ABSTRACT

This chapter focuses on the application and analysis of big data in a large-scale power system. Big data can be analyzed for insights that lead to better decisions and strategic business moves. The fundamental challenge of big data is not about collecting data, but about making sense out of it. "Big Data" demand cost-effective, innovative forms of information processing for enhanced insight and decision making. Explosive growth of big data was triggered by widespread adoption of the Internet around the globe. The big data explosion touches every possible business and industry throughout the world. The key goal of using big data analytics is to find out which data source can significantly improve the analytics effort to help solve the problems in health care. The chapter discusses three well-known supervised learning algorithms in detail. These three algorithms are artificial neural network, support vector machine, and decision tree which are widely used for data analysis and classifications in power system problems.