Artificial active

Artificial intelligence and energy markets

“With AI providing cutting-edge answers to major challenges in the energy sector, operators are being called upon to pay increasing attention to compliance mechanisms as regulations evolve.”

The crisis in the energy sector is forcing operators to provide effective responses to various challenges: price volatility influenced by geopolitical factors, growth in demand and the need to reduce their environmental impact. In such a complex scenario, artificial intelligence (“AI”) could be an effective way to help find effective solutions. The large-scale application of AI frequently intersects with energetic topics, particularly in terms of the need to make data-driven decisions and ensure instant reactions to ever-changing factors, where learning automatic is in the foreground. It is in this context that technological solutions ranging from so-called “algo-trading” to “smart homes” should be considered, without forgetting intelligent networks and automated processes for optimizing renewable energies.

Smart networks

AI plays a crucial role in the networking of energy consumers and distributors: the increasing decentralization and digitization of networks leads to a growth in the number of active participants and, with it, the difficulty of maintaining the balance of the network. At the same time, the rise of irregular energy sources, such as solar and wind, forces distribution to adapt quickly to floating consumption and vice versa. Smart grids – managed by Distribution Network Operators (“DSOs”) – fall within the scope of medium and low voltage local distribution, transporting not only electricity but also data. The management of the smart grid, from the origin to the final branches, is done by remote control systems that allow consumption metering, real-time monitoring of the infrastructure and energy management at the points of use. individual food. These means of managing the balance between supply and demand direct the evolution of networks towards a “prosumer” key, based on the decentralized energy produced by B2C and B2B customers through photovoltaic solutions and beyond.

AI and commerce

The predictive capabilities of AI have even greater potential in electricity trading. AI facilitates the systematic evaluation of large amounts of historical market or weather data. Moreover, as we have already seen, better forecasts ensure greater grid stability and greater security of supply. On these premises, some AI algorithms are already proving to be smart enough to trade independently (algo trading or oneautomated trading), similar to what has already happened in the financial markets.

AI for home consumption

Consumers, when connected to electrical systems through AI, can contribute to a stable and green grid. Solutions such as smart homes and smart meters already exist, but they are not yet widely used. In a smart home, networked devices react to market prices for electricity and adapt to household usage patterns to save electricity and reduce costs.

What changes with the regulations?

In this scenario, companies using AI systems in the energy market should, from a legal perspective, begin to consider the regulatory requirements related to the systems they use. Indeed, the debate on the use of AI intersects with the legislative progress of the law on Artificial Intelligence, anchored in an ethical and risk-based approach with a specific target: the reliability of AI systems. The approach to AI systems should therefore be based on an assessment of the risks associated with them and consider different compliance mechanisms depending on whether the system is high or low risk.

Alongside compliance, which can prove rather rigid once EU regulations are finalized, operators should also consider EU proposals for other aspects of AI use. In particular, in October 2020, the issue of civil liability was the subject of a resolution of the European Parliament, where a draft regulation for the AI ​​sector was prepared. The project, which proposed to introduce an objective liability mechanism for players operating on high-risk systems, was the subject of a public consultation and has not yet been transposed into a binding text.

Given this uncertainty, operators in the energy sector, whether traders, resellers or professional users, are called upon to pay increasing attention to the issue of AI in order to exploit its advantages to the maximum. Above all, it will be essential to put internal compliance mechanisms in place well in advance to comply with future provisions and avoid bans or limits on AI systems that could penalize their business against potential competitors.