Histogram Visualization of Smart Grid data using Mapreduce algorithm

This research emphasis the utility of Big Data analytics, as an upcoming trend, in smart grid data. Large datasets are handled using a relatively newer technology called big data analytics. Volume, variety, velocity, veracity, value, and complexity are the six main characteristics of big data. Smart grids have begun to generate tremendous volume of data which is exponentially increasing with the day and possess majority of the big data characteristics. Earlier researches on big data for smart grids has emphasis only on necessities, design, concepts, problems, challenges and further research directions but this work focus on developing solutions for processing the massive data sets. As a study a residential electricity demand profile with 10 million records is considered and the ‘mapreduce’ function in MATLAB is used for dimensionality reduction. Histograms of power consumption pattern with ‘mapreduce’ helps to visualize huge sets of data without the need to load all the observations instantaneously into memory. This will help in further analysis power consumption pattern and predicting the future power demand and short term /long term load forecasting