In recent years, the governments of most nations have pledged to (i) limit carbon dioxide emissions, (ii) reduce primary energy consumption by increasing production, distribution and end-use efficiency and (iii) increase the utilization of renewable energy sources. In general, these goals are pursued separately by law, by subsidizing renewable en ergy technologies, reducing the demand or using high efficiency technologies. In this context, multi-source systems for the fulfillment of energy demands are highly advantageous because they are based on different technologies which use renewable, partially renewable and fossil energy sources. However, the main issues of multi-source systems are (i) the allocation strategy of the energy demands among the various technologies and (ii) the proper sizing of each technology. For this purpose, a model, which takes into consideration the load profiles for electricity, heating and cooling for a whole year is developed and implemented in the Matlab® environment. The performance of the energy systems are modeled through a systemic approach. The concurrent optimization of the size and switch-on priority of the different technologies composing the multi-source energy plant is performed by using a genetic algorithm, with the goal of minimizing the primary energy consumption only. Moreover, a minimization of the net present value is performed in the Italian scenario by considering the cost of technologies and, in particular, the current tariffs and incentives. The optimization model is applied to a thirteen-floor tower composed of a two-floor shopping mall at ground level and eleven floors used as offices.
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