Partial fuzzy grid models and application to condition monitoring of photovoltaic systems

This paper presents a computational strategy for condition monitoring of multi-mode processes on the example of real data from a photovoltaic system. The concept uses a new type of fuzzy models with partially activated set of fuzzy rules on a pre-determined grid, called partial fuzzy grid models. Each such model represents one specific operating condition of the process, which is saved in the Model Base. Then the (unknown) operation data are processed by all of the partial models and produce their own estimations. The model with the best estimation shows the most similar operation to the newly presented one. The novelty in the paper is focused on the concept and the learning algorithm for the partial fuzzy grid models as well as on the calculation steps for the condition monitoring.

I. Introduction (Heading 1)

There are many kinds of processes, which are multi-mode (multi-regime) in nature. Typical examples are the photovoltaic (PV) systems that can operate under different conditions in the different seasons of the year. The following Fig. 1 gives a graphical illustration for two operating modes (in winter and in summer) of a PV system. Figure 1.

Illustration of different operating conditions for a photovoltaic system in winter and summer days