Optimal sizing of a multi-source energy plant for power heat and cooling generation

Multi-source systems for the fulfilment of electric, thermal and cooling demand of a building can be based on different technologies (e.g. solar photovoltaic, solar heating, cogeneration, heat pump, absorption chiller) which use renewable, partially renewable and fossil energy sources. Therefore, one of the main issues of these kinds of multi-source systems is to find the appropriate size of each technology. Moreover, building energy demands depend on the climate in which the building is located and on the characteristics of the building envelope, which also influence the optimal sizing. This paper presents an analysis of the effect of different climatic scenarios on the multi-source energy plant sizing. For this purpose a model has been developed and has been implemented in the Matlab^® environment. The model takes into consideration the load profiles for electricity, heating and cooling for a whole year. The performance of the energy systems are modelled through a systemic approach. The optimal sizing of the different technologies composing the multi-source energy plant is investigated by using a genetic algorithm, with the goal of minimizing the primary energy consumption only, since the cost of technologies and, in particular, the actual tariff and incentive scenarios depend on the specific country. Moreover economic considerations may lead to inadequate solutions in terms of primary energy consumption. As a case study, the Sino-Italian Green Energy Laboratory of the Shanghai Jiao Tong University has been hypothetically located in five cities in different climatic zones. The load profiles are calculated by means of a TRNSYS^® model. Results show that the optimal load allocation and component sizing are strictly related to climatic data (e.g. external air temperature and solar radiation)