
The application helps optimise the development and management of energy distribution networks based on data analytics.
TAURON Dystrybucja provides electricity for 5.6 million customers.
The company is part of TAURON Holding and the largest distribution system operator in Poland, distributing 50 TWh of energy in the area of 57,940 km2.
In search of innovative solutions, TAURON Dystrybucja takes part in research and development activities and implements new technologies, focusing on smart grid technologies.

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Data management
TAURON Dystrybucja searched for a partner to carry out a project which consisted of designing, building, testing, and implementing a system that enabled advanced analytics for large sets of data gathered on the basis of smart metering infrastructure to support the business processes of the DSOs.
The first stage of the project was the installation of 400,000 smart meters (AMI) in the area of Smart City Wrocław. The objective of the applied solutions was to ensure scalability and flexible architecture.
The implementation was crucial in the context of the planned mass operations regarding the AMI meters.
Scope of work
Project Management
Business Analysis
Quality Assurance
Big Data
Cloud
Machine Learning
IT Security
The application can be accessed by means of a graphical user interface presenting the processed data. This allowed us to create more advanced queries and algorithms that operated on complete data sets or their elements.
The project was implemented in close collaboration between TAURON Dystrybucja and Future Processing (getFlow) and with the support of universities: Częstochowa University of Technology and Opole University of Technology.

We faced the following challenges:
Data Integrity
ensuring data integrity for various sources: CBP, ZMS
Project's contexts
various contexts of the project (The National Centre for Research and Development, product, security, universities, project team)
Optimisation
optimisation of the cloud services in order to maintain cost effectiveness

In our cooperation, Future Processing displayed great professionalism, flexibility, involvement, and understanding of the DSO business processes, including the challenges that occur on the road towards digital transformation as well as newly emerged legal requirements. We highly value the quality of their work, their organisational culture, and the engagement of their team. We can recommend Future Processing as a reliable, trustworthy, and professional company and a great partner for the energy sector.
Revolutionary solutions

To increase the efficiency of detecting illegal energy consumption, we implemented state-of-the-art technologies of machine learning and balancing that allowed identifying places suspected of illegal energy consumption. In the module concerning illegal energy consumption, two tools were used: a chart and thematic maps.
One of the key benefits of the project was the possibility of testing the developed solution in real-life conditions, before the planned process of implementing smart remote meters in Poland.
By 31 December 2028, the company intends to have smart meters installed at homes of at least 80% of end-users (i.e. around 14 million meters).
GridFlow by Future Processing – a unique solution created for TAURON Dystrybucja based on innovative technologies and perfectly suited to the client’s needs. For the DSOs that undergo digital transformation, GridFlow is a solution that helps to ensure the safety of the electrical grid through high-quality data analytics.

Implementation in Wrocław
In partnership with TAURON Dystrybucja, we successfully deployed the application in Smart City Wrocław. The goal of that implementation was to check the benefits of GridFlow to the DSOs. It served as the first milestone in the company-wide deployment.
We proved that advanced analytics of low-voltage grids increased the transparency of daily operations, optimised the infrastructure management, enhanced safety and stability of energy supply, and lowered the sales losses.
440,000
AMI measurement point
35 mln
daily readings
1 TB
monthly data increase
1.1 bln
readings per month
Modules we delivered together
- Smart meters – validation and advanced analysis in terms of the ways of supporting various DSO processes
- Balancing meters – correlating data collected from AMI and balancing electricity meters installed at low- and medium-voltage grid stations for advanced data analytics
- Reactive energy – analysis of the influence of reactive energy flow on active energy losses in low-voltage grids, supervision of the grid efficiency and the use of the existing grid
- SAIDI & SAIFI – automated calculation of quality indexes and better control of permissible energy supply breaks
- Load models – identifying daily load models for different customer groups, improved planning of grid expansions, and performing load simulations for target groups
- Illegal electrical energy consumption – identifying power delivery points suspected of electricity theft based on data collected from AMI and balancing electricity meters
- Simultaneity factor (kj) and simulations – automated calculation of the simultaneity factor (kj) for the existing structure of the electricity grid and the possibility of simulating the factor and the transformer load in the designed lowand medium-voltage grid stations

Specialists in the industry
The team consisted of specialists in a variety of subjects. The main members on Future Processing’s side were getFlow specialists – experts in the field of electricity, water resources, and IT, who understand both the industry and the client’s business goal and deliver products and services which support their performance and development.
The size of the team was adapted to the current situation in the project.
The system implemented for TAURON Dystrybucja will provide its users with easier access to processed and aggregate data from our AMI structure and with visual presentation of measurements and technical information on graphs and infrastructure maps. The data will enable our engineering teams to increase their efficiency and the safety of the infrastructure.
Thanks to this, GridFlow will help us meet the highest standards of electricity supply to our end users. It will also allow us to optimise our future investments and maintenance works on the network infrastructure. Additionally, GridFlow will support our engineers with identifying places suspected of illegal energy consumption, which will directly reduce our commercial losses by detecting and eliminating such events.
Main benefits of our partnership
The application delivered by us made it possible to:
- facilitate business processes thanks to smart meters collecting data about the status and activity of the distribution grid, loads, and other events,
- better analyse the data collected from meters for micro-installations,
- achieve the top level of functionality for solutions combining smart meters with communication technologies to enable the use of measurement data for the DSO business processes,
- minimise trading losses, decrease the number of technical failures, and reduce the costs of analytics and simulations by lowering the technical losses in low-voltage grids,
- accelerate the detection of illegal energy consumption, provide customers with the possibility of regular access to the information about their energy use, and automate calculations and simulations,
- streamline customer service, e.g. quickly verify complaints concerning measurement data and energy quality parameters to support the process of issuing the requirements for connection to the distribution grid,
- have a positive impact on the environment by improving energy efficiency, reducing technical and trading losses, and optimising the workload of the network.
The introduced solution increased transparency to optimise low- and medium-voltage grid management by analysing data collected from smart meters, balancing meters, dispatch systems, and grid assets. The tool combines the newest technological solutions, advanced algorithms, and domain knowledge. It referred to cost efficiency, safety and stability, optimisation and streamlined investments.
Some screens of the solution

Analysis of the changes in the distribution of probability density
The probability density distribution shows the variability of energy demand (vertical distribution) and the probability of energy demand at a given level.

Low- and medium-voltage transformer overload
The graph presents data for individual low- and medium-voltage transformers. The high kj simultaneity factor alongside the long o verloads and numerous energy breaks at low- and medium voltage stations may support the decision to renovate or modify the network.

Average loads calculated on the basis of real-world data
The graph shows average loads calculated on the basis of real-world data, which serves as a basis for defining the load models in the load module.
Used in the project
Visualise data, design and create a solution
Process data effectively, base new services and business decisions on knowledge and improve your day-to-day operations.






