Thermal 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.
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.