Urban Energy Modelling System for Sustainable City Planning

The client faces difficulties in accurately modelling and optimizing energy infrastructure within urban environments to support sustainability goals. Existing perspectives lack comprehensive spatial and energy simulation capabilities necessary for informed decision-making in renewable energy deployment and microgrid integration.

A governmental or large municipal planning agency seeking to develop energy-efficient, sustainable urban areas through advanced spatial and energy modelling tools.

• Enable comprehensive spatial and energy modelling of urban areas for energy efficiency assessment.
• Develop simulation capabilities for optimizing photovoltaic placement, wind turbine siting, and microgrid configurations within cityscapes.
• Provide decision-support tools to estimate CO₂ emission reductions resulting from various renewable energy interventions.
• Establish a foundation for future proof-of-concept (PoC) projects that validate energy solutions within urban contexts.

• CityGML-based model import and management for detailed 3D urban spatial data.
• Simulation as a Service (SaaS) modules for photovoltaic system optimization including location and coverage analysis.
• Planning tools for micro-wind turbine installation, evaluating potential energy yield and spatial constraints.
• Microgrid installation simulation that models renewable energy source pairing and estimates CO₂ emission reductions.
• Recommendations engine based on scenario analysis, providing actionable insights for urban energy planning.

• GIS data repositories for urban spatial information.
• Renewable energy simulation tools and APIs.
• CO₂ emission calculation modules.
• Urban infrastructure data sources.

• System should support modeling of city areas spanning up to 100 square kilometers with detailed 3D data.
• Simulation modules must deliver results within minutes to support iterative planning.
• Data security compliant with municipal and environmental data standards.
• System designed for scalability to handle incremental data and user load growth.

The platform is expected to empower urban planners and energy managers with accurate, data-driven insights to optimize renewable energy deployment, leading to improved energy efficiency and significant CO₂ emission reductions. This approach will facilitate more informed decision-making, reduce planning costs, and support broader sustainability objectives across urban development projects.