Cogeneration is recognized as one of the most effective techniques to meet the increasingly stringent requirements regarding energy saving in buildings. Hospitals are great consumers of energy, both electrical and thermal: the use of heating and cooling equipment for maintaining satisfactory comfort and indoor air quality for the patients as well as the adoption of several electrical health equipments result in the highest energy consumption per unit floor area of the entire building sector. Moreover, the potential advantages to simultaneously meet electrical, thermal and cooling demand are concerned not only in higher final use efficiencies (compared to the separate production), with consequent reduction of pollutant and green house gases emissions, but also in promoting the use of alternative technologies. In the present study, a CHP plant for a hospital facility with 600 beds has been considered. More specifically, after the presentation of the hospital’s energy consumption, the optimal plant configuration (sizing of all cogeneration units) has been outlined by means of a numerical code (Trigen 3.0) in-house developed. Afterwards, in order to optimize the load distribution in a smart grid characterized by electrical, thermal, cooling and fuel energy fluxes, an ulterior numerical investigation has been performed. The software, named EGO (Energy Grids Optimizer) consists of a genetic algorithm procedure: it is able to define the optimal load distribution of a number of energy systems operating into a smart grid based on the minimization of an objective function which expresses the total cost of energy production. Finally, the results have demonstrated that the optimal plant and grid configuration, associated to the indication of the operation time and load status of each device, proved to be fully dependent on economical profitably aspects.

Optimum Sizing of Cogeneration for a Hospital Facility: Multi-Objective Analysis Applied to a Case Study

M. A. ANCONA;M. BIANCHI;C. BISERNI;F. MELINO;S. SALVIGNI;P. VALDISERRI
2017

Abstract

Cogeneration is recognized as one of the most effective techniques to meet the increasingly stringent requirements regarding energy saving in buildings. Hospitals are great consumers of energy, both electrical and thermal: the use of heating and cooling equipment for maintaining satisfactory comfort and indoor air quality for the patients as well as the adoption of several electrical health equipments result in the highest energy consumption per unit floor area of the entire building sector. Moreover, the potential advantages to simultaneously meet electrical, thermal and cooling demand are concerned not only in higher final use efficiencies (compared to the separate production), with consequent reduction of pollutant and green house gases emissions, but also in promoting the use of alternative technologies. In the present study, a CHP plant for a hospital facility with 600 beds has been considered. More specifically, after the presentation of the hospital’s energy consumption, the optimal plant configuration (sizing of all cogeneration units) has been outlined by means of a numerical code (Trigen 3.0) in-house developed. Afterwards, in order to optimize the load distribution in a smart grid characterized by electrical, thermal, cooling and fuel energy fluxes, an ulterior numerical investigation has been performed. The software, named EGO (Energy Grids Optimizer) consists of a genetic algorithm procedure: it is able to define the optimal load distribution of a number of energy systems operating into a smart grid based on the minimization of an objective function which expresses the total cost of energy production. Finally, the results have demonstrated that the optimal plant and grid configuration, associated to the indication of the operation time and load status of each device, proved to be fully dependent on economical profitably aspects.
Proceedings SET Conference 2017, Bologna
1
10
Ancona, M. A.; Bianchi, M.; Biserni, C.; Melino, F.; Salvigni, S.; Valdiserri, P.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/615032
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