To gain necessary insights into the power grid and the energy consumption of the companies at the harbor, EFFORT will collect measurement data from the industry's electricity, heat, and water consumption, as well as local production. The data collection is done through the setup of a cloud-based data hub, which constitutes the seventh and final use case in EFFORT. The data hub is built based on general principles regarding:

·         Data collection

·         Data storage,

·         Data sharing,

·         Data security,

·         Scalability,

·         and analysis.

 

What will EFFORT achieve with the use case?

Through the data hub, energy-related data can be collected across energy sectors. When data is gathered from different sources in one data hub, it opens opportunities to use the data in new ways. Users can also access a necessary data foundation through a central source.

By collecting company data through a data hub, EFFORT can create the foundation for companies to make data-driven decisions, which can optimize their energy consumption and reduce their costs. By collecting and analyzing data from the power grid, patterns of energy transport can be identified and optimized in the actual composition of energy consumption and production in the system.

Another central aspect is the data hub's contribution to optimizing the harbor's and the companies' use of renewable energy.

 

How will EFFORT work with the use case?

Data will be collected from the DSO segment (use case 1 [link]) and from the companies at the harbor (use cases 2-6 [link]). To build the data hub that will collect this data, existing data from the Port of Hirtshals is identified, as well as the development path for the data hub using Danish Technological Institute’s EnergyFlexLab.

In EFFORT, there is a focus on the electricity distribution network, and the primary points of interest for utility company data are:

·         The overall energy flows in the distribution networks,

·         Identification of passive/active components in the system,

·         And value parameters defined for simulation purposes.

 

For the companies, the primary points of interest for the data are:

·         The overall energy flows to/from the company,

·         Identification of systems/processes that consume/produce energy,

·         And flexibility insights into systems/processes.

 

This necessary data is collected through the data hub, stored, and used for the development of digital twin models that enable the calculation of flexibility and optimization of renewable energy consumption at the harbor and by the companies.

Measurement indicators for the use case

To assess the quality of the data and the functionality of the data hub, various set indicators are measured. The indicators are:

•        Data hub availability (uptime measured in %)

•        Data ingestion rate ("MB per second" and/or "sample rate x sampled data points")

•        Evaluation of bottlenecks (capacity for data ingestion rate/actual ingestion rate), target >= 1

•        Data processing time from data being available at the source to being ingested in the data pool (seconds per "data transfer")

•        Data processing time from data being requested by the consumer to being made available for transfer (seconds per "data transfer")

•        Processing time from data being available to control proposals being available (seconds per control) for evaluating the system control readiness (requirements for control loop/process time data hub), target >= 1

•        Latency from data source to end consumer (seconds per "data transfer")