Associates Area
The energy transition is an urgent and indisputable need, but it faces complex challenges. Since the 1970s, the energy sector has led the adoption of digital technologies to improve the management and operation of networks. Today, with the growing importance of data, it is crucial to rethink how this information can be strategically used to accelerate the energy transition. While significant investments have been made in digital technologies to improve the efficiency, reliability and sustainability of energy systems, including Big Data and Artificial Intelligence (AI), we are still unable to fully see the potential of these investments.
The International Renewable Energy Agency (IRENA) highlights that although investments in renewable energy are increasing, there is a significant gap between current efforts and the measures needed for a sustainable energy transition. IRENA's World Energy Transitions Outlook 2023 highlights the urgent need to increase investment in renewable energy and infrastructure to meet the 1.5°C climate objective. Many companies have prioritized physical infrastructure like smart grids and electric vehicle chargers, neglecting software and data management systems essential for transforming raw data into actionable insights. For effective digitalization, it is essential to balance investments in hardware and software, implementing a clear strategy for data management and analysis.
Furthermore, extracting value from data is an imperative recognized by industry executives, but the operationalization of this knowledge is still progressing slowly, resulting in missed opportunities for new revenue streams. Internal innovation teams lead this process in the search for a data-driven digital business model, recognizing that digitalization can mean different things: hardware, software or the knowledge generated by the combination of both. To accelerate this process, acceleration programs, strategic partnerships and collaborations with academic institutions are crucial. These approaches reveal that some companies have already realized that digitalization goes beyond physical infrastructure, exploring different possibilities with the increasing availability of data to develop new and more efficient business models.
In the future, the digitalization of the energy sector promises to be even more transformative, with the large-scale adoption of emerging technologies, such as Artificial Intelligence, which will allow us to anticipate energy needs and potential equipment failures, and optimize the performance of production assets. energy in real time. The integration of these technologies in the first phase will create challenges, which can be as simple as the user's ability to understand the new layer of information generated. At the same time, they will have multiple algorithms at their disposal with the guarantee of solving all daily problems, and the difficulty will be in understanding which are the best and how to use them. The best algorithm ecosystem will be the one capable of integrating and making algorithms cooperate with each other in the most relevant way for each situation, providing the best information for each user. On the other hand, Cloud Computing and Edge Computing will allow faster and more efficient data analysis, processing information directly at the source location; and, business models such as Energy as a Service (EaaS), based on the continuous supply of energy and optimization of consumption through data, are also gaining prominence.
Digitalization in energy must be seen as an integrated strategy, where hardware and software work in harmony to transform raw data into valuable, operational insights. Encouraging companies and industry leaders to adopt this innovation mindset and strategically invest in digitalization is essential to accelerating the energy transition. By integrating data effectively, we can create energy systems that not only meet current needs, but are prepared for future challenges and opportunities, paving the way to a sustainable and efficient future for all.