According to the approach presented in section 3.2.1.ii above, ‘an AI system intended to be used in the management and operation of supply of electricity’ refers to an AI system intended to be used in an asset, a facility, equipment, a network, or an system or a part of an asset, a facility, equipment, a network or a system which is necessary for the provision of the essential services established in point (a) of Article 2(1) CER Delegated Regulation. This includes29:
- the supply of electricity (electricity undertakings);
- the operation, maintenance and development of an electricity distribution system (distribution system operators);
- the operation, maintenance and development of an electricity transmission system (transmission system operators);
- the generation of electricity (producers);
- the nominated electricity market operator service (nominated electricity market operators);
- the demand response (electricity market participants);
- the aggregation of electricity (electricity market participants);
- the energy storage (electricity market participants).
An AI system used in the management and operation of supply of electricity should be considered high risk if intended to be used by an electricity entity (i.e.: electricity supply undertaking, distribution or transmission operator, electricity producer, nominated electricity market operator or electricity market participant) that has been identified by a Member State as a critical entity under the CER Directive.
A specific consideration is needed in relation to AI systems used as safety components in nuclear energy production. Recital 5 CER Directive delineates the scope within the energy sector, acknowledging that electricity generation may include electricity transmission parts of nuclear power plants, but excludes nuclear-specific elements covered by treaties and Union law, including relevant Union legal acts concerning nuclear power.
For this reason, AI systems used as safety components in nuclear energy production do not fall within the high use case listed in point (2) ofAnnex III. AI systems deployed within nuclear power plants are not covered by the critical infrastructure use case , while AI systems used as safety components in electricity components of nuclear power plants could be included.
a) Practical examples of an AI system falling within the high-risk use case of the supply of electricity
An AI system used in a surveillance and protection for physical perimeter protection such as camera systems, radar systems and drone control systems used to directly protect the physical integrity of the infrastructure. An AI system used for the detection of anomalies in data patterns when operating electricity grids for the purpose of monitoring and supporting decision-making in relation to critical functions, such as power load distribution, grid stability, or shutdown procedures.
b) Practical examples of AI systems falling outside the high-risk use case of the supply of electricity
- An AI system used for electricity grid optimization by forecasting the energy demand. The core safety functions are handled separately, so that the system cannot be considered to have a direct safety function.
- An AI system used in a cybersecurity monitoring for energy grid networks. Such a system is intended to be used solely for cybersecurity purposes. Itcontinuously monitors network traffic, detects anomalous patterns, and identifies potential cyber threats across electricity grid communication networks. It analyses data flows, identifies suspicious activities, and alerts security personnel to potential intrusions or malware. It operates independently from operational technology systems that directly control physical grid operations.
- An AI system used as a quality assurance of meter installation. Such an AI system analyses the images of installed electricity meters. The output of the system is provided to the human worker with recommendations regarding errors and improvements. It does not have a direct safety function.
- An AI system used as an incident detection for e.g. precautionary outage prevention. The output is the detection of anomalies and the prediction of impending outages or incidents . In order to prevent them from happening the AI system is sending the grid control centre a warning of the detected or foreseen incident as part of a range of safety measures. The grid control centre operator can then take precautionary measures like switching loads to prevent an outage. Such AI system is not considered as a high risk due to lack of a direct safety function as it is only one measure that is precautionary in nature and not essential for the safe operation of the system . It does not act on itself but rather only enriches the decision-making options in the grid control centre. Even if the system wrongly indicates impending outages or incidents, no outage is created.
- An AI system used for detection and analysing anomalies in data provided from operating the power grid, where the output e.g. is the basis for future improvements in operating the power grid. An AI system that is used for detection of anomalies in data patterns when operating electricity grids so that they are checked by the human operator exists to enrich the decision-making process. It lacks a direct safety function.
- An AI system used for providing recommendations as an assistant, predicting energy consumption at transmission, regional or local level. Such an AI system lacks a direct safety function.
- An AI-system, supervised by a human worker, makes forecasts for grid imbalances, e.g. 15- minutes interval. That forecasts support operational planning, but also directlyinfluence market players. A malfunctioning in the AI-system could mislead both external and internal actors, potentially causing suboptimal dispatch or hedging strategies. This can affect grid stability, which can lead to malfunctioning in electricity supply. This will not be classified as a high-risk system due to lack of a direct link between the system and potential harm.
- The supply of electricity use case does not include the hydrogen sector as defined in Annex III point 1c of the CER Directive (operators of hydrogen production, storage and transmission).