Boundaries (Methodology) -- 4 Impacts of LED Scenarios on SDGs -- 4.1 SDG 1.2: Poverty -- 4.2 SDG 7.1: Access to Energy -- 4.3 SDG 7.2: Renewable Energy -- 4.4 SDG 7.3: Energy Efficiency -- 4.5 SDG 10.1: Overcoming Income Inequality -- 4.6 SDG 12.2: Use of Resources -- 4.7 SDG 16.7: Participatory Decision Making -- 5 Conclusions -- References -- Implications of the Net Zero Transition Scenarios on SDG Indicators: Linking Global Energy System, CGE and Atmospheric Source-... -- 1 Introduction -- 2 Methodology -- 2.1 KINESYS Global Energy System Model. , 2.2 ENVISAGE Computable General Equilibrium Model -- 2.3 TM5-FASST Atmospheric Source-Receptor Model -- 2.4 Model Linking -- 2.5 Scenario Framework -- 2.6 SDG Indicators -- 3 Results and Discussion -- 3.1 Emission Pathways -- 3.2 Impacts on SDGs at the Global Level Show Major Co-benefits But Also Highlight Several Trade-Offs -- 3.3 Alternative Revenue Recycling Options Might Strengthen Positive Spillovers -- 3.4 It Is Important to Properly Capture the Interactions Across Various SDG Dimensions: A Case of Air Pollution-Related Mortal... -- 4 Conclusions -- References -- Accelerating the Performance of Large-Scale TIMES Models in the Modelling of Sustainable Development Goals -- 1 Introduction -- 2 Methodology -- 2.1 Overview of the EUSTEM Model -- 2.1.1 Generation of EUSTEM Instances with High Temporal and Spatial Resolution -- 2.2 Using the CPLEX/Barrier Interior Point Solver for Shared-Memory Systems -- 2.2.1 Accelerating the Cholesky Factorisation of CPLEX/Barrier -- 2.2.2 Improving the Starting Point and Avoiding ``Wasted ́́Iterations in Barrier -- 2.2.3 Accelerating the Crossover Algorithm -- 2.2.4 Using Parallel Mode in Barrier -- 2.3 Using the PIPS-IPM++ Parallel Interior Point Solver for Distributed-Memory Systems -- 2.3.1 Annotating Variables and Equations to Reveal the Block Structure of the Model Matrix -- 2.3.2 How to Solve an Annotated Model with the PIPS-IPM++ Solver -- 3 Results -- 3.1 How to Accelerate the CPLEX/Barrier in Shared-Memory Systems -- 3.1.1 Step 1: Examining if Passing the Primal Problem Performs Better Than Dual -- 3.1.2 Step 2: Identifying the Number of Dense Columns to Minimise Cholesky Factorisation Complexity -- 3.1.3 Step 3: Exploring Different Ordering Algorithms and Starting Point Heuristics for Barrier -- 3.1.4 Step 4: Eliminating ``Wasted ́́Iterations -- 3.1.5 Step 5: Accelerating the Crossover Algorithm. , 3.2 Insights from Parallel Solving with PIPS-IPM++ -- 3.2.1 Annotation Strategy for the Block Definitions -- 3.2.2 PIPS-IPM++ Solution Times -- 3.3 Insights from Different Spatial and Temporal Resolutions in Modelling SDG7 and SDG13 -- 3.3.1 Different Regional Aggregations of ``Europe ́́Yields Different Projections of Technology Uptake -- 3.3.2 Different Timeslices Aggregations Yield Different Projections of Flexibility in the Energy System -- 3.3.3 Different Regional and Temporal Aggregations Yield Different Projections of Energy System Cost -- 4 Conclusions -- References -- Enabling Coherence Between Energy Policies and SDGs Through Open Energy Models: The TEMOA-Italy Example -- 1 Introduction and Motivation -- 2 Model Structure -- 2.1 Power Sector -- 2.2 Constraints -- 2.3 Emissions Accounting Methodology -- 3 Sustainability Indicators -- 4 Scenarios and Results -- 4.1 Scenarios -- 4.2 Energy and Emissions -- 4.3 Sustainability -- 5 Conclusions and Perspectives -- 5.1 Conclusions -- 5.2 Perspectives -- References -- Part II: Using Energy System Modelling to Support the Transition to Renewable Energy -- Assessing the Impact of Climate Variability on Wind Energy Potential in Decarbonization Scenarios in Energy Systems Models -- 1 Introduction -- 2 Methods -- 2.1 Definition of the Decarbonization Scenarios -- 2.2 Data Pipeline Process -- 2.3 Global Statistical Analysis -- 2.4 Overview of the TIMES United States (TUSM) Energy System Model Framework -- 3 Results -- 3.1 Global Statistical Analysis -- 3.1.1 Africa -- 3.1.2 Oceania -- 3.1.3 Americas -- 3.1.4 Asia -- 3.1.5 Europe -- 3.1.6 Offshore -- 3.2 Decarbonizing the Electricity Generation -- 3.3 Decarbonizing New Capacity Installation -- 4 Conclusion -- References -- Clean and Affordable Norwegian Offshore Wind to Facilitate the Low-Carbon Transition -- 1 Introduction -- 1.1 Motivation. , 1.2 Energy Modelling Literature -- 1.3 Research Questions -- 2 Methodology -- 2.1 Energy System Model -- 2.2 Modelling of Offshore Wind -- 2.3 Case Studies and Sensitivity Analysis -- 3 Results -- 3.1 Norwegian Offshore Wind Resources -- 3.2 Offshore Wind Investments -- 3.3 Electricity Production and Use -- 3.4 Electricity Trade -- 3.5 Sensitivity on Acceptance for Onshore Wind and Transmission Cables -- 4 Conclusion -- References -- Will the Nordics Become an Export Hub for Electro Fuels and Electricity? -- 1 Introduction -- 2 Who Will Be the Future Net Exporter of Power and Green Fuels? -- 2.1 Hydrogen in the Context of the Nordics -- 2.2 Example 1: Analysis with DTU Balmorel Europe -- 2.2.1 EU Hydrogen Infrastructure in 2050 -- 2.2.2 Hydrogen Demand Assumptions -- 2.2.3 EU Self-Sufficiency -- 2.2.4 Blue Hydrogen Production -- 2.2.5 Generation and Storage Capacities -- 2.2.6 Transmission Infrastructure -- 2.2.7 Electricity and Hydrogen Exports -- 2.3 Example 2: Analysis with EML TIMES-NEU Model -- 2.3.1 Future Demand for Green Fuels -- 2.3.2 Development of Infrastructure -- 2.4 Take Aways from the Two Modelling Examples -- 3 How Is the Green Fuel Revolution in the Nordics Affecting SDGs? -- 4 Key Challenges and Social Concerns -- 4.1 Price Gap: A Battle of Colours -- 4.2 Delays and Challenges -- 4.3 Renewable Electricity: It Needs to Happen Sooner Rather than Later -- 4.4 Willingness-to-Change: The Carrot and the Stick -- 4.4.1 Political Willingness -- 4.4.2 Funding -- 4.4.3 Technology Maturity -- 5 Conclusion -- 5.1 Export Potential from the Nordics -- 5.2 Need for Ramping Up Wind, PV, Electrolysers, and Infrastructure -- 5.3 Political Decisions and Regulation -- 5.4 Sustainable Development Goals -- 5.5 Social Concerns -- References -- Transition Pathways for a Low-Carbon Norway: Bridging Socio-technical and Energy System Analyses. , 1 Introduction -- 2 Approach and Methods -- 2.1 Envisioning Socio-technical Transition Pathways -- 2.2 Energy-Economy Modelling -- 2.2.1 Energy System Analysis with IFE-TIMES-Norway -- 2.2.2 Regional Economic Analysis with REMES-Norway -- 3 Socio-technical Scenarios Definition, Quantifications and Bottlenecks -- 3.1 Scenario Storylines -- 3.1.1 Incremental Innovation Pathway (INC) -- 3.1.2 Technological Substitution Pathway (TECH) -- 3.1.3 Social Change Pathway (SOC) -- 3.1.4 Radical Transformation Pathway (RAD) -- 3.2 Transition Bottlenecks -- 3.3 Quantification of Socio-technical Transition Pathways -- 4 Results -- 4.1 Techno-Economic Analysis -- 4.1.1 Power Generation and Trade -- 4.1.2 Transport Fuels -- 4.1.3 Hydrogen Supply -- 4.1.4 CO2 Emissions -- 4.2 Regional Economic Analysis -- 5 Discussion -- 6 Conclusion -- References -- Part III: Informing Energy Security with Energy System Models -- Modelling of Demands of Selected Minerals and Metals in Clean Energy Transition with 1.5-2.0 C Mitigation Targets -- 1 Introduction -- 2 Overview of Input Data Formulation on Minerals and Metals and Modelling Approach -- 2.1 Data Formulation for Demands of Selected Minerals and Metals -- 2.2 TIMES-VTT Model Description -- 2.3 Description of Scenario Formulation with 1.5-2.0 C Mitigation Target -- 3 Key Results of Mineral and Metal Demands in the Clean Energy Transition -- 3.1 Scenario Results for Energy Systems and Greenhouse Gas Mitigation -- 3.2 Overview of the Demands of Selected Metals for Selected Technologies -- 3.3 Sufficiency of Cobalt, Copper, Dysprosium, Lithium, Neodymium, Silver, and Nickel in Climate Change Mitigation -- 4 Linking SDGs with the Clean Energy Transition -- 5 Conclusion -- References -- Emission Free Energy Carriers and the Impact of Trade to Achieve the 1.5 C Target: A Global Perspective of Hydrogen and Ammonia -- 1 Introduction. , 2 Research to Date.

Weitere Ausg.: Print version: Labriet, Maryse Aligning the Energy Transition with the Sustainable Development Goals Cham : Springer,c2024 ISBN 9783031588969

Sprache: Englisch

Schlagwort(e): Electronic books.

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