The German BAFA subsidy is an attractive opportunity for companies to receive financial support for energy-efficient measures. In this article, we answer the most important questions about BAFA Module 3 subsidy so that you can make the most of the funding opportunities.
Electrification and individual circumstances as a cause
Electrification in Brandenburg is in full swing: heat pumps and wallboxes are being installed and charging infrastructure for e-cars is being created. And according to the Federal Network Agency, industry is also facing ever higher electricity requirements as a result of progressive electrification. The network in Oranienburg is struggling with this development and has stopped connecting further energy-intensive consumers (Handelsblatt, 2024). Even though there are sometimes individual circumstances there, the fundamental problem is not unique to Oranienburg. What can we do to deal with this side effect of the energy revolution?
Consumers pay for network expansion
Expanding network capacities is one solution, but it involves immense costs. The extent of network expansion is defined in terms of possible simultaneity by the maximum assumed load in the network, which may only occur in specific, short-term time windows. The costs incurred are then in turn passed on to users in the form of ever higher network charges.
Smart grid as a solution
We imagine the smart grid of the future, for which there is currently no regulation, differently. We support the idea of dynamic network charges. With the right incentives, network utilization by participants (producers, consumers, prosumers) can be better coordinated in real time and potential spikes in the network can be efficiently smoothed out. Dynamic high-load time windows can also achieve this effect. They could be notified in advance to participants, who adjust their power consumption accordingly and together relieve the network. Especially in refrigeration and heating technology, this is due to a intelligent, predictive control possible. At the same time, additional storage and redundancies can be used to bridge time windows.
Implement dynamic network charges and dynamic high-load time windows
But what are the concrete steps to take as a company to adapt to this?
- Combination of all relevant data: Historical and real-time data about internal consumption & processes as well as external data such as signals from the smart grid are collected in a database within 15 minutes.
- Use energy management with AI: Based on the data, AI can make forecasts of consumption and electricity production and create intelligent, individual timetables for its own consumption. At the same time, it automatically controls the systems according to timetables and constantly learns from the new data.
Network congestion such as in Oranienburg could be avoided with a data-based smart grid. Consumers could also reduce their energy costs and increase energy efficiency. In this way, dynamic network charges and high-load time windows could be implemented, which also incentivize consumers to consume electricity that is beneficial to the grid, as it is cost-effective.
Even though that is not yet a reality: The benefits of Energy management with AI companies can already benefit from them today! Feel free to get in touch with us to find out more.