A clustering-based preprocessing on feeder power in presence of photovoltaic power plant

The equivalent power of feeder, as one of the inputs of chronological simulation of a power network in presence of a large scale photovoltaic power plant, needs some preprocessing in order to reduce simulation time. The Fuzzy C-means, Gustafson Kessel, K-means and K-medoid methods are applied to find a few numbers of representatives for the equivalent power of feeder. The proposed techniques are validated and optimal number of clusters is found out by means of several clustering validity indices. A comparison with a conventional technique is made on the score of invariant separation index.