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Marko V. MANČIĆ Dragoljub S. ŽIVKOVIĆ Milena N. RAJIĆ Milan Lj. DJORDJEVIĆ


A polygeneration system is an energy system capable of providing multiple utility outputs to meet local demands by application of process integration. This paper addresses the problem of pinpointing the optimal polygeneration energy supply system for the local energy demands of a livestock farm in terms of optimal system configuration and optimal system capacity. The optimization problem is presented and solved for a case study of a pig farm in the paper. Energy demands of the farm, as well as the super-structure of the polygeneration system were modelled using TRNSYS software. Based on the locally available resources, the following polygeneration modules were chosen for the case study analysis: a biogas fired internal combustion engine co-generation module, a gas boiler, a chiller, a ground water source heat pump, solar thermal collectors, photovoltaic collectors, and heat and cold storage. Capacities of the polygeneration modules were used as optimization variables for the TRNSYS-GenOpt optimization, whereas net present value, system primary energy consumption, and CO2 emissions were used as goal functions for optimization. A hybrid system composed of biogas fired internal combustion engine based co-generation system, adsorption chiller solar thermal and photovoltaic collectors, and heat storage is found to be the best option. Optimal heating capacity of the biogas co-generation and adsorption units was found equal to the design loads, whereas the optimal surface of the solar thermal array is equal to the south office roof area, and the optimal surface of the PV array corresponds to the south facing animal housing building rooftop area.

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MANČIĆ, Marko V. et al. OPTIMIZATION OF A POLYGENERATION SYSTEM FOR ENERGY DEMANDS OF A LIVESTOCK FARM. Thermal Science, [S.l.], v. 20, p. S1285-S1300, feb. 2017. ISSN 2334-7163. Available at: <http://thermal-science.tech/journal/index.php/thsci/article/view/1650>. Date accessed: 14 dec. 2017. doi: https://doi.org/10.2298/TSCI16S5285M.
Received 2017-02-07
Accepted 2017-02-07
Published 2017-02-07


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