TANDEM: InTelligent Energy DAta MaNagement and Online DEcision Making

The electrification of transportation and industry challenges utilities and grid owners as energy demand rises faster than grid capacity can expand. To address this, TANDEM focuses on enhancing flexibility in energy distribution through efficient big data handling and processing. 

This includes online monitoring to identify bottlenecks, improved forecasting methods for flexibility needs, and economic control applications to optimize flexibility orders. Supported by over a decade of collaboration among academic and industrial experts, TANDEM aims to facilitate informed decision-making in Smart Grids and Advanced Metering Infrastructures.
 
Intelligent Energy Management: effective energy management is crucial for ensuring a sustainable and reliable power supply. In this context, “intelligence” is built on two fundamental pillars: (1) sensing and sharing of data, and (2) processing of that data to extract valuable insights.

The interconnected nature of data sharing and processing: sensing and sharing of data involves collecting real-time information from various sources, such as smart meters, sensors, and other devices within the energy grid. This data can reveal important patterns and trends in energy consumption, generation, and distribution. Once sensed, such data must be shared and communicated effectively among different stakeholders, e.g., households, small and medium-sized enterprises (SMEs), and charging stations for electrified transportation and analyzed to generate actionable insights. This analysis can help identify inefficiencies, predict demand, and optimize energy usage.

TANDEM’s vision: In this context, TANDEM aims to boost data processing in both existing and future AMIs and Smart Grids. The project's primary focus is on energy balancing and storage within multi-actor systems that involve a variety of participants, including households, SMEs, and public transportation charging stations. 

TANDEM seeks to advance state-of-the-art in several key areas:

1) Smart Stream Data Preparation, to automate the selection of crucial data for further analysis, enabling scalable data validation and monitoring, filtering out unnecessary information and focusing on the most relevant data points.

2) Models for Electrification and Renewable Energy: to create models to promote the electrification of various sectors and enhance the integration of renewable energy sources. This includes developing tariffs designed to lower peak loads, encouraging consumers to shift their energy use to off-peak hours, thereby balancing the load on the grid and reducing the need for additional generation capacity.

3) Improved Prognosis Techniques: to establish techniques for better forecasting at multiple levels within the system hierarchy. This encompasses everything from smart meters to electric vehicles and third-party applications. By enhancing prediction capabilities, TANDEM will help energy providers make informed decisions about supply and demand, ultimately leading to a more resilient energy system.

Involved in the project

Vincenzo Gulisano, Romaric Duvignau, and Marina Papatriantafilou, Joris van Rooij, Mariliis Lehtveer

Partners

Chalmers University of Technology, Göteborg Energi

Funders

Chalmers University of Technology, Göteborg Energi, Energimyndigheten