Grants awarded for Energy System Integration & Big Data

19 January 2018

NWO has awarded grants to six projects in the ‘Energy System Integration & Big Data’ round. Approximately 3.85 million euros has been made available by NWO’s Science domain and by its Applied and Engineering Sciences domain. In addition, one or more public/private parties will be participating in each project, each contributing 15% in cash and 15% in kind, on top of the NWO funding. Using this combined funding, researchers will be appointed to Dutch knowledge institutes. The call, which was drawn up in cooperation with Commit2Data, is part of NWO’s work programme for the Energy Top Sector.

The grants are awarded to projects focusing on the development of a new, sustainable energy system featuring coordinated upgrades to electricity, gas and cooling/heating systems. Big Data and the associated analysis techniques are of pivotal importance here.

The following six projects have been awarded grants:

Data at neighbourhood level: central learning or local gossiping
Using small data and big data: Neighborhood Energy & Data Management Integration System
Prof. W. Zeiler, Faculty of Architecture, Eindhoven University of Technology

The integration of decentralized renewable energy will have an impact on the stability of the grid. The building, its installations and users can offer energy flexibility. This requires effective data exchange and analysis. Two different concepts will be used at building level and at neighbourhood level. The central feature involves deep learning while, at local level, ‘gossiping’ algorithms are employed.

Participating institutions and companies: Eindhoven University of Technology, Centre for Work and Income, Municipality of Breda, Enexis (energy network operator), Stichting Promotie Installatie Technologie (Foundation for the Promotion of Plant Technology), Kropman Installatietechniek (engineering company), Stichting Knooppunt Innovatie Elektrotechniek Nederland (The Netherlands Foundation Hub for Innovation in Electrical Engineering), Coöperatie De Dobbelsteen (cooperative for a disused school building), Brede Sociëteit Princenhage (village cooperative).

Intranets for Energy
Energy Intranets
Dr E.J.E.M. Pauwels, Department of Intelligent & Autonomous Systems, Centrum Wiskunde & Informatica (Centre for Mathematics and Computer Science)

Renewable energy from sources such as the sun and the wind contributes to a sustainable world. Technology cannot compensate entirely for the variability of these mostly decentralized energy generation systems, so it’s becoming increasingly difficult to balance the power grid. Based on a specific requirement by the power generation industry, this project will explore the potential of computational intelligence to better predict and utilize the flexibility of supply and demand.

Participating institutions and companies: Centre for Work and Income, Delft University of Technology, Utrecht University, University of Amsterdam, SURFSara (IT facility for Dutch education and research), Sympower (demand response aggregator).

Peer-to-peer energy trading
Enabling peer-to-peer energy trading by leveraging prosumer analytics
Prof. J.G. Slootweg, Faculty of Electrical Engineering, Eindhoven University of Technology

More than 30% of the electricity generated in Organisation for Economic Co-operation and Development (OECD) countries is consumed in homes. That’s why it is vital to involve small consumers in the development of a sustainable energy system. New behind-the-meter technologies (solar panels, storage, etc.) and modern communications infrastructure facilitate direct trade between consumers. This research project focuses on understanding how such trading networks should be set up, how their value can be maximized and what impact they have on the electricity distribution system.

Participating institutions and companies: Eindhoven University of Technology, Delft University of Technology, Enexis, ICT Automatisering Nederland (provider of industrial technology solutions and services), SynerScope (Big Data solutions company).

Using simulations to protect power grids
Resilient Synchro Measurement-based Grid Protection Platform
Dr M.S.E.E. Popov, Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology

The goal of this project is to design a new simulation platform for the power grid. This involves the use of improved measurement methods and Big Data to better detect disruptions, and stop them from spreading. The new disruption-detection algorithms will be validated using real data.

Participating institutions and companies: Delft University of Technology, VSL (Dutch Metrology Institute), General Electric, and the energy network operators TenneT, Alliander, Enduris and Stedin.

Multi-dimensional Big Data modelling to ensure long-term power and heat system adequacy
Multi-dimensional Big Data modelling to ensure long-term power and heat system adequacy
Dr M.A. van den Broek, Faculty of Geosciences, Utrecht University

The large-scale use of renewable energy poses new challenges, due to daily and yearly fluctuations in the weather. Energy network operators use computer models to help them select the best combination of financial and practical measures to tackle these challenges. The goal of this study is to improve these models. For instance, processes in the areas of climate, weather, energy production and energy demand will be collectively analysed through the use of Big Data analysis techniques. This will make it possible to estimate the requirements for a reliable electricity supply under future weather conditions while also making allowance for new trends, such as the electrification of transport and heating.

Participating institutions and companies: Utrecht University, The Royal Netherlands Meteorological Institute and TenneT.

Greenhouses as flexible energy sources
Energy saving in greenhouse crop production by flexible management
Prof. E.J. van Henten, Department of Plant Sciences, Wageningen University & Research

We aim to cut national energy consumption by several percentage points, while also reducing peak load on the power grid. This will require more flexible greenhouse energy management, based on parameters such as crop capacity, meteorological data and supply on the power grid.

Participating institutions and companies: Wageningen University, LTO Glaskracht (horticultural association), Agro Energy (energy company), Delphy (horticultural research and consultancy company), B-Mex (computer modelling company), (data collection and analysis).





Source: NWO