Modelling of solar systems
The proper sizing of the components of a solar system is a complex problem which includes both predictable (collector and other components performance characteristics) and unpredictable (weather data) components. In this section an overview of the simulation techniques and programs suitable for solar heating and cooling systems is presented.
Computer modelling of thermal systems presents many advantages the most important of which are the following :
1. Eliminate the expense of building prototypes.
2. Complex systems are organised in an understandable format.
3. Provide thorough understanding of system operation and component interactions.
4. It is possible to optimise the system components.
5. Estimate the amount of energy delivery from the system.
6. Provide temperature variations of the system.
7. Estimate the design variable changes on system performance by using the same weather conditions.
The initial step in modelling a system is the derivation of a structure to be used to represent the system. It will become
apparent that there is no unique way of representing a given system. Since the way the system is represented often strongly suggests specific modelling approaches, the possibility of using alternative system structures should be left open while the modelling approach selection is being made. The structure that represents the system should not be confused with the real system. The structure will always be an imperfect copy of reality. However, the act of developing a system structure and the structure itself will foster an understanding of the real system. In developing a structure to represent a system, system boundaries consistent with the problem being analysed are first established. This is accomplished by specifying what items, processes, and effects are internal to the system and what items, processes, and effects are external.
Simplified analysis methods have advantages of computational speed, low cost, rapid turnaround, which is especially important during iterative design phases, and easy of use by persons with little technical experience. Disadvantages include limited flexibility for design optimisation, lack of control over assumptions, and a limited selection of systems that can be analysed. Thus, if the system application, configuration, or load characteristics under consideration are significantly non-standard, a detailed computer simulation may be required to achieve accurate results. The following sections describe briefly four software programs TRNSYS, WATSUN, Polysun and F-Chart as well as artificial neural networks applied in solar energy systems modelling and prediction.