How EDF uses BlueGen. ai to improve predictions, create new commercial opportunities, and simultaneously protect privacy.
The global energy transition is changing the way we produce and use energy. However, renewable energy and the shift to electricity are putting additional pressure on the power grid.
EDF (Électricité de France) is Europe’s largest energy company. The state-owned company is active in all areas: from production to supply. In 2021, EDF had a turnover of 85 billion euros. The liberalization of the internal electricity and gas market has created more competition in France. Grid operators have been separated from energy suppliers, leading to free access to consumers. This has encouraged electricity providers to offer innovative services based on grid load. Other drivers of this innovation include recent crises: COVID-19, inflation due to geopolitical tensions, and technical issues in the production park.
How does EDF still obtain the necessary insights?
Making accurate predictions, customer segmentations, and propositions are highly data-intensive processes. Essential customer data, including that from smart meters and customer characteristics, are subject to the European privacy law GDPR. EDF is only allowed to retain this data for two years. This makes it impossible to retrieve energy consumption data over a longer period, such as during a very cold winter or an extremely hot summer. EDF sought a way to still obtain the necessary insights. Prediction is important for aligning supply and demand. In addition, analyses make it possible to segment customers based on consumption in order to then make appropriate commercial offers.
AI platform for synthetic data
With BlueGen.ai’s synthetic data platform, EDF is able to generate 100% privacy-safe data. Using artificial intelligence (AI), the BlueGen.ai platform creates synthetic data that looks and behaves just like the underlying real data. They are suitable for valuable data analysis without the limitations imposed by privacy regulations. As a result, the French energy company can still make accurate predictions of energy demand and align its supply accordingly. EDF is now able to generate detailed data sets based on gas heating, including synthetic time series for an entire year and what-if scenarios. With these scenarios, the company can compile consumption data. For example, what does it mean if there are ten percent more electric cars on the road? Or if it’s five degrees colder or warmer?
Improved prediction and understanding of consumer needs
Synthesized data ensures both privacy and security. EDF data experts now have the ability to use data for research, analysis, and predictions. This makes it possible to create load profiles based on privacy-sensitive data from smart meters. With synthesized data, EDF can train machine learning models. This allows the energy company to make detailed predictions, better understand its customers, and formulate an optimal customer proposition. Because synthetic data is completely privacy-proof, EDF data experts are allowed to retain this data for longer than two years. In doing so, they are also able to account for existing segmentations and increase the model’s accuracy.
"BlueGen.ai enables EDF to develop innovative commercial offers and predictions using synthetic customer data, while ensuring privacy with a secure solution."
Better predictions of energy consumption
Developing new innovative services
Safeguarding privacy