Artificial neural networking model of energy and exergy district heating mony flows

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] .

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