Contingency Analysis for a Solar Energy Generation System Using Real-Time Data Analysis

Owing to being environment friendly, having a decrement in the amount of greenhouse emissions from fossil fuels, increment in the reliability of the current system, application and adoption of renewable energy systems has been escalating in electric generation systems. The major concern arises due to different faults occurring in the electric power system. The presence of certain harmonic contents and abnormalities can lead to major faults occurring in the power system, thereby causing an interruption in the distribution system of the grid. This greatly sways the efficiency of the electric power grid system. To address this challenge is the key to conducting contingency analysis. Numerous techniques have been enacted upon for identifying and truncating the occurrence of fault, thereby increasing the efficiency. This paper presents an overview of contingency analysis and the challenges faced in the field of renewable energy generation system. This paper focuses on analysis of solar energy generation system using real-time data which has been visualized on Google Colab platform using the Exploratory Data Analysis technique of machine learning. Thereafter, the results are taken into account to identify the possible contingencies that would be present in the solar energy generation system. Furthermore, challenges in renewable energy contingency analysis and an effective method to reduce the occurrence of contingency in the generation system have been proposed in this paper.