Modeling of District Heating Networks for the Purpose of Operational Optimization with Thermal Energy Storage

Abstract

The aim of this document is to present the topic of modeling district heating systems in order to enable optimization of their operation, with special focus on thermal energy storage in the pipelines. Two mathematical models for simulation of transient behavior of district heating networks have been described, and their results have been compared in a case study. The operational optimization in a DH system, especially if this system is supplied from a combined heat and power plant, is a difficult and complicated task. Finding a global financial optimum requires considering long periods of time and including thermal energy storage possibilities into consideration. One of the most interesting options for thermal energy storage is utilization of thermal inertia of the network itself. This approach requires no additional investment, while providing significant possibilities for heat load shifting. It is not feasible to use full topological models of the networks, comprising thousands of substations and network sections, for the purpose of operational optimization with thermal energy storage, because such models require long calculation times. In order to optimize planned thermal energy storage actions, it is necessary to model the transient behavior of the network in a very simple way -allowing for fast and reliable calculations. Two approaches to building such models have been presented. Both have been tested by comparing the results of simulation of the behavior of the same network. The characteristic features, advantages and disadvantages of both kinds of models have been identified. The results can prove useful for district heating system operators in the near future.

Optimal Scheduling of Combined Heat and Power Generation Units Using the Thermal Inertia of the Connected District Heating Grid as Energy Storage

“…As well considering thermal inertia of buildings and heating grid dynamics [12] proposes an optimization model with fixed transport delays calculated based on design flows which allows to use off-the-shelf solvers. A very simple model of the heating grid as one dynamic energy mass is proposed and compared with other methods in a simulation in [13]. Groß starts from a detailed physical model as well, but in contrast to others trains a linear regression model using multiple simulations.…”

Comparison of various solution techniques in dispatching coupled electricity‐heat system with independent thermal energy storage

“…Moreover, thermal energy storage (TES) is appealing in future as its lower capital cost compared to electricity storage [15,16]. Relevant research on this topic is categorised into pipe-based TES [6,7,17], where the heat energy stored in pipelines are investigated, and non-pipe TES [2,9,13,[18][19][20][21][22][23], where the TES is formulated as independent equipment without considering heat networks. However, most reported research on operating non-pipe TES do not take the dynamics of heat network into account.…”

Mathematical Analysis of Optimal Operating Conditions in Heating Systems

“…Based on outdoor temperature prediction and process data history, Laakkonen et al [14] modeled delay as a distribution function and developed a robust optimizer to minimize pumping cost and heat loss; by optimizing the water supply temperature and flow rate, the heating system could run efficiently and smoothly. M. Leśko et al [15] have presented different approaches to a simplified modeling of district heating networks for optimization purposes. Yiwen Jian et al [16] analyzed an existing water temperature regulation mode and its impact on indoor environment and energy utilization on the basis of field investigation.…”