5. trend dynamics
The following trend dynamics show the most striking changes in the assessments of the overall perspective between the two online surveys in 2021 and 2023.
The INFLUENCE of the two trends big data analytics and digital literacy was assessed as medium in the current survey. These trends therefore recorded the greatest reduction in the influence rating. In contrast, the influence of the trends rebound effects and role change of transmission and distribution system operators were rated as high and therefore increased the most in this criterion of all the trends considered.
In 2021, the trends electromobility and charging infrastructure as well as digital twin were rated as having a high PRIORITY for their own company or organization. In the new 2023 survey, the trends were only given a medium priority. In contrast, the trends of change in energy market design, rebound effects, mindset resilience and energy, climate, nature and species protection in harmony have increased in priority rating.
The two trends of liquefied natural gas and blockchain were now rated earlier as INNOVATION DRIVERS . This is consistent with the fact that the two surveys were conducted around a year and a half apart. This means that liquefied natural gas is seen as an innovation driver within the next three years, with blockchain continuing to be rated as an innovation driver in the next three to six years. In comparison, the assessment of the innovation-driving effect for the trends predictive analytics and predictive maintenance, system integration of renewable energies and augmented reality has shifted back in time. These three trends are estimated to be drivers of innovation in the next three to six years.
6. Conclusion
The Energy Trend Radar is an innovation management tool for the Bavarian energy sector from the field of trend scouting. The trend assessments are based on a qualitative expert survey and are not a representative survey of the industry's opinion, but they do enable the industry players to draw their own conclusions with regard to their individual business activities and to develop sustainable strategies.
In the Energy and Construction Innovation Network of Bayern Innovativ GmbH, the Energy Trend Radar is used as a valuable tool for aligning thematic network work. The processing of the results and the analysis of trend dynamics enable the selection of targeted network activities to strengthen the innovative power of the Bavarian energy landscape. The following are examples of the innovation network's own derivations:
- The acceleration of the energy transition has a major impact on the energy sector according to both the scientific and business communities. The scientific perspective rates the trend as a high priority in their own institution, while participants from the business sector even prioritize it as very high. The reduction of regulatory hurdles, knowledge transfer and networking between business, science and politics are important building blocks for accelerating the energy transition - areas of activity in which the Energy and Construction Innovation Network is already active on a daily basis.
- Energy storage and management are rated as high to very high both in terms of their impact on the energy landscape and the priority of the experts involved. For a sustainable and efficient design of the future energy landscape with innovative battery technologies, the Energy and Construction Innovation Network of Bayern Innovativ GmbH is driving forward the initiation of a Bavarian battery network.
- Cybersecurity is given a very high priority in the economic perspective. Suitable network activities are needed to provide possible assistance with regard to options and points of contact for system security. The Energy and Construction Innovation Network is planning a webinar on the topic of cybersecurity in the energy sector for 2024 in order to bring small and medium-sized companies closer to the topic and provide initial impetus.
- The rebound effects trend has achieved a significant increase in the overall impact assessment. The aim here is to promote knowledge transfer and initiate cooperation through networking for more energy efficiency measures and at the same time address causes and solutions to avoid rebound effects. The increased activity of the Energy and Construction Innovation Network in the formation of energy efficiency networks as part of the Bavarian Energy Efficiency Network Initiative (BEEN-i) is just one example of this (Bayern Innovativ GmbH, n. d. e.).