Abstract

The task of fuel and energy balance preparation for heat energy sources in inadequate data conditions is an urgent issue, especially for the outdated boilers. It is difficult to use formulas for physically worn-out systems description, mainly because thermotechnical characteristics of the insulating components have significant deviations from the standard values. Boiler’s equipment physical depreciation increases greenhouse gas emissions into the atmosphere. Therefore, dealing with modernization funding feasibility of the heat energy sources, and also for periodic adjustment works that help to reduce harmful substance emissions into the atmosphere, requires the use of a fairly complete mathematical model of a boiler and a heat network. However, the lack of data makes it very difficult to formulate a reliable model. Status analysis of every element in the system is a labor-intensive and expensive task. Another extremely labor-intensive issue is a determination of the forecasted thermal energy demand of the municipal consumers and sector of housing and public utilities. Physically worn-out buildings have low thermal resistance, which increases heat demand. Calculation of the necessary amount of heat generation by the worn-out boilers for the city districts with worn-out buildings is difficult due to lack of a wide range of data about the boiler’s condition, network condition, and heated buildings condition. The paper presents the predictive energy balance preparation method using the statistical method of information processing only.

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