The goal of this paper was to evaluate heat loss and the demand of district heating (DH) in the context of the fourth generation DH concept using a data-driven approach. The heat loss profile was calculated with GIS Zulu© (software (8.0.0.7539, Politerm, LLC, St.Petersburg, Russia) using eight various states of insulation, detailed information on thermal conductivity, internal heat transfer coefficient, and geometry of the concrete trench. There is a strong correlation between the heat sold and the average annual outdoor temperatures. The outstanding episodes are extremely rare, and the difference in the overall pattern is elusive. The results of the annual heat production and annual heat loss analyses were compared using three different estimation methods. The new method was the only one that showed a positive effect after the complete modernization of thermal insulation. The actual proportion of heat loss is much higher at 16%, while the actual heat delivery is less than anticipated at 85–86% only. The trend of the normative approach is correct but cannot determine changes in network heat loss due to aging. The method focuses on the effects of the state of insulation and actual supply temperature levels. The transition to smart energy systems includes strategic and progressive energy planning, as well as new pricing rules and tariffs. Thus, the method presented is the first step in the transition towards the fourth generation DH networks.

A district heating (DH) system in the Russian city of Omsk has been considered as a case study. This study is based on the data set of temperature and demand recorded over two-year operation of the DH system. We provide an insight on how the heat demand profile is met by the control framework. The paper quantifies the DH system performance by using heat load curves, maximum, minimum and average values of temperature, paving the way for a modelling approach. Central heating process in Omsk in 2017 was generally smoother than in 2016, while peak values are also lower. In 2017, its supply temperature was about 5°C closer to the control curve. The dispersion of the points was reduced between 2016 and 2017, especially at higher outdoor temperatures. Further lowering annual and peak heat demand, which are respectively 4% and 9% lower in 2017 should be a priority in future.

The constraint contains two elements, namely the heat losses and the electricity consumption for pumping at the producer. The aim was to achieve the lowest acceptable costs in an operation. The options with the supply temperature at the area starting point set to 80/60, then 60/40, and eventually 50/30 (low temperature, 4^th generation district heating) were tested. The balance between the savings due to lower heat losses and the electricity consumption of pumps could be performed to assess the economic viability of the solution. This means that if the electricity price is sufficiently high, the model will always choose to minimize electricity consumption and thereby, maximise the profit from high temperature difference. Results concerning heat losses consider both experiences of proper insulation of pipes with variety of design outdoor temperatures (DOTs) and long term measurements from a pump station for district heating (DH) network in Canberra, Australia. We also noted that the heat energy tariffs and purchase price of electricity affect a lot optimal configuration of a DH system. For the best scenario, solutions are obtained that reach over 12% of the available saving potential after calculating 11 equations. Knowing that the policy is updated on a case study base, this is considered a promising result.