Abstract
Currently, the district heating systems (DHSs) are intensively promoted both nationally and globally. The advantages of using these systems in urban areas compared to individual heating systems are practically indisputable. Still, it is essential that the calculation underlying the assessment of the economic profitability of the projects to connect the new heat consumers to DHS be made correctly by taking into account all the necessary investments and the benefits obtained from the additional amount of energy sale. The article presents the methodology for the optimal regression model selection that can be applied to predict the additional electricity produced in cogeneration mode in case of the new heat consumer connection to the DHS, based on the actual data of the thermal and electrical energy supplied to network from a CHP in the Republic of Moldova. At the same time, it is demonstrated that between the thermal energy supplied to a new consumer connected to DHS and the additional electricity produced in the cogeneration mode, there is a direct and linear correlation.
Highlights
The main purpose of the current projects on the district heating systems development in the Republic of Moldova is to provide for the heat consumers a high quality, reliable and affordable service
The results of the regression analysis: produced electricity - supplied heat The corresponding graphs for each heating season were drawn to verify the correlation between the electricity produced and the thermal energy supplied into the network
It is recommended to use the obtained linear regression model for the dependence of produced electricity - heat supplied into the network in the 2018-2019 heating season, to predict the additional electricity produced in cogeneration mode in case of the new heat consumer connection to the district heating systems (DHSs), used as a model in this article, namely: yy = 550,41 ⋅ xx + 338014, (3)
Summary
The main purpose of the current projects on the district heating systems development in the Republic of Moldova is to provide for the heat consumers a high quality, reliable and affordable service. The calculation temperatures of indoor and outdoor air, while the amount of electricity to be produced with the production of thermal energy for the new consumer, cannot be determined by applying a calculation formula This problem can be solved by using regression analysis. The R2 = 0,4036 (Figure 1) analysis results that the heating degree-days influenced the natural gas consumption for space heating in 2020 insignificantly Another driver that influenced the gas consumption in 2020 must be identified (for instance: possible thermal agent leaks in the distribution networks, heat supply with a higher temperature than it is required following the outdoor air temperature, increase the number of thermal energy consumers, etc.).
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