In the transition towards a fully sustainable energy system, thermal networks are a key technology to significantly reduce CO2 emissions and local pollution, as well as to integrate residual energy sources and exploit flexibility. By 2050, regional, integrated and interconnected thermal networks will offer its users decarbonized, efficient, reliable and affordable energy solutions based on a high share of renewable energy sources, supported by digitalization. Digitalization allows district energy companies to offer diversified products and services that are highly automated, standardized, and personalized.
EnergyVille performs top basic, applied and industry-driven research to make thermal networks more intelligent, digitalized, autonomous as well as energy efficient. This leads to generic technologies and methodologies resulting in novel products and services that facilitate optimal design, optimal control, and improved maintenance of thermal networks.
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Erik De Schutter
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Johan Desmedt
Smart District Heating and Cooling Control
EnergyVille works on technologies tackling the energy efficiency of district heating networks. We have developed a smart DHC controller based on self-learning algorithms that enables to maximize the use of waste heat and renewable energy sources in DHC networks. The controller optimises the consumption of the buildings and districts and the demand of the network and optimally uses the potential of activating the building thermal mass as thermal energy storage system. The technology also controls the supply and consumption side (demand side management) of district heating networks and the different components of the energy system (such as storage units, heat pumps, etc.).
Network design
Themal networks are an important means to reduce the primary energy use for heating and cooling. Given the many design variables involved, the optimal design of thermal networks is nontrivial. Because manual and intuitive designs will most often lead to sub-optimal solutions, the use of optimisation methods is advised. Within EnergyVille we work towards the next generation network topology optimisation based on geo-spatial information (e.g. energy sources, energy users, installed storage systems). Starting from this input, the optimal routing and temperature level for the thermal network piping and optimal location of storage and conversion units can be determined.
Analytics
Substations in thermal grids make the connection between the grid and the buildings or installations connected to it. Traditionally, they are built with one or more heat exchangers, some piping and valves to regulate the flow and pressures, and a control framework combined with (limited) sensor equipment. Any flaw or fault in these substations results in an increased return temperature of the grid, which is extremely detrimental for low temperature operation and energy efficiency. These flaws and faults occur more than often in practice; studies have shown that up to 75% of all installed substations exhibit some kind of faulty behaviour.
To rapidly identify these faults or flaws, EnergyVille is developing automated methods for fault detection, fault diagnosis and correction for poorly working substations and building installations based on the use of big data. Adding this intelligence to substation and/or network controllers allows an easy and remote detection of inefficiencies in the system, which on their turn reduces the costs for maintenance and operation costs for both service companies and network operators. In addition, EnergyVille works on methods to lower the return temperature of heating networks significantly in order to increase the efficiency of the energy systems.
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