Digitalization is a key to integrate renewables in electricity systems, to improve reliability and leverage data to get sustainable energy where it needs to be. At the EM-Power Europe Conference 2022 in Munich renowned experts shared their views and experiences in dealing with the challenges of digitalization. In the run-up to the conference, Jean Philippe Poirrier, Head of Department, Smart Grid Solutions, Enedis, answered a few questions about the potentials of digitalization.
How are you embracing digital technologies to integrate renewables?
We offer an array of solutions to integrate renewables faster. First, we make available grid connection portals to assess green energy insertion at a local level. Second, we provide solutions for self-consumption using the potential of Linky, our advanced metering infrastructure (AMI). Third, we are progressively introducing to our high voltage (HV) customers alternative connection offering flexibilities. The next step will be the launching of new flexibility offers for low voltage (LV) customers.
How do you see the role of Machine Learning and AI to optimize the grid?
Machine Learning and AI serve a wide range of use cases within Enedis’ scope of activity, ranging from DER production forecast, grid operations, down to investment prioritization. For instance, one of our major use cases relates to predictive maintenance for LV grid. It is using an AMI-based solution that generates automatic pre-incident intervention recommendations thanks to a learning base enriched by patterns and qualifications made by experts. Furthermore, we are currently testing a similar solution for the HV grid. Climate-related crisis management also involves AI solutions, as our experts already receive incident volume predictions based on weather forecasts.
How do you deal with reliability and security challenges for the grid?
Several tools in use at Enedis can address reliability challenges for our grid. One of the most prominent is an application gathering data collected by sensors or smart meters on the LV grid in order to locate power quality issues experienced by LV customers. As Enedis holds an essential public service responsibility, we ensure a strong protection of our infrastructure, especially our SCADA systems. All of our applications have to comply with high cybersecurity standards defined at the enterprise level to protect sensitive data.
What role does data analytics and forecasting play in your company?
Enedis has implemented data analytics and forecasting tools to assess drafted and generated energy at the primary substation level. Specifically, our in-house tool predicts energy consumption within a day+4 horizon, based on the analysis of the previous week´s consumption. In the near future, forecasts will be estimated almost in real-time thanks to a vast network of connected objects. As for network operation, our digital twin includes a real-time computation model offering localization and description of constraints upcoming within 5 hours.
What new concepts and solutions do you foresee for the future?
We are deeply convinced that our observations of the grid and the way we conduct predictive maintenance will converge. Therefore, new opportunities will appear for AI-based solutions processing qualifications of past events to help future human decisions. For instance, image recognition already allows detecting defaults on overhead HV lines and equipment, enabling an overhaul program ahead of incidents to come.