Static security classification and evaluation classifier design in electric power grid with presence of PV power plants using C-4.5

Abstract

Energy suppliers all over the world must expand energy in a way that is secure, clean, affordable, and environmentally responsible. Photovoltaic (PV) has been a competitive renewable-energy source for the power generation mix in the world. With the presence of solar PV technology, this paper proposes C4.5 approach for static security evaluation and classification (SSE). This paper proposes PV generators connected to the grid when bilateral energy transactions with the loads are implemented to see their impacts on the system security. To build a classifier in binary class, the process is divided into four components: data collection, pre-processing and feature selection, comparison of the techniques, best classifier selection and performance evaluation. A comprehensive comparison of four of Decision Tree׳s Algorithms for SSE is conducted. The study is (accomplished using) conducted on IEEE 30 bus system, which comprises 5 PV power generators deliver a total power of 40 MW. Data are generated on (30, 57, 118 and 300) bus IEEE test systems used to train and test the classifiers. Empirically, with the presence of PV power generators, the implementation results indicate that these classifiers have the capability for system security evaluation and classification. Lastly, C4.5 is an efficient and effective approach for real-time evaluation and classification classifier design