Accelerate the energy transition with congestion management and energy efficiency

Making data from smart meters available in a privacy-safe manner

To mitigate climate change, a transition to sustainable energy is currently underway. It involves a structural change in energy supply and consumption. This transition presents opportunities for existing organizations as well as for providers of new services.

Are you an energy supplier, grid operator, or independent service provider (ISP)? For example, a provider of metering services that distributes data on the use of electricity and gas? Then you are among the players who are part of the smart grid. This smart metering and control system ensures that energy peaks and valleys are managed properly.

Supply and demand imbalance

Due to the energy transition, the demand for electricity is rapidly increasing. The growth of solar and wind energy is meant to meet this demand, but due to the significant increase in these sustainable forms of energy, the power grid is becoming overloaded in more and more areas. As a result, supply and demand are not in balance, ultimately leading to congestion.

Predictive computational models

Computational models provide insight into energy needs. However, the performance of such predictive computational models heavily relies on the quantity and quality of available data. Collecting this data, such as from smart meters in households, is rather challenging. It involves privacy-sensitive information. Legally (think of the GDPR), there are restrictions and regulations to adhere to.

Synthetic data and AI

Here’s where synthetic data combined with AI comes into play. But what exactly is synthetic data? It makes it possible to extract the value of personal data without using or leaking privacy-sensitive information. Allow me to give an example. Suppose you want to post a photo of a person on your website. You cannot simply use an existing person’s photo, as it could violate their privacy. However, if you use a synthetically generated photo, you can safely use it on your website without compromising privacy. Such a photo has the same characteristic features and is often indistinguishable from real ones. This image cannot be traced back to an existing person. See the photos below.

Which photos are fake and which are real?

These photos are all from the site https://thispersondoesnotexist.com/

Application in energy consumption
This technology can also be applied to energy consumption from smart meters in households. You can create a synthetic version of the consumption that contains the same characteristics and patterns but cannot be traced to an individual connection. This data can then be used for various purposes such as analysis or training machine learning models, including predicting energy needs or profiling customers.

Feeding information models
The data that feeds and trains your information models is completely privacy-proof. The resulting data model cannot be reversed to identify individuals. There is no direct information available. This therefore ensures compliance with the strict privacy requirements of regulatory parties such as Energy Data Service Nederland (EDSN).

Using AI to extract insights from your data
With Artificial Intelligence (AI), you can use proven algorithms to generate truly new datasets. You can safely store, study, or even condition such a dataset to work out what-if scenarios. One of the possibilities is to use synthetic data to better predict the demand for energy by taking variables such as temperature change into account. But you can also examine the effect of a significant increase in the number of charging points for electric vehicles or a substantial rise in the number of households that have air conditioning or other forms of climate control. With the AI-based platform of BlueGen.AI, you can generate new scenarios, giving you insight into solutions even before problems arise.

 

Data factory of the future
Because synthetic data is flexible and can be shared, the BlueGen.AI platform can derive useful and anonymous results from it much faster than from a conventional database. The information you gather holds value: both for yourself and others. Your own company can use this data to create new products and price levels. You can offer aggregated data to customers who want to know how to better utilize their resources. In short, as an energy supplier, grid operator, or independent service provider (ISP), you become the data factory of the future.

If the concept of synthetic data using AI is new to you, I recommend conducting further research and contacting us by phone or e-mail. At the very least, you should be aware of it because synthetic data is here to stay.

Share this article: