Optimizing energy management in industrial facilities is a complex challenge that implies managing the demand for production and distributed energy resources. However, the latest artificial intelligence technologies (AI) are transforming this complexity into a competitive advantage.
In the context of the energy transition, the question arises: could I be the solution to the main challenges of industries? A survey conducted by ABB to those responsible for decision -making in European electrification has highlighted the difficulties in energy management, such as the combination of multi -sources energy and the provision and management of the demand.
Energy management solutions based on AI address a complex network of interconnected variables both inside and outside industrial facilities. Current analytical tools can predict from the energy demand for production and energy prices to climate and the generation of renewable energy. “Companies that use analytical tools of AI will obtain the best results in resilience, operating costs and decarbonization,” says a spokesman for ABB Electrification.
Demand management: efficiency and cost savings
The first step towards energy savings is to understand when and how energy is used. The solutions based on AI help industrial facilities to better understand this process, reducing consumption and effectively managing demand peaks. For example, ABB Electrification collaborates with NDUSTRIAL, a startup whose Energy Management solution based on INDUSTRIAL CUSTOMERS A precise visibility of the energy intensity of its production.
Energy management promoted by the help from industries to overcome
By integrating data on the weather, market rates, equipment performance and industrial processes results, companies can analyze, optimize and predict their energy consumption and production costs. This allows real -time decisions and automating the specific controls of the industry, the installation or the production line that is being optimized.
For its part, Genan, the largest mechanical tire recycling company in the world, saved hundreds of thousands of dollars thanks to the automated NDUSTRIAL response to energy prices. Genan could quickly stop production when energy prices exceeded an established threshold.
Transforming energy management With ia
Industrial plants face numerous decisions by supplying their operations: how to use the energy generated by renewables, when to load or download battery storage and when to buy or sell electricity to the network. With the right strategy, companies can save energy costs and even generate income.
IA -based solutions apply climate prediction models, energy market prices and production needs to design real -time strategies for energy supply management. An example is ABB electrification investment on the Gridbeyond -based platform.
It is expected that the advantages of energy management based on the increase as it will continue to be adopted and the prediction models benefit from a greater number of data.
