Dynamic Model of BIPV System for Performance Prediction

The intermittent property of photovoltaic (PV) system requires some sort of energy storage or supplement to supply the similarly intermittent load demand. It can be achieved by connecting the PV generated electricity to the utility grid, or by energy storage device like battery. Either of these means would, to certain extent, affect the electrical network stability if not designed properly. An accurate supply and load forecast would also be a useful tool in ensuring the system stability and reliability when the supply and load can be predicted with higher accuracy. Furthermore, artificial intelligence could play an important role here when the controllable supply and loads can be regulated to promote energy efficiency and system stability. With the precise knowledge of the efficiency characteristics of different PV technologies, including those newly commercialised ones, the simulation of dynamic model of energy output from a building integrated photovoltaic (BIPV) system can be achieved as an indispensable part of the building energy management system (BEMS) in providing necessary control mechanism for the energy demand within the building. When the effect of exposure to weather on the system performance is considered as well, the dynamic model shall be able to adjust itself over time when the system components are degrading and the weather patterns changing. This concept of feedback loop is adopted as the basis of the dynamic model to realize its adaptive ability to learn through previous experience