Abstract
One of the most challenging areas of Future Smart Cities Research is the Smart Energy domain. Critical issues related to optimization, provision of smart customizable networks and sophisticated computational techniques and methods enabled by artificial intelligence and machine learning need further investigation. The renewable energy (RE) is a powerful resource for the future global development in the context of climate change and resources depletion. Artificial intelligence (AI) implies new rules of organizing the activities in order to respond to these new requirements. It is necessary to improve the design of the energy infrastructure, the deployment and production of RE in order to face the multiple challenges that will affect the sector’s growth and resilience.. In this research work we exploit the recent developments on the AI adoption for RE sector in European Union (EU). In this respect, we analysed (i) the efficiency of the transformation processes of the RE within the energy chain from Gross Inland Consumption to Final Energy Consumption, (ii) its implications on the structure of renewable energy by source (solar, wind, biomass etc.), (iii) the labour productivity in RE sector compared to the economy as a whole and its correlation with investments level, (iv) the implication of the adoption of AI for RE towards Future Smart Cities Research. The main contribution of this research is the development of a framework for understanding the contribution of AI in the RE sector in Europe. Another bold contribution of this work is the discussion of the implications for Future Smart Cities Research and future research directions.
Highlights
The issues related to the integration of sophisticated artificial intelligence technology to Smart Energy systems and grids, requires a multi-fold understanding of computational, economic and social issues
RESEARCH MODEL The literature on renewable energy (RE) sector and the role of Artificial intelligence (AI) lead to concerns related to these fields which were included in the objectives of our research
To address the first objective of our research and to identify implications on energy management, we identify the following questions: 1) What are the changes in Gross Inland Consumption, how extended is the use of RE and how has evolved the efficiency of the transformation processes of the RE within the energy chain from Gross Inland Consumption to Final Energy Consumption?
Summary
The issues related to the integration of sophisticated artificial intelligence technology to Smart Energy systems and grids, requires a multi-fold understanding of computational, economic and social issues. This kind of socio-technical platform and integration needs an initial definition of the domain and a well-grounded specification of the research problem. Processes associated with the changes, and the literature describing the resulted challenges were enriched. Sophisticated disruptive technologies set new challenges for the investigation of sustainable models of economic development. The research issue of Energy management is one of the core application areas for both smart cities research and disruptive technologies adoption. In our research study this investigation is a key research objective
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