A Review of District Heating Systems: Modeling and Optimization

Abstract

The ever-increasing demand for heating in different sectors, along with more preventative regulations on greenhouse emissions, has forced different countries to seek new alternatives to heat buildings such as district heating system (DHS). Although rudiments of DHSs can be observed over the centuries, it was not widely implemented until last two decades when the DHS became a strategy to design more energy-efficient way of heating the buildings. This paper suggests a new approach in categorizing DHSs based on their geographical location, scale, heat density, and end-user demand. Furthermore, this paper reviews system and component modeling approaches with a focus on DHS load prediction. Main limitations of the existing methods are also addressed and discussed with a comprehensive review of the recent studies. Finally, the state of the art in optimization of the different DHSs has been reviewed and categorized based on their objective functions and the techniques used for solving optimization problems (deterministic and heuristic).

A review of modelling and optimisation techniques for district heating systems

“…CHP, geothermal energy, and biomass are known as permanent sources, whereas the wind and solar energies, with high rate of fluctuations, are categorised as nonpermanent sources …”

“…User system modelling consists in determining the user heat demand to define the total network load and design an HX for each user . Diverse approaches have been indicated in the literature to estimate the user demands using some deterministic and stochastic methods…”

“…39 CHP, geothermal energy, and biomass are known as permanent sources, whereas the wind and solar energies, with high rate of fluctuations, are categorised as nonpermanent sources. 26 For modelling the heat sources in a DHS, a minimum efficiency index is defined according to the heat source type. For example, the efficiency of a CHP heat source can be assessed using the primary energy saving (PES) index calculated as follows 40 :…”

“…During the past years, a large variety of nonlinear and heuristic methods have been used for heating network optimisation in design and operation …”

“…[23][24][25] During the past years, a large variety of nonlinear and heuristic methods have been used for heating network optimisation in design and operation. 26,27 This review article provides an extensive survey on the modelling and optimisation of DHSs and their recent advances focused on the heat distribution network. For this purpose, the major components of a DHS have been described and discussed, and their modelling has briefly reviewed including numerical simulation models for heat sources, end-users, and especially, the distribution network.…”