Determination of influential parameters for heat consumption in district heating systems using machine learning

Energy ◽  
2020 ◽  
Vol 201 ◽  
pp. 117585 ◽  
Author(s):  
Danica Maljkovic ◽  
Bojana Dalbelo Basic
Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 586 ◽  
Author(s):  
Danica Maljkovic

Assessing the influential factors on measured (or allocated) heat consumption in district heating systems is often limited by the available data. Within a project of modelling consumption in district heating systems in Croatia for the Ministry of Environmental Protection and Environment, an access to a complete billing database of the largest Croatian district heating company was granted. The company supplies approximately 126,400 final consumers (both households and businesses) over 375 km of distribution network. The billing database has 40 vectors in a few million single inputs. In addition to these data, a questionnaire is distributed to the final consumers in several buildings labelled as “model buildings”, gathering behavioural and demographic data of final consumers (such as occupancy, mode of space usage, heat comfort level, age of occupants, etc.). The two sets of data are then merged, and a correlation analysis is performed. Furthermore, a two-step regression analysis is performed based on variables from billing database in the first step, with added behavioural and demographic variables obtained from the questionnaires in the second step. The models from two steps are compared, tested and interpreted. Results of the most influential factors on heat consumption in district heating systems are given and the influence of the behavioural/demographic variables on the prediction accuracy of heating consumption is interpreted.


Author(s):  
A. V. Kiryukhin ◽  
V. M. Sugrobov

The forecast geothermal resources of Kamchatka are sufficient to generate 3900 MW of electrical energy. The same resources for heat supply are estimated at a capacity of 1350 MWt (thermal). Thermohydrodynamic TOUGH2 modeling of exploitation of already identified productive hydrogeothermal reservoirs with installed energy properties allows us to predict: 1) the possibility of increasing the electrical performance of already operating areas of the Mutnovsky field up to 105 MW and the Pauzhetsky field up to 11 MW using binary technologies; 2) the possibility of increasing heat generation at the Paratunskoye field with submersible pumps up to 216 MWt, which will fully ensure the heat consumption of the district heating systems of Petropavlovsk-Kamchatsky.


2021 ◽  
pp. 54-62
Author(s):  
V. Stennikov ◽  
E. Mednikova ◽  
I. Postnikov

The paper presents a method developed to determine an effective heating radius (EHR) in district heating systems (DHSs) in terms of reliable heat supply to consumers. The search for EHR for various heating mains from the considered district heating source in DHS involves identifying heat source operation zones in various city areas. At the same time, apart from the search for EHR, the nodal reliability indices are estimated for each consumer and then used (if necessary) to adjust the obtained EHR. The paper briefly discusses some of the practical research results.


Energy ◽  
2019 ◽  
Vol 188 ◽  
pp. 116085 ◽  
Author(s):  
Puning Xue ◽  
Yi Jiang ◽  
Zhigang Zhou ◽  
Xin Chen ◽  
Xiumu Fang ◽  
...  

2017 ◽  
Vol 116 ◽  
pp. 208-216 ◽  
Author(s):  
Christian Johansson ◽  
Markus Bergkvist ◽  
Davy Geysen ◽  
Oscar De Somer ◽  
Niklas Lavesson ◽  
...  

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