OPTiOptimisation of District Heating Cooling systems
The OPTi project aspires to create a long-lasting impact by rethinking the way district heating and cooling (DHC) systems are architected and controlled. The overarching goal is to create business benefit for the industry as well as to ensure optimal end-consumer satisfaction.
OPTi will deliver methodologies and tools that will enable accurate modelling, analysis and control of current and envisioned DHC systems. The methodology will be deployed both on a complete system level, and on the level of a building(s).
OPTi will treat the DHC system as a system subject to dynamic control, and will treat thermal energy as a resource to be controlled for DHC systems towards saving energy and reducing peak loads. This will lead to the most environmentally-friendly way of utilising energy sources, thus reducing the reliance on additional boilers running on oil and/or electricity and overall providing a socio-economically sustainable environment.
OPTi will help energy companies to operate both today’s and future DHC systems in an optimal way:
- on system level: opportunities for SMEs to provide new services/solutions are envisioned;
- on house level: more intelligent home DHC control systems like remote control and the consumer “virtual knob”;
- in general: it is foreseen that the OPTi framework will enable engineers to design and plan DHC
In particular the vision of OPTi includes the following main pillars:
- Rethink DHC systems through an architecture that can be adapted in real-time to exogenous and unpredictable factors and dynamics
- Exploit the hidden potential of passive-heat storage, thus turning the household into a heat battery
- Develop automated heat Demand Response mechanisms that make the most efficient distribution and use of heat while minimizing DHC system operational costs
- Bring the user in the foreground by: (i) minimizing user discomfort (ii) placing emphasis on securing user engagement through appropriate viable incentive mechanisms
- Validate the principles and techniques above with data-driven approaches as well as with two real-life pilot trials in a hospital and in a block of residential buildings.