KiNESYS+

KiNESYS+ (Knowledge-Based Investigation of Energy System Scenarios) is a pioneering data management system that creates rich, tailored models with distinct regional or sectoral focuses. By making energy system modeling better, faster, and more accessible, KiNESYS+ empowers impactful decisions at global, regional, and national levels. It revolutionizes the way we explore energy transition scenarios using energy system models.

Nimble

Effortlessly enabling the rapid creation of tailored energy models, KiNESYS ensures agility in responding to diverse policy, technology, and market scenarios. This streamlined process prioritizes actionable insights, allowing users to focus on decision-making rather than technical complexity.

Accessible

Designed for inclusivity, KiNESYS leverages intuitive online interfaces that lower barriers to entry for non-modelers. It empowers stakeholders at all levels to interact with model output and input directly.

KAIZEN++

Rooted in the philosophy of continuous improvement and collective learning, KiNESYS fosters collaborative exploration and iteration. With each use and adaptation, the platform evolves, integrating feedback to enhance functionality and refine assumptions, ensuring it stays current in this rapidly evolving landscape.

Contents:

• Introduction
  • What is KiNESYS+?
  • Motivation
  • The Three Pillars of KiNESYS+
  • Model Setup and Collaboration
  • Future Vision
• Institutional and Research Applications
  • A New Scale of Deployment
  • Institutional Use Cases
  • Example: The World Bank’s CCDR Program and Regional Reports
  • Research Integration — Multi-Model SDG Analysis
  • What These Applications Reveal
  • The KiNESYS + Veda Online Impact
• Primary energy supply
• Power sector
  • Existing Stock Representation
  • Renewable Resource Characterization
  • Conventional Technology Characterization
  • Electricity Demand Load Shapes and Timeslice Design
  • Operational Constraints and Integration Limits
• Electricity Load Shapes
  • Overview
  • Methodology Workflow
  • Data Sources
  • Sectoral Disaggregation Methodology
  • Timeslice Aggregation
  • Literature Foundation
  • Conclusion
  • References
• Renewable Energy Characterization
  • Overview
  • Methodology Pipeline
  • Data Sources
  • Clustering Methodology
  • COM_FR: Energy Share by Timeslice
  • Firmness Coefficients
  • Connection Costs
  • Multi-Year Weather Support
  • Existing Capacity Allocation
  • VEDA Integration
  • Computational Implementation
  • Visualization
  • References
• Liquid fuels processing
  • Processing Framework
• Hydrogen
  • Hydrogen Production Pathways
  • Hydrogen Trade Infrastructure
  • Hydrogen End-Use Applications
• Energy trades
  • Trade Coverage
  • Electricity Trade Methodology
  • Gas Infrastructure Details
  • Hydrogen Trade Infrastructure
• Transport
  • Transport Mode Coverage
  • Road Transportation Vehicle Categories
  • Non-Road Transportation
• Industry
  • Petrochemicals
  • Iron and Steel
  • Cement
  • Ceramics
  • Glass
  • Aluminium
• Residential and commercial buildings
• Agriculture
• Carbon capture and storage (CCS)
• Demand Projection
  • Overview
  • Driver Preparation
  • Elasticity Estimation
  • Demand Projection
  • Demand Categories
  • Data Sources
• The Zen of GESM
• Data Sources
  • Energy Balances and Statistics
  • Macroeconomic Projections
  • Power Sector
  • Gas and LNG Infrastructure
  • Electricity Transmission and Trade
  • Oil and Gas Supply
  • Biomass and Land Use
  • Industrial Sector
  • Transport
  • Renewable Energy Potential
  • Renewable Resource Characterization
  • Carbon Capture and Storage
  • Climate Data
  • Electricity Demand Load Curves
• GitHub Desktop Guide
  • Installing GitHub Desktop
  • Key GitHub Operations
  • Why GitHub Desktop?
  • Getting Help