Optimization of the Thermal Request Profiles of Buildings Connected With a Large District Heating Network

Abstract

Thermal storage is very important in modern district heating networks in order to increase the share of waste heat and heat produced through renewable sources and cogeneration. The role of thermal storage is even more important in the case of Mediterranean areas, where climate and user behavior cause high peak requests in the morning. Nevertheless the installation of large storage volumes is not always feasible, especially in dense urban areas, therefore alternative options are investigated. One of these options is virtual storage. This consists in proposing changes to the thermal request profiles of some of the connected buildings, in order to obtain a peak shaving, which is an effect similar to that obtained using storage. To perform such approach there are two crucial elements: 1) an advanced ICT solution able provide real time information about the thermal request of the buildings and the thermodynamic conditions at the thermal substations; 2) a detailed thermo fluid-dynamic model of the district heating network able to simulate the temperature evolution along the network as the function of time. Using physical models it is possible to examine the effects, obtained by modifying the thermal request of users, on the total load of the thermal plants feeding the network. In particular, the model is applied to the analysis of changes in the start-up time of the buildings as well as possible pauses during the day. The start-up strategy should not produce significant effects on the building temperatures, so that acceptable comfort standard can be guaranteed. This is checked using a compact model of the buildings which parameters are obtained through data measured at the thermal substations. These changes in the request profiles usually involve a larger heat request. Nevertheless, peak shaving is accompanied by a reduction in heat generation of boilers and an increase in the thermal production of efficient systems, such as cogeneration units. This results in a significant reduction in the primary energy consumption. The goal of the analysis is to find the optimal start-up strategy in order to minimize the primary energy consumption at the thermal plants. An application to the Turin district heating network, which is the largest network in Italy, is presented. In particular, a subnetwork connecting the main transport network to about 100 buildings located in the central area of the town is considered. The analysis if performed in selected days where the optimization was conducted the day before on the basis of weather forecasts and then applied to the network. Despite the changes in the request profiles could be applied only to a limited number of buildings, the analysis show that the peak request can be reduced. Simulations performed considering the application of changes to a larger number of buildings show that reduction in the primary energy consumptions of the order of 1.25% can be obtained.