Evaluation of the return temperature reduction potential of optimized substation control

Network temperatures play a major role in the overall efficiency of district heating networks. Low network temperatures are desirable, because they allow high heat production efficiency and low network heat losses. Furthermore, low network temperatures benefit the injection of low-temperature renewable and excess heat sources. At the same time, a high temperature difference between supply and return pipes is desired to limit the network flow rate. This reduces pumping power and increases the network capacity. Whereas the network supply temperature is governed by the heat supply, the network return temperature is determined by the connected customers. This paper focuses on an approach for reducing the network return temperature by considering the control of district heating substations for space heating. Optimal heating control curves exist for the secondary-side supply temperature and flow rate that minimize the network return temperature of indirect substations. The goal is to investigate the impact of optimized control curves on the network return temperature, under various circumstances. Using a steady-state model of an indirect substation connected to a radiator system, the optimal control strategy is calculated. Its performance is compared to that of traditional control using a pre-set heating curve. The results show that the biggest impact occurs in partial-load conditions, with a potential for reducing the network return temperature by up to 9.9 degrees C (average 6.0 degrees C) and primary flow rate reduction up to 14.7 % (average 7.6 %). A parametric analysis to evaluate the impact of the network supply temperature, heat demand and heating system design sizing is presented. It is concluded that the use of optimized substation control for space heating could significantly reduce the network return temperature and primary flow rate. This would benefit the overall energetic system performance of district heating grids. (C) 2018 The Authors. Published by Elsevier Ltd.