Improving heat measurement accuracy in district heating substations
Abstract (Summary)The idea of district heating is to heat up a whole district from a central source through a distribution network. The heat is extracted by heat exchangers and the water is then subsequently returned to the central source. The heat exchange between the district heating network and the building occurs in district heating substations. Heat meters are located in such substations and are divided into two main categories depending on their heat energy estimation frequency modes. Which are either constant or flow rate dependent. The Swedish district heating industry is a business with revenue of approximately 19.8 billion SEK (as of the year 2002). Considering an error of 1% in energy delivered, that is a loss of 198 million SEK, which justifies the current research. The accuracy in heat measurement for billing purposes is then one of the major reasons for conducting this research. Few studies have been done in this area. A Swedish study shows that the major causes of the errors are: flow meters, temperature sensors, integrating units, lightning, control systems, valves, leaks in heat exchangers and the dynamic heat demand imposed on the district heating substation. I have chosen to study the heat measurement errors due to dynamic load imposed on the district heating substation because they are the least investigated and presumably account for a substantial portion of the total error. I have delimited my research area to include single family houses, since the effects of dynamic heat load on heat metering are more important in this kind of dwelling. A major tool in the investigation has been simulations based on a Simulink model, of a district heating substation and a house. For this purpose, the simulation model has been extended to handle new heat measurement strategies. A district heating laboratory was built at Luleå University of Technology to test not only the accuracy of different heat measurement algorithms but also control and diagnosis methods. Based on analysis of the measurement strategies, an adaptive algorithm and a feed-forward method are proposed in this thesis to reduce the heat measurement errors due to the dynamic heat demand imposed on the substation. Simulations conducted show that the adaptive algorithm has a higher measurement accuracy than both kinds of existing heat meters. The feed-forward method has the highest measurement accuracy compared to both kinds of existing heat meters and the adaptive algorithm.
School:Luleå tekniska universitet
Source Type:Doctoral Dissertation
Date of Publication:01/01/2006