Impact factors of heat generation units for zoned temperature controlled in office buildings

Abstract

According to the German Trade and Invest group, there are 17 million heating generators in Germany and only 12% of them are considered state of the art with an energy conversion efficiency of more than 90 %. 70% of them are between 10 and 24 years old having an energy efficiency of around 85 %. The remaining units are older than 24 years old and have a low efficiency of 65% [1]. From these heating generators, around 80% are either fuelled by oil or natural gas normally in the formof boilers which are responsible for the majority of space heating [2]. Even though the boilers have a high efficiency rating, their optimum operating efficiency in day to day operations is rarely achieved. Germany has for target to reduce its heating requirements by 20% in the building sector by 2020 when compared to 2005 figures [3]. To achieve this target, either the complete replacement of old boilers with newer, more efficient ones or the optimisation of the operation of the existing boilers have to be done. The former can prove to be very resource-intensive. The implementation of the latter requires that the most influential factors on the boiler are known. This thesis, using a simulated model, investigates and obtains these factors. In collaboration with vilisto, a Hamburg based company specialised in effortless room temperature control using smart thermostats for office buildings, useful building characteristic data for the simulations was obtained. The simulations were done for buildings with three different insulation envelopes; well insulated, averagely insulated and poorly insulated in two separate outdoor conditions. The building’s insulation turned out to have the most impact on the capacity of the boiler and the user comfort; around twice more heat is needed to meet the demand for a poorly insulated building as for a well insulated building. The operating efficiency and the number of cycles of the boiler are greatly influenced by the type of control method that is implemented. Maximum cost and energy savings of around 59% were obtained with the best control method. With outdoor temperatures of -20 °C, it was observed that having a tank did not positively affect the results due to the high heat demand. Lastly, reducing the desired