Optiheat+ (Optiheat+)

New district heating networks evolve towards lower temperatures, multiple production sites and combined energy vectors. This significantly increases the operational complexity and the risk of suboptimal performance, reducing the economic viability. However, AI and big data, offer new opportunities to solve this challenge. Also in existing networks with ageing and operational faults, automated fault detection can lead to significant performance increase. European surveys show that DH networks have very limited automated supervision and rely on the operators' quality. OptiHeat+ tackles this challenge by exploring a permanent, online, intelligent system for automated fault detection and diagnosis in heating networks. It investigates predictive algorithms starting from real data and elaborates a new sensor prototype for water leakage detection. Innovative machine learning approaches, a unique lab and emulator infrastructure with key network components and real-life test beds will provide the required new intelligence. The investigated technology aims to be applicable in the majority of DH networks in Europe, targeting both existing and new networks. The potential is promising for Flanders, as district heating is an emerging market.

Keywords:DISTRICT HEATING, INFRASTRUCTURE OPTIMIZATION, DATA SCIENCE

Disciplines:Energy in buildings and built environments, Sustainable buildings and cities

Project type:Collaboration project