A rational use of energy is a key aspect for governments, companies, and individuals all around the world due to social, economic, and environmental reasons. The smart meters that are connected to the smart grids generate an enormous amount of data. This date needs to be stored and processed as fast as possible but also securely and cost-effectively, which is just achievable by means of recently developed big data and cloud computing techniques. The main goal of the ENERLOUD project is to build a platform for the storage, process and analysis of large amounts of data from smart grids by using big data and cloud computing techniques. The ENERLOUD project is focused on creating an innovative platform for the development of a new generation of Smart Grid solutions and services for the integration, management, analysis and diagnosis of energy grid infrastructures. The ENERLOUD project aims to make a relevant contribution to energy saving through IT solutions.
Summary of project results
The main outcome of the project is the development of an interoperability system to optimice the energy consumption within a house, which fulfills the most important goal stablished for the project. The system integrates information from heterogenous sources, such as in-home sensors, open data or advanced metering system of the distribution network, to be able to store, consolidate and process the information to perform a set of recommendations in order to help the inhabitants of the house to consume the energy in a more efficient manner. This result leads to reduce the carbon dioxide footprint, optimice the network system and produce savings and better quality of life to the final consumers and society.
Summary of bilateral results
The partners from donor countries did not achieve to get funding, so their contribution was about knowledge transfer among organizations and support for the project. They helped the Spanish consortium by putting their expertise in the topic at our disposal, as specifications of convenient sensors and the needs about energy optimization in Norway houses. They also collaborated in the data processing and the recommendation system, proposing different alternatives to better achieve the goals of the project.