Research and innovation projects

At NODA we strive to innovate and push the boundaries of the state-of-the-art. These are some examples of our research projects.

Flexi-Sync

Flexi-Sync (Flexible energy system integration using concept development, demonstration and replication) aims to optimize the flexibility in the district energy sector, a sector with untapped potential to balance the energy system. The project gathers 16 partners from four EU Member States: Austria, Germany, Spain and Sweden. Six demo sites in the countries will participate.

Flexi-Sync is funded by ERA-Net Smart Energy Systems.

TEMPO – Temperature Optimisation for Low Temperature District Heating across Europe

The TEMPO project develops technical innovations that enables district heating networks to operate at lower temperatures. By decreasing the temperature in the systems, it reduces heat losses and allows a higher share of renewable and excess heat to be used as heat sources. The use of these heat sources will be crucial to adapt current district heating systems and create new ones suitable for a sustainable energy system.

BigData@BTH

Data will be generated at an ever-increasing rate for the foreseeable future. Added value and cost savings can be obtained by analysing big data streams. The analysis of large data sets requires scalable and high-performance computer systems. In order to stay competitive and to reduce consumption of energy and other resources, the next generation systems for scalable big data analytics need to be more resource-efficient. The research profile, Scalable resource-efficient systems for big data analytics, combines existing expertise in machine learning, data mining, and computer engineering to create new knowledge in the area of scalable resource-efficient systems for big data analytics. The value of the new knowledge will be demonstrated and evaluated in two application areas (decision support systems and image processing).

BigData@BTH is funded by the Knowledge Foundation.

DAD – data analytics for fault detection in district heating

The purpose of DAD is to, together with industry partners, apply, improve and develop new methods and algorithms for predictive data analytics in order to increase energy efficiency in heating systems via fault monitoring, detection and prediction activities. Scientifically, the project targets several of the most dynamic areas in machine learning and data analytics – e.g., deep learning, anomaly detection, imbalanced learning, interpretability, prediction with confidence and concept drift, and loss function optimization – in order to address the problem of how to automatically monitor, detect and predict faults in a district heating system (DHS) using sensor data collected from DHS substations, e.g., data collected with Individual Metering and Debiting sensors.

DAD is funded by the Swedish Knowledge Foundation.

SHINE – a smart home in a smart grid

In this project, NODA and Malmö University together with leading industrial actors used state-of-the-art IoT technologies to tie the smart home together with the intelligent energy system. A platform for a decentralized cyber-physical system with intelligent control for automated handling of heating and cooling in buildings in relation to system-wide constraints in the energy system was developed. The system provides increased user empowerment through the use of individual climate zones while providing benefits for the utility and building owners on a system scale.

SHINE was funded by Vinnova, NODA and Karlshamn Energi.

STORM

The project tackled energy efficiency at district level by developing an innovative district heating & cooling (DHC) network controller. The project partners have developed a controller based on self-learning algorithms, which has been evaluated in the two STORM demo sites. The developed controller is used to maximize the use of waste heat and renewable energy sources in DHC networks.

STORM was funded as part of EU Horizon 2020.

Flexible Heat and Power (FHP)

The inertia of power to heat solutions constitutes an enormous potential for electric and thermal flexibility. The thermal inertia of buildings and thermal storage holds a lot of flexibility. Heat pumps, central heating and cooling installations, and forced ventilation systems act as interfaces connecting the thermal storage and inertia to the electrical distribution grid.

FHP as funded as part of EU Horizon 2020.

Arrowhead

The Arrowhead project targeted five business domains; Production (process and manufacturing), Smart Buildings and infrastructures, Electro mobility, Energy production and Virtual Markets of Energy. In these domains there is a number of technological architectures used for implementing SOA solutions. One of the grand challenges of Arrowhead was to enable interoperability between systems that are natively based on different technologies. Arrowhead had a budget of about 70 MEUR and nearly 80 partners from 15 different countries

Arrowhead was funded as an Artemis Innovation Pilot Project.