Big Data and IoT System for Utility Power Planning using Commercial Cloud Database

Utility providers face power planning challenges regarding energy efficiency and managing electricity generation based on consumer peak demand patterns. Smart homes and smart meters provide Big Data that can assist in mitigating these issues. However, to perform large scale analytics utility providers require vast computing and storage resources. Cloud service provider services such as cloud storage and cloud analytics are viable options that facilitate accessible, saleable, relatively low cost and highly available operations for utility services. This work discusses the efficacy of the two leading cloud service providers to evaluate the performance in big data read and writes, as well as on the performance of the data analysis within the context of utility power planning. The work also implements a solution for a smart home system to integrate with the cloud platform for storing generated data and forecasting peak demand predictions using platform specific tools. The forecasting models are compared to custom baseline models to benchmark the performance of the cloud platform models. The results of this work show that cloud platforms are viable alternatives for utility provider big data storage and analysis and enhances on the power planning capabilities.