In-Memory Real-Time Energy Management
This Bachelor Project is a cooperation between the SAP Innovation Center Potsdam and the Chair of Prof. Hasso Plattner. It focuses on the real-time evaluation and processing of huge amounts of data that arise from smart grids, both for enterprises as well as customers since smart homes and smart industries leverage great possibilities for the existing challenges in the energy business. In-memory column store technology allows us to process the huge amount of data in real time. The state of the art in smart grid architectures, protocols, and data structures have been analyzed and evaluated in relation to a roll-out of the technology throughout Germany. We identify starting points from which we could develop a system that will have an impact on the way energy is managed today and help to realize the energy turnaround proposed by German government. We simulate the German smart grid with 100 million households. Smart meter readings are reported every 15 minutes. This means that we have to process 100 million records in a 15 minutes time frame, which imposes high performance requirements to the underlying database system. Leveraging in-memory technology, column-based databases and massive parallelism will enable us to achieve this goal. The collected data is used for real-time analyses. We can track the energy consumption at the very moment it is being used, calculate the energy costs and make predictions for the future consumption. Answering all those questions at the speed of thought allows more efficient and cost saving real-time energy management. We model existing rates as well as new rates that adjust energy costs every 15 minutes depending on supply and demand. Using the predicted values, we are able to project costs for each rate allowing the customer to constantly contract the cheapest rate.
