Abstract
The performances of combined cooling, heating and power (CCHP) system are greatly dependent on its design, operation strategy and thermal and electric demands. This paper illustrates how the use of a genetic algorithm can provide speedy optimization, by applying it to two styles of buildings operated in different operation strategies. The primary energy consumptions of CCHP system following electric demand management (EDM) and thermal demand management (TDM) are firstly analyzed respectively. Then, sixteen hypothetical buildings are constructed to represent various energy demands. Primary energy saving (PES), annual total cost saving (ATCS), and CO2 emission reduction (CO2ER), are weighted to evaluate the integrated performances of CCHP system in comparison to separation production system. Finally, the optimized CCHP system for sixteen scenarios using GA are compared.
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