Prototype of an In-Memory Business Intelligence Solution for the Support of Forecasting of Energy Load Demand

The proposed project aimed at building an environment that would wrap algorithms programs written by our team in SAP HANA to provide easy to use and flexible tool for business entities coming from the energy sector and to enable them to apply different forecasting models, dynamic visualizations and make modifications to existing approaches by introducing new variables or changing the parameters. The additional goal was to evaluate SAP HANA reporting capabilities.

The short synopsis of the project’s main scenario may be presented in a condensed form as follows (The Elevator Pitch style presentation of the main scenario):
FOR: An energy sector analyst
WHO: wants to estimate the forecasts of energy demand and energy generation from renewable energy for an artificially defined area
THE: prototype of an in-memory Business Intelligence solution using SAP HANA and Crystal Reports
IS A: tool that allows for preparing a pre-defined set of forecasting models and reports
UNLIKE: other commercial solutions that enable users to choose only strictly static models that are based only on a small number of variables
OUR PROJECT: enables any energy analyst, without prior programming knowledge, to calculate and compare, in a dynamic manner, various energy forecasts (energy demand and RES generation) for an artificially defined area. The additional goal of the project was to acquire and analyze additional energy data, design and implement new forecasting methods, evaluate efficiency and performance of different computational strategies, as well as examine various reporting capabilities of SAP HANA and Crystal Reports. One of the research hypothesis that we focused on, was that the gathered data, both on the load demand and generation, should make it possible to carry out the market simulations even for the artificially defined area.

External project website: