OPTITwin – Next-Generation Digital Twin Platform for Intelligent Optimization of Heating and Cooling in Buildings

Project Description

OPTITwin addresses the need for more intelligent, coordinated, and predictive operation of heating and cooling systems in buildings through the development and demonstration of a next-generation AI-enhanced Digital Twin platform. The project integrates real-time building representation and system intelligence with forecasting, predictive control, optimization, and data analytics to support more effective operation of building energy systems.

At the core of OPTITwin is the integration of heating, cooling, ventilation, district energy systems, and thermal energy storage within a common digital-twin framework. The project advances predictive HVAC control through forecast-driven operation and develops methods for coordinated optimization across interacting building and energy-system components. The project also builds on competencies in modelling and simulation, semantic interoperability, AI-driven control, fault detection and diagnostics, performance analysis, data analytics, and software engineering.

A key technical element is the development of a digital twin platform, with forecasting, detection, predictive-control and optimization algorithms. The project further addresses use cases, key performance indicators, technical requirements, system integration, and real-world demonstration and validation.

Through its real-world demonstration activities, OPTITwin aims to advance building HVAC operation from conventional reactive approaches toward predictive, integrated, and data-driven optimization, establishing a foundation for scalable and intelligent operation of future building energy systems.

Project Summary