Bachelor's thesis Julian Wyszynski
Optimisation Potential of dictrict cooling system of Forschungszentrum Jülich
Rising energy demand and decreasing availability of fossil energy sources, fosters the necessity to
develop alternative energy generation methods and increase the energy efficiency in all sectors. Airconditioning,
ventilation and refrigeration already forms a great part of the energy consumption, of
whichmore than a quarter is produced by buildings’ air-conditioning. Furthermore, a rapid increase
in this sector because of rising comfort standards and decreasing technology prices is predicted.
In order to improve the efficiency of refrigeration systems, district cooling networks can be used. In
these networks a fluid at a lowtemperature level is produced in central chiller plants and distributed
to several consumers through a pipe network. The main advantages are on the one hand the possibility
to use synergy effects of the simultaneous generation of electrical energy and cold fluid and on
the other hand the possibility of using bigger, more efficient chillers. This thesis analyses different
optimisation methods for district cooling systems with a focus on the optimisation of load sharing
for systems with more than one chiller. [Beghi u. a., 2011] presents a method using an evolutionary
algorithm to optimise the control strategy of a multi chiller system based on the objectives of energy
consumption reduction and a decrease of on/off switch processes. This method shall be applied to
the example object of the cold generation of the Forschungszentrum Jülich. An investigation based
on measured data demonstartes high variances in the efficiency characteristics of the eight chillers.
Furthermore, a simple control strategy is identified which leads to the expectation of a high optimisation
potential. The optimisation method of [Beghi u. a., 2011] is refined and applied to a created
reference scenario of the example object. The evaluation of the results shows a decrease in the electrical
energy demand of 8,61% and a reduction of on/off switch processes of 27,29%. Based on these
results a simplified control strategy, which could be implemented in the existing system, is derived.
Evaluation of this strategy shows a decrease in the electrical energy demand of 8,45% and a reduction
of on/off switch processes of 41,39%. Before the advanced control strategy is implemented in
the system a simulation is advised.