Optimization of integrated CCHP and solar plants following a multi-objective approach. An application to the household sector

Yıl 2014, Cilt: 4 Sayı: 2, 453 - 463, 01.06.2014

Valentina Panone Michele Anatone

Öz

Integrated Energy Systems for buildings constitute one of the most strategic solution for achieving the current objectives in the energy sector. Integration broadens the possibilities for the diffusion of district heating and cooling systems, for a wider Renewable Energy Sources exploitation, for the waste heat recovery and for the energy storage. Moreover, integrated systems can include cogeneration, certainly leading to primary energy needs and to CO2 emissions reduction but low carbon technologies imply relevant investments and an optimal solution for this trade-off behaviour has to be defined. With this aim, a combined cooling heating and power system, based on an internal combustion engine and on an absorption heat pump, integrated to a solar collectors plant through a thermal energy storage, has been studied and applied to a group of apartments requiring heating, domestic hot water, cooling and electrical energy. A tailored model has been developed, able to optimize the system considering its peculiarities in a more easy and immediate way compared to the models available in literature, generally designed to study large-scale systems. Two different configurations have been studied: in the first the absorption heat pump is fed, during the warmer months, directly by the high temperature engine exhaust gases; in the second it’s fed by the storage tank all the year. The procedure results are the optimal sizes of the devices (engine, solar plant, and, for the latter case, also the absorption heat pump) and the trade-off fronts, which show a greater convenience for the second case, where a stronger integration among the various devices is achieved and mean annual costs and CO2 emissions reduction of 25% and 35%, respectively, are obtained.

Anahtar Kelimeler

CCHP; Thermal solar plants; Systems Integration; Multi-objective Optimization; Thermal Energy Storage.