Big data analytics and cloud computing for sustainable building energy efficiency

Currently, big data analytics and cloud computing are emerging practices for sustainable energy systems and efficient energy management. Utilizing building energy usage data is critical for the successful deployment of energy efficiency. This chapter presents the framework of a smart decision support system (SDSS) that integrates smart grid big data analytics and cloud computing for building energy efficiency. The framework is based on a layered architecture that includes smart grid and data collection, an analytics bench, and a web-based portal. A real-world smart metering infrastructure was installed in a residential building for the experiment. The SDSS is expected to accurately identify the building energy consumption patterns and forecasted future energy usage. Moreover, end users can reduce electricity costs by using the system to optimize operation schedules of appliances, lighting systems, and heating, ventilation, and air conditioning. The proposed framework serves as a start-up creation in an application of big data analytics and cloud computing technology for sustainable building energy efficiency.