Building Energy Simulation And Modelling

Simulation And Modelling Digital tools and platforms that use data inputs, statistical models, ML algorithms, physics-based simulation engines or digital twin infrastructure – individually or in combination – to represent, predict or optimize the energy performance of buildings, supporting decisions across the full building life cycle, from design and retrofit planning to operational management and long-term scenario analysis.

Help building owners solve the following challenges: High and volatile energy costs by forecasting consumption, modelling tariff impacts and identifying opportunities to reduce energy use before costs escalate. Poor visibility into building performance through real-time monitoring of energy consumption, equipment operation and anomalies across single buildings and entire portfolios. The "energy performance gap" where buildings consume significantly more energy than design models predicted. Continuous modelling and calibration help align actual performance with design intent. Decarbonization planning uncertainty by allowing organizations to test retrofit options, electrification strategies and carbon reduction pathways before investing capital. Difficulty prioritizing capital investments through simulation of future energy savings, carbon impacts, payback periods and investment scenarios, creating more defensible business cases. Regulatory and reporting pressures by supporting compliance with evolving energy efficiency standards, carbon disclosure requirements and sustainability frameworks. Inability to predict future building performance using forecasting and scenario analysis to understand how assets will perform under different operating conditions, energy prices or climate futures. Climate resilience risks through modelling of overheating, extreme weather, grid stress and future climate scenarios to inform resilience strategies. Verification of retrofit benefits with measurement and verification (M&V) capabilities that quantify actual performance improvements and savings after projects are implemented. Management of complex energy systems including solar, batteries, EV charging and demand-response programs by evaluating their impact on building performance and operating costs. Limited operational expertise by using cloud platforms, AI and digital twins to make advanced energy insights accessible to facility managers and non-specialists.