A method for assessing heat losses in developing countries with a focus on operational data of a district heating (DH) system

Abstract

The goal hereof was to propose a new method to estimate heat loss rates and find out how either the weather conditions of the serviced area or the available operational data affect each of the heat loss rate components. A linear regression function was used to describe the correlation between heat production and outdoor temperatures. Monthly measurements are used to estimate onsite heat loss in pipes in Russia. However, model coefficients can be adjusted to make it applicable to any European city, and the simulated behavior of the system is realistic in terms of the temperature profiles and heat losses for any DH system. The proposed model is more accurate than the conventional method with respect to the heat loss difference attributable to the variance in outdoor, supply, return, and ground soil temperatures. The difference between actual heat losses and heat losses projected by this new method varies from 0.4% to 1.2% with an average error of 0.65%. The results also show how the measurements state-of-the-art DH systems provide can help improve daily operation and maintenance to promote data-driven approaches. Technologies can be combined to further improve the performance.