The energy world is changing radically: In the past, electricity was transported from a few power plants to households via "electricity highways". Today there are over 1.7 million decentralized generation plants in Germany alone, which feed green electricity from wind power, solar energy or biogas into the grid via many “small roads”. More and more consumers are becoming producers at the same time, meaning electricity is flowing in both directions.

At some periods of the day, renewable energy plants generate more electricity than is needed. However, when there is no wind or sun, these plants only cover a few percent of demand. To balance out these fluctuations, we need intelligent, innovative solutions and networks in the new energy world that meet the challenges of the energy transition with more flexibility and intelligence.

The demand for electricity will continue to rise in the future due to digitization and new consumers such as electric cars and electric heaters. This will also result in further expansion of green energy systems, so the energy system of the future will be extremely complex.

Dr. Karsten Wildberger

Artificial intelligence (AI) is an important component and driver of the energy transition

Here are a few examples of where we use Artificial Intelligence

AI, for example, can distribute and store energy intelligently, thereby balancing generation and consumption locally. This increases efficiency in the grid and can reduce costs for consumers.

Using AI and so-called meta-forecasts, we can calculate very precisely how much wind will be at a particular wind farm the next day or even in the next few hours. This enables us to react accordingly in advance – both in the event of a shortage of wind energy and in the event of an expected surplus.

We use AI to maximize the energy yield in wind farms: AI manages to synchronize the turbines and align them optimally with the wind.

AI supports the security of supply for our customers and warns of power outages: Using AI, we can calculate when a cable needs to be replaced and intervene before it is actually damaged. This enables us to minimize disruptions and significantly reduce supply interruptions.

Artificial intelligence helps us to better understand our customers. This enables us to better anticipate what is bothering our customers and develop possible solutions before a problem arises. This improves our call-center activities, for example, and increases customer satisfaction. 

Predictive maintenance

We have developed a self-learning algorithm that predicts when medium voltage cables in the electrical grid need to be replaced. The system uses all sorts of data to identify electricity generation behaviour patterns and inconsistencies, including external factors like weather, lightning and salt content. Our research has shown that this intelligent approach can reduce the number of outages in the grid by up to 30% compared to a conventional approach. This results in better security of supply and better network quality for our customers and partners.

Predictive maintenance
E.ON Home

E.ON Home

For private consumers, we can use AI to create consumption overviews that show not only how much energy was consumed, but also by which appliances and at what time. This also allows us to derive potential savings. We also offer consumption comparisons to help customers classify their own consumption levels.

Responsible use of Artificial Intelligence

We want to use Artificial Intelligence to secure the greatest possible benefits for our customers, society and our company. AI will influence all areas of our lives: It will affect the way we live and work. That is why ethics plays an important role in the debate about Artificial Intelligence.

AI certainly also involves risks and therefore requires responsible and ethically correct behavior in its implementation. We have given a great deal of thought to how we can ensure that our data experts not only behave legally correctly in accordance with data protection regulations, but also ethically.

This is why we have pioneered the Oxford-Munich Code of Conduct for professional data scientists together with Oxford University. It is intended to provide guidance not only to our E.ON employees in the form of a practical guide, but also to everyone who supports this code. 

Juan Bernabé-Moreno

The book How Artificial Intelligence is accelerating the Energy Transition, published in cooperation with BDEW, provides a comprehensive overview of E.ON's activities in the field of Artificial Intelligence.

Kerstin Andreae

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