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Artificial neural networking model of energy and exergy district heating mony flows
https://orcid.org/0000-0003-2531-3081
Graphical abstract
Highlights District heating system thermo-economic model is developed. The energy and exergy models of mony flows were compared. Model computes the mony flows of 5 district heating consumers. Consumers located nearest to the source of heat pay 12.9% less by exergy model. For the same thermal power supplied last consumers pay the same excessive amount.
Abstract This paper describes a computation model using an artificial neural network (ANN) for a thermoeconomic analysis of district heating (DH) mony flows (MF). The model will compute the results of the MFs in accordance with an energy method or a caloric method and an exergy method at various DH substations. A heat distributer is unable to ensure the same quality of heat to all consumers due to the length of the network. A consumer nearest to the heat source receives heat of a higher quality than the last consumer. As the DH heat is usually calculated using the MF energy method, the available heat quantity that can actually be converted into another form of energy is not taken into account in the calculation. The above indicated deviations, however, are taken into consideration in the calculation of heating costs in accordance with the MF exergy method, giving a more realistic picture of the heating cost evaluation. Considering the first law analysis of thermodynamics, the amount of energy consumed is calculated disregarding the difference between work and heat. The analysis and design of engineering systems based on only the first law is not adequate [1].
Artificial neural networking model of energy and exergy district heating mony flows
https://orcid.org/0000-0003-2531-3081
Graphical abstract
Highlights District heating system thermo-economic model is developed. The energy and exergy models of mony flows were compared. Model computes the mony flows of 5 district heating consumers. Consumers located nearest to the source of heat pay 12.9% less by exergy model. For the same thermal power supplied last consumers pay the same excessive amount.
Abstract This paper describes a computation model using an artificial neural network (ANN) for a thermoeconomic analysis of district heating (DH) mony flows (MF). The model will compute the results of the MFs in accordance with an energy method or a caloric method and an exergy method at various DH substations. A heat distributer is unable to ensure the same quality of heat to all consumers due to the length of the network. A consumer nearest to the heat source receives heat of a higher quality than the last consumer. As the DH heat is usually calculated using the MF energy method, the available heat quantity that can actually be converted into another form of energy is not taken into account in the calculation. The above indicated deviations, however, are taken into consideration in the calculation of heating costs in accordance with the MF exergy method, giving a more realistic picture of the heating cost evaluation. Considering the first law analysis of thermodynamics, the amount of energy consumed is calculated disregarding the difference between work and heat. The analysis and design of engineering systems based on only the first law is not adequate [1].
Artificial neural networking model of energy and exergy district heating mony flows
https://orcid.org/0000-0003-2531-3081
Graphical abstract
Highlights District heating system thermo-economic model is developed. The energy and exergy models of mony flows were compared. Model computes the mony flows of 5 district heating consumers. Consumers located nearest to the source of heat pay 12.9% less by exergy model. For the same thermal power supplied last consumers pay the same excessive amount.
Abstract This paper describes a computation model using an artificial neural network (ANN) for a thermoeconomic analysis of district heating (DH) mony flows (MF). The model will compute the results of the MFs in accordance with an energy method or a caloric method and an exergy method at various DH substations. A heat distributer is unable to ensure the same quality of heat to all consumers due to the length of the network. A consumer nearest to the heat source receives heat of a higher quality than the last consumer. As the DH heat is usually calculated using the MF energy method, the available heat quantity that can actually be converted into another form of energy is not taken into account in the calculation. The above indicated deviations, however, are taken into consideration in the calculation of heating costs in accordance with the MF exergy method, giving a more realistic picture of the heating cost evaluation. Considering the first law analysis of thermodynamics, the amount of energy consumed is calculated disregarding the difference between work and heat. The analysis and design of engineering systems based on only the first law is not adequate [1].
Artificial neural networking model of energy and exergy district heating mony flows
Strušnik, Dušan (author) / Avsec, Jurij (author)
Energy and Buildings ; 86 ; 366-375
2014-09-25
10 pages
Article (Journal)
Electronic Resource
English
Artificial neural networking model of energy and exergy district heating mony flows
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Online Contents | 2009